Summer Institute on Climate Information for Public Health 2010

TR10-11 technical report:

Summer Institute on Climate Information for Public Health 2010Gilma Mantilla, Michelle Stanton, laurence cibrelus

Summer Institute 2010 | Final Report

IRI Technical Report 2010 Summer Institute on Climate Information for Public Health

Summary of the Climate Information for Public Health Training Course

Palisades, New York

May 17- 28, 2010

Gilma Mantilla

Michelle Stanton

Laurence Cibrelus

International Research Institute for Climate and Society

The Earth Institute at Columbia University

Palisades, New York, 10964, US

Organized in partnership with

Mailman School of Public Health, Columbia University

Center for International Earth Science Information Network, Columbia University

Report available online at:

» http://iri.columbia.edu/publications/id=1011

With trainees’ sponsorship by Spanish Meteorological Office

Google.org

Center for Disease Control Uganda

Center for Disease Control Kenya

Deutsche Gesellschaft für Technische Zusammenarbeit Tunisia

Nigerian Meteorological Office

U.S. Agency for International Development Ethiopia

Malaria Research Institute India

National Oceanic and Atmospheric Organization’s West Coast Center for Oceans and Human Health


Contents

Executive Summary 3

Acronyms 7

Acknowledgements 8

Team Members 10

Introduction 11

Participants 12

The CIPHAN Web-page, the CIPHA Newsletter and the CIPH Alumni Network 13

Course Overview 15

• Learning Goals by Module 19

• Sessions Summaries by Module 21

Daily Quiz and Personal Projects 41

• Quiz Questions by Module 41

• Trainees Personal Projects Guidelines and Summaries 41

• Project Summaries 43

Course Awards 50

Course Evaluation 51

Conclusions 52

Recommendations 54

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Executive Summary

Executive SummaryNow that the world’s attention is focused on climate variability and climate change adaptation, it is essential, not only for public health communities, but also for planners in central government, to understand the role climate plays in driving disease burden and impacting economic growth. Public health emerges as the final common pathway for all impacts of climate variability and climate change on individuals as well as societies.

As a contribution to this process, The International Research Institute for Climate and Society (IRI), in partnership with the Center for International Earth Science Information Network (CIESIN) and the Mailman School of Public Health (MSPH) at Columbia University initiated this two-week course in 2008. Building on the response of our 2008 - 2009 alumni, and a great demand from the climate and health community the 2010 Summer Institute on Climate Information for Public Health (SI10) was designed to engage professionals who play a key role in the operational decision-making for climate-sensitive diseases in identifying and evaluating appropriate use of climate information. SI10 was held at Columbia University’s Lamont-Doherty Campus in Palisades, New York, between May 17th and May 28th, 2010.

Participant selection

The IRI received 134 applications to SI10, spanning the globe, with Africa leading in number of application submis-sions. By region, 78 applications were received from Africa, 24 from Asia, 13 from Europe, 11 from North America, 7 from Latin America and the Caribbean, and 1 from the Southwest Pacific. Of the applications received, the majority of applicants reported holding positions of program management or directorship (22). Also well repre-sented amongst applicants were members of academia, including graduate-level students (20) and professors of varying experience (16). Researchers and scientists followed (15), along with project officers (14), meteorologists (8), and others.

After removing applications that were incomplete or who demonstrated a lack of relevance to the course as currently set, applicants for SI10 were selected based on: (i) Funding ability, (ii) Strategic opportunity for engagement with key partner organization via an institutional support, and (iii) Personal characteristics, skills, grasp of the central issues expressed on the Statement of Interest, as well as ambitions. Candidates were ranked depending on the number and priority of criteria they met. At the end of the selection process, thirteen professionals from ten countries in the Americas, Asia and Africa were selected to participate in SI 10. Participants hailed from Ethiopia (4), Kenya (1), Uganda (1), Burkina Faso (1), Niger (1), Tunisia (1), India (1), China (1), Nigeria (1) and the United States (1). Three trainees worked in the climate or meteorological sector, and the remaining nine worked either in the public health sector or in health research fields. All trainees were key stakeholders in decision-making for health-care planning, evaluation or control of climate-sensitive diseases.

Course Overview

The course was designed to help participants (i) understand the role climate plays in driving the infectious disease burden and public health outcomes, (ii) use new tools for accessing climate and epidemiological data, for analyzing and mapping using the IRI Data Library and other Geographic information Systems (GIS) and (iii) understand management and data integration as an opportunity to improve the decision making process in public health.

The structure of the course provided a balance of concepts and methods from the health and climate communities using an approach deeply oriented toward methodology, gathering and using evidence for decision-making in order

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Executive Summary

for the trainees to get in-depth knowledge and skills in decision-making for health-care planning of climate-sensitive diseases. The concepts presented during the morning lectures were reinforced by lunch seminars, the panel discussion, afternoon hands-on exercises using the on-line version of the IRI Data Library and Map Room, the daily quiz, the summaries of the key messages discussed on the previous day given by the trainees as well as the group discussion following the summary.

Thirty-two facilitators (including lecturers and organizers), supported by 13 information technology (IT), admin-istrative, communication professionals and SI alumni, led the participants through the following modules: (i) Basic Concepts in Public Health and Climate, (ii) Sources and Tools for Analyzing Climate and Public Health Data and (iii) Use of Climate Information in Decision-Making for Climate-Sensitive Diseases. Additionally, a panel discus-sion involving international keynote speakers from the Centers for Disease Control and Prevention (CDC) and the United Kingdom Meteorological Office was hosted by the MSPH at the Medical Campus of Columbia University.

Throughout the course, trainees were assigned to develop a personal climate and public health project that would be relevant to their own institution and area of work. The trainees projects addressed issues as varied as “Temperature and Mortality in Beijing”, “Relationship between rainfall and dengue in Delhi”, “Typhoid Fever and Climate in Uganda: Is there a link?”, “Relationships between climate and year-to-year variability in meningitis outbreaks: a case study in Burkina Faso and Niger” or “Malaria Risk Mapping in Oromia, Ethiopia”. In order to offer the trainees the opportunity to share their learning experience with co-participants, facilitators, SI alumni and the Climate Information for Public Health (CIPH) network, these projects were presented on the last day of the course as posters, accompanied by a 300-word summary.

Several awards acknowledged the following outstanding performances: Best Poster, Excellence in Teaching, Involve-ment, active interaction and timeliness of a course facilitator during the pre course development, Best IT innovation, Best logistic support, and Originality in the development of the course curriculum.

The Climate Information for Public Health Action Network

The Climate Information for Public Health Action Network (CIPHAN) Web platform supported all course materials. As developed using the open-source Moodle1 software, CIPHAN provides public health professionals with knowledge, methodologies, tools, and data to better manage climate sensitive diseases toward improving health outcomes. It acts as a web portal to guide the learner towards other sources of information, as well as a source of learning resources, such as educational modules and exercises. This site’s library also contains a directory of published material to give the reader opportunity for further investigation. The CIPHAN Web-page also links to the IRI Data Library and Map Room.

During the course, trainees were also introduced to the contribution they are strongly encouraged to have within the CIPH Alumni Network and the Climate Information for Public Health Action (CIPHA) Newsletter, which provides updates on the latest developments within the CIPH network, including the activities of alumni and facilitators, brief meeting reports, news from the health and climate community, and opportunities for collaboration.

1 Moodle is a Course Management System, also known as a Learning Management System or a Virtual Learning Environ-ment. It is a free Web application that educators can use to create effective online learning sites. Adapted from: http://moodle.org/

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Executive Summary

Course Evaluation

The course evaluation process was designed to highlight any gaps in the contents and delivery of the course material, and further to provide the organizers with an insight into how changes in the course since SI 09 were received. Overall, the evaluation indicated that the trainees found the training to be very valuable, and provided them with knowledge that could be incorporated into their future work. Trainees were impressed with the commitment of the facilitators, organizers and support staff who were involved in SI 10, and equally the facilitators enjoyed engaging with the trainees and sharing in their enthusiasm towards combining the climate and health communities.

In addition to praise for the training course, the evaluation process also highlighted areas where the training could be improved. During the course the trainees were encouraged to apply the practical skills they were learning to their own data. The trainees had a great deal of praise for this learning technique, however were a little frustrated that the scheduling of the course didn’t allow them to immerse themselves in this task as much as they would’ve liked. Further, a common recommendation made by the course facilitators and organizers was that the contents of the course be scaled back in order to focus more on the practical aspects of the training.

Trainees Financial Support

Financial support to the course trainees was provided by the Spanish Meteorological Service (AEMET), Google.org, CDC Uganda, CDC Kenya, Gesellschaft für Technische Zusammenarbeit (GTZ) Tunisia, the Nigeria Meteorological Office, USAID Ethiopia, the Malaria Research Institute of India and the National Oceanic and Atmospheric Administration (NOAA)’s West Coast Center for Oceans and Human Health.

“... The structure of the training course is excellent: comprehensive in scope; good teachers; adequate learning materials and methods. It should yield excellent results

after the two week period of training”

Ulisses Confalonieri, member of the IRI’s International Scientific and Technical Advisory Committee and SI facilitator

“The hands-on experience we got in the practical sessions exceeded my expectations”

SI 10 trainee

“Exposure to the Data Library with hands-on experience and availability of internationally renowned expertise in all aspects of climate and health at the Summer

Institute is the uniqueness of the course”

SI 10 trainee

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Executive Summary

“The faculty, facilitators and organizers of the course deserve commendation”

SI 10 trainee

“By the way of the Summer Institute, I was able to expose [to new concepts] people who can shape a whole weather service, who can contact a public health service in

their country and make a big difference”

SI 08 trainee

Participants and Facilitators of SI 10. Francesco Fiondella/IRI

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Acronyms

AcronymsAFRO-WHO World Health Organization Regional Office for AfricaAMS American Meteorological SocietyCDC Centers for Disease Control and PreventionCHWG Climate and Health Working GroupCIESIN Center for International Earth Science Information NetworkCIPH Climate Information for Public HealthCIPHA Climate Information for Public Health Action, newsletterCIPHAN Climate Information for Public Health Action NetworkCPT Climate Predictability ToolCRED Center for Research on Environmental Decision MakingCRM Climate Risk ManagementENSO El Niño-Southern OscillationEPA U.S. Environmental Protection AgencyEWS Early Warning SystemFETP Field Epidemiology Training ProgramGIS Geographic Information System GPS Geographic Position SystemGTZ Deutsche Gesellschaft für Technische ZusammenarbeitIPCC Intergovernmental Panel on Climate ChangeIRI International Research Institute for Climate and SocietyIT Information TechnologyLSHTM London School of Hygiene and Tropical MedicineMDG Millennium Development GoalMERIT Meningitis Environmental Risk Information TechnologiesMEWS Malaria Early Warning SystemMCQ Multiple Choice QuestionsMoH Ministry of HealthMSPH Mailman School of Public Health NOAA National Oceanic and Atmospheric AdministrationNGO Non Governmental OrganizationNRDC Natural Resources Defense CouncilPAHO-WHO Pan-American Health Organization - World Health OrganizationQ&A Questions and AnswersSI Summer Institute on Climate Information for Public HealthUK United KingdomUSAID United States Agency for International DevelopmentWHO World Health OrganizationWMO World Meteorological Organization

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Acknowledgements

AcknowledgementsThe organizers of SI10 and the authors of this report would like to acknowledge the following persons for the truly dedicated support during SI10:

Scott Wood, from the Climate and Society Master Program at Columbia University, for carefully helping on building up the SI10 documentation before course begun and for setting up the application report.

Jason Rodriguez, from the IRI, for designing the document.

And all the trainees’ sponsors, facilitators, support staff and trainees of SI10 for contributing to the success of the course:

Sponsor

Spanish Meteorological Office (AEMET)Google.orgCDC Uganda CDC KenyaGTZ Tunisia

Nigerian Meteorological OfficeUSAID Ethiopia Malaria Research Institute IndiaNOAA’s West Coast Center for Oceans and Human Health

Support Staff

Baaba Baiden, IRI

Ann Binder, IRI

Jessie Carr, MSPH

Michael Dervin, IRI

Francesco Fiondella, IRI

Rise Fullon, IRI

Saleh Ghani, CIESIN

Chihuei Lu, IRI

Luciana Mendiola, Climate and Society Program, Columbia University

Althea Murillo, IRI

Barbara Platzer, IRI

Jason Rodriguez, IRI

Kelli Stewart, LDEO

Jeffrey Turmelle, IRI

Cathy Vaughan Green, IRI

Sandy Vitelli, IRI

Scott Wood, Climate and Society Program,

Columbia University.

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Acknowledgements

Facilitators

Walter Baethgen, IRI

Tony Barston, IRI

Eric Bertherat, WHO

Mark Becker, CIESIN

Michael Bell, IRI

Menno Bouma, LSHTM

Pietro Ceccato, IRI

Ulisses Confalonieri, Oswaldo Cruz Foundation

Laurence Cibrelus, IRI

Stephen Connor, IRI

Remi Cousin, IRI

Ashley Curtis, IRI

John del Corral, IRI

Peter Diggle, Lancaster School of Health and Medicine

Dia El Naiem, University of Maryland

Wayne Elliot, UK Meteorological Office

Francesco Fiondella, IRI

Patricia Graves, the Carter Center

Patrick Kinney, MSPH

Kim Knowlton, MSPH and NRDC

Richard Luce, CDC

Bradfield Lyon, IRI

Stephen Morse, MSPH and USAID

Ousmane Ndiaye, IRI

Gilma Mantilla, IRI

Sabine Marx, CRED

Simon Mason, IRI

Judy Omumbo, IRI

Carlos Perez, IRI

Andrew Robertson, IRI

Sabine Marx, CRED

Simon Mason, IRI

Judy Omumbo, IRI

Carlos Perez, IRI

Andrew Robertson, IRI

Daniel Ruiz, IRI

Wendy Marie Thomas, AMS

Madeleine Thomson, IRI

Sylwia Trzaska, IRI

Pascal Yaka, Burkina Faso Meteorological Office

Steve Zebiak, IRI.

Trainees Betty Abang, CDC, Office of Uganda

Wakgari Amente, Addis Ababa University

Yilma Bekele, Addis Ababa University

Ali Bouattour, Tunisia Pasteur Institute

Ramesh Chand Dhiman, Indian Council of Medical Research

Abenet Girma Dessalegn, CHWG of Ethiopia

Stephanie Kay Moore, NOAA

Tiantian Li, CDC of China

Ayub Shisia Manya, Ministry of Health and Sanitation of Kenya

Mouhaimouni Moussa, Niger Meteorological Office

Hiwot Namaga, USAID, Office of Ethiopia

Andrew Oniarah, Nigeria Meteorological Office

Pascal Yaka, Burkina Faso Meteorological Office.

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Team Members

Team Members

Organizers

Gilma Mantilla, Laurence Cibrelus and Madeleine Thomson, from the IRI, Mark Becker, from CIESIN and Patrick Kinney, from the MSPH, were responsible for the organization of SI10.

Development of the course agenda and training materials

The team was led by Laurence Cibrelus, from the IRI. Gilma Mantilla, also from the IRI, oversaw the development of the agenda and the training materials.

Logistic team

The following persons led the logistics of SI 10: Ann Binder, Francesco Fiondella, Mike Dervin, Baaba Baiden, Jeffrey Turmelle, Althea Murillo, Jason Rodriguez and Sandy Vitelli, from the IRI. Jessie Carr from MSPH and Luciana Mendiola from the Climate and Society Master Program also supported SI10 and the MSPH panel discussion.

Evaluation group

The following persons were responsible for developing and overseeing the course evaluation: SI 08 alumna Michelle Stanton from the Lancaster School of Medicine, Gilma Mantilla and Laurence Cibrelus, from the IRI.

Poster Prize Committee

The following team evaluated the posters of the SI10 trainees and attributed the Best Poster Prize: Mark Becker, CIESIN, Ann Binder, IRI, Carolyn Mutter, IRI, Andrew Robertson, IRI and Wendy Marie Thomas, AMS.

Authors of this report

Gilma Mantilla was the general coordinator of SI10.

Michelle Stanton was a SI10 facilitator conducted the course evaluation.

Laurence Cibrelus was a SI10 facilitator and conducted the development of the course curriculum.

Detailed biographies of the facilitators and support staff are available in a separate appendix.

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Introduction

IntroductionThe International Research Institute for Climate and Society (IRI)/Earth Institute at Columbia University is the premier global research and capacity building institution focused on the use of climate information in public health, agriculture and water decision-making. IRI is a collaborating center with WHO-PAHO on climate sensitive diseases and has active international partnerships concerning malaria, meningococcal meningitis, Rift Valley Fever and other diseases. IRI’s areas of interest also include dengue, diarrheal diseases, Kala-azar (leishmaniasis) and conditions associated with flood, drought and disasters.

The mission of the IRI is to enhance society’s capability to understand, anticipate and manage the impacts of climate in order to improve human welfare and the environment, especially in developing countries. The IRI conducts this mission through strategic and applied research, education, capacity building, and by providing forecasts and information products with an emphasis on practical and verifiable utility and partnership.

• In particular, the public health commitment of the IRI involves developing, with partners, a knowledge system based on three main components:

• Understanding the community of practice, identifying the needs, and collaborating with Ministries of Health to work at the local to regional levels;

• Developing tools to monitor, survey and predict disease epidemics based on climate data, patterns and trends

• Building capacity through the education and training of public health professionals on the relationship between climate and health.

The IRI is committed to converting knowledge gained into training and education products which are then commu-nicated in person and in electronic media to expand the basis for learning about climate risks and introducing concepts into a decision making process of different sectors. The Summer Institute on Climate Information (SI) was created in 2008 to meet this need and achieve the Public Health goals of the IRI, in partnership with the Columbia University Center for International Earth Science Information Network (CIESIN) and Mailman School of Public Health (MSPH).

This report summarizes Summer Institute 2010 on Climate Information for Public Health (SI10). It describes the content and the evaluation of the course with summaries of each training module. It also introduces the participants – organizers, trainees, lecturers and facilitators – who contributed to the success of SI 10.

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Participants

Participants

Selection Process

The IRI received 134 applications for this year’s Climate Information for Public Health Action Summer Institute. Applicants spanned the globe, with the continent of Africa leading in number of application submissions. By region, 78 applications were received from Africa, 24 from Asia, 13 from Europe, 11 from North America, 7 from Latin America and the Caribbean, and 1 from the Southwest Pacific. Of the applications received, the majority of applicants reported holding positions of program management or directorship (22). Also well represented amongst applicants were members of academia, including graduate-level students (20) and professors of varying experience (16). Researchers and scientists followed (15), along with project officers (14), meteorologists (8), and others.

Applicants for the 2010 Summer Institute were selected based on a range of criteria. In order to facilitate the selection process of the pool of 134 applicants, an initial shortlist was compiled which appropriately narrowed down the pool of potential candidates. This was accomplished by removing applicants who did not submit a complete application on line, had previously been trained, and who demonstrated a lack of relevance to the course as currently set (e.g., lawyers or volunteers). Following the development of the short list, the following criteria were applied to each of the remaining candidates.

Criteria Applied to Each Candidate

Criteria Criteria Description

1 Funding: Self-funding is highly recommended

2 Strategic opportunity for engagement with key partner organization via an institutionally supported individual

3 Personal characteristics, skills, grasp of the central issues expressed on the Statement of Interest, and ambitions

Candidates were then ranked and selected according to the following method (1 = Highest Priority, 4 = Lowest Priority). Criteria Applied to Rank the Candidates

Priority Rating Criteria Required

1 Meets all three criteria

2 Meets criteria 1 and 2 or 3

3 Meets criteria 2 and 3

4 Meets one of the criteria listed

The full application report is available from a separate appendix.

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The CIPHAN Web-page, the CIPHA Newsletter and the CIPH Alumni Network

Accepted Trainees

At the end of the selection process, thirteen professionals from ten countries in the Americas, Asia and Africa were selected out of the 134 applicants to participate in SI10.

Participants hailed from Ethiopia (4), Kenya (1), Uganda (1), Burkina Faso (1), Niger (1), Tunisia (1), India (1), China (1), Nigeria (1) and the United States (1). Three trainees worked in the climate or meteorological sector, and the remaining nine worked either in the public health sector or in health research fields. All trainees were profes-sionals who play a key role in decision-making for health-care planning, evaluation or control of climate-sensitive diseases.

The organizers of the course were very much honored to welcome the following professionals to SI10: Betty Abang from the CDC, Office of Uganda, Wakgari Amente from Addis Ababa University, Yilma Bekele from Addis Ababa University, Ali Bouattour from the Tunisia Pasteur Institute, Ramesh Chand Dhiman from the Indian Council of Medical Research, Abenet Girma Dessalegn from the CHWG of Ethiopia, Stephanie Kay Moore from NOAA, Tiantian Li, from the CDC of China, Ayub Shisia Manya from the Ministry of Health and Sanitation of Kenya, Mouhaimouni Moussa from the Niger Meteorological Office, Hiwot Namaga from the USAID Office of Ethiopia, Andrew Oniarah from the Nigeria Meteorological Office, and Pascal Yaka from the Burkina Faso Meteorological Office.

Detailed biographies of the SI10 trainees are provided in a separate appendix.


SI10 Facilitator Brad Lyon, IRI, and SI10 Participant Ramesh Chand Dhiman, National Institute of Malaria Research at the Indian Council of Medical Research, interact during the poster session. Francesco/IRI

For the first time since the imple-mentation of the Summer Institute, the Climate Information for Public Health Action Network (CIPHAN) Web platform supported all course materials. Trainees were also introduced to their expected role within the CIPH Alumni Network and the Climate Information for Public Health Action (CIPHA) Newslet-ter.

A lot of knowledge remains indeed to be built in the area of climate and public health and the field efficiency of the new approaches implemented is yet to be assessed. For these

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reasons, it is critical that networking and interaction platforms allowing climate and public health professionals to communicate and share their knowledge and experience exist.

The CIPHAN platform was developed to respond to this need. It provides public health professionals with knowledge, methodologies, tools, and data to better manage climate sensitive diseases toward improving health outcomes. CIPHAN acts as a web portal to guide the learner towards other sources of information, as well as a source of learning resources, such as educational modules and exercises. This site’s library also contains a directory of published material to give the reader opportunity for further investigation.

Front page of the CIPHAN Web-platform.

Similarly the CIPHA Newsletter was created to provide updates on the latest developments within the CIPH network, including the activities of alumni and facilitators, brief meeting reports, news from the health and climate community, and opportunities for collaboration.

Trainees from SI10, as well as from the previous summer institutes and in-country CIPH trainings, are expected to contribute to development and sustainability of these platforms and associated CIPH projects.

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Course Overview

Course OverviewWeek one: May 17-21, 2010

Mon, 17-May Tues, 18-May Wed, 19-May Thr, 20-May Fri, 21-MayModule Basic Concepts in Pub-

lic Health and ClimateBasic Concepts in Pub-lic Health and Climate

Sources and Tools for Analyzing Climate and Public Health Data



Morning 9:00am-12:30pm

9:00-9:15am Welcome Stephen Zebiak

9:00-9:30am 10min Quiz 20 min Summary of the Previous Day by a Participant, followed by Open Discussion with the Lecturers Selection of the Rap-porteur for the Next Day




9:15-9:30am Introduction to Sum-mer Institute 2010 and to the CIPHA Network Madeleine Thomson, Patrick Kinney, Mark Becker

9:30-9:45am Overview of the Course Gilma Mantilla

9:30-10:30am Introduction to Climate and Climate Information Sylwia Trzaska

9:30-10:15am Climate and Vector-Borne Disease Dynamics Madeleine Thomson

9:30-10:15am Remote Sensing as a Tool to Manage Envi-ronmental Data Pietro Ceccato

9:30-10:30am, Field Practice Using GPS, GIS and Google Maps for Public Health Part I Mark Becker

9:45-10:15am Introduction of the Participants and Facilitators Selection of the Rap-porteur for the next day Madeleine Thomson

10:15-10:30am Coffee Break



10:15-11:00am Introduction to Clus-ter Analysis Andy Robertson


10:30-11:15am Climate Risk Manage-ment and Develop-ment Walter Baethgen

11:00-11:45am Core Concepts in Public Health and Epidemiology Judy Omumbo

10:30-11:00am, CIESIN Lab Malaria Vector Distri-bution and Rainfall Judy Omumbo

10:45-11:45am, Field Practice Using GPS, GIS and Google Maps for Public Health Part II Mark Becker

11:15-12:00pm Climate, Vulnerability and Health: Interna-tional and National perspectives Ulisses Confalonieri

11:00-12:00pm, CIESIN Lab Exploratory Time Series Analysis Andy Robertson

11:00-12:00pm, Monell Auditorium Special Climate Brief-ing Tony Barston -- coffee break will be served at the Monell Auditorium --

11:45-12:30pm Meningitis Environ-mental Risk Infor-mation Technology (MERIT) Madeleine Thomson

12:00-12:30pm Climate Risk Manage-ment in Health Madeleine Thomson

11:45-12:30pm Public Health Surveil-lance and Opportuni-ties to use Climate Information Richard Luce

12:00-12:30pm, CIESIN Lab Malaria Mapping and the Climate Suit-ability for Malaria Transmission Tool in the Health Map Room Judy Omumbo, Remi Cousin

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Course Overview

Week one: May 17-21, 2010

Mon, 17-May Tues, 18-May Wed, 19-May Thr, 20-May Fri, 21-MayLunch 12:30-2:00pm

Welcome Lunch Lunchtime seminar History of Climate and Malaria - Does Causal-ity Matter?

Menno Bouma

Lunch-time seminar Infectious Diseases and Climate: Influenza Seasonality and Early Warning

Stephen Morse

Nature Walk Cathy Vaughan, Ashley Curtis

Afternoon 2:00-5:30pm CIESIN Lab

2pm-3:30pm Overview of the IRI Data Library Michael Bell

2:00-4:00pm Summarizing climate and health data using descriptive statistics and map tools Michael Bell

2:00-3:00pm Open practice with the Data-Library using participants’ datasets

2:00-3:00pm Remote Sensing Tools in the Health Map Room Part I Pietro Ceccato

2:00-3:00pm Lagged Correlation of Rainfall with Malaria Incidence Michael Bell

3:30-3:45pm Coffee Break


3:00-4:00pm Transfer to the Mail-man School of Public Health



3:45-5:15pm Understanding Data and Data Quality Control John del Corral, Michael Bell, Remi Cousin

4:15-5:00pm Applications using the Participants’ Datasets John del Corral, Michael Bell, Remi Cousin

4:00-6:00pm

Mailman School of Public Health Panel Discussion: Creating a “Climate Smart” Global Health Community: How do we Commu-nicate? Who do we Train? Opening Speech: Dean Linda Fried, Mailman School of Public Health Facilitator: Madeleine Thomson, IRI Panelists: • Elliot Wayne, Met Off ice UK • Richard Luce, CDC/Field Epidemiology Training Programs. Resident Advisor Ethiopia • Patrick Kinney, Mailman School of Public Health

3:35-4:45pm Remote Sensing Tools in the Health Map Room Part II Pietro Ceccato

3:15-4:45pm K-Means Cluster Analysis Exercise: Malaria Seasonality Pietro Ceccato

5:00-5:15pm Open space for prac-tice with the Data-Library or meetings with facilitators



5:15-5:30pm Daily Evaluation of the Course




Evening Reception at the Mail-man School of Public Health

Palisades Mall Tour

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Course Overview

Week Two: May 24-28, 2010Mon, 24-May Tue, 25-May Wed, 26-May Thr, 27-May Fri, 28-May

Module Use of Climate Infor-mation in Decision-Making for Climate-Sensitive Diseases

Use of Climate Infor-mation in Decision-Making for Climate-Sensitive Diseases




Morning 9:00am-12:30pm






9:30-10:45am Understanding Pre-dictions and Projec-tions in Climate Sylwia Trzaska

9:30-10:30am Climate Change, War and Disease Dia El Naiem

9:30-10:15am Temperature Trends in the Highlands of East Africa Bradf ield Lyon

9:30-10:15am Climate Change and Human Health: Current Impacts and Future Risks Patrick Kinney

9:30-10:15am Open space to work on projects Part I






11:00-11:45am Building Sustain-able Partnerships to Improve Meningitis Surveillance and Response: the MERIT Initiative

10:45-11:30am Malaria Early Warning and Early Response Stephen Connor

10:30-11:15am Linking ENSO and Society Tony Barston

10:30-11:15am Heat Waves in the USA from the Cli-mate Perspective Bradf ield Lyon

10:30-12:00pm Open space to work on projects Part II

11:45-12:30pm Spatio-Temporal Modeling of Men-ingitis Peter Diggle

11:30-12:30pm Integrated Surveil-lance and Control System for Malaria in Colombia Daniel Ruiz

11:15-12:30pm Climate Change and Vulnerability Carlos Perez

11:15-12:00pm Heat Waves and Public Health: a USA Case Study Kim Knowlton

12:00-12:30pm Group Discussion on Heat Waves

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Course Overview

Week Two: May 24-28, 2010Mon, 24-May Tue, 25-May Wed, 26-May Thr, 27-May Fri, 28-May

Lunch 12:30-2:00pm

Lunch break Celebrity Walk Barbara Platzer

Lunch break Lunch break Lunch break

Afternoon 2:00-5:30pm CEISIN Lab

2:00-3:30pm Using GIS to Explor-ing the Links between Poverty and Natural Hazards Part I Mark Becker

2:00-3:30pm Epidemic Detection and Monitoring using Thresholds Part I Patricia Graves

2:00-4:00pm Climate Prediction for Weather Forecast Skeptics Simon Mason

2:00-3:30pm Open space for prac-tice with the Data-Library or work on projects Part I

2:00-3:00pm, Monell Lower Lobby Presentation of partici-pants’ projects Part I






3:45-5:15pm Using GIS to Explor-ing the Links between Poverty and Natural Hazards Part II Mark Becker

3:45-4:45pm Epidemic Detection and Monitoring using Thresholds Part II Patricia Graves

4:15-5:15pm How to Use Maps as a Tool to Communicate Climate Risk Sabine Marx, Francesco Fiondella

3:45-5:15pm Open space for prac-tice with the Data-Li-brary or meetings with facilitators Part II And/or

4:00-5:00pm Poster Clinic Francesco Fiondella, Jason Rodriguez

3:15-4:15pm, Monell Lower Lobby Presentation of partici-pants’ projects Part II

4:45-5:15pm Open space for prac-tice with the Data-Li-brary or meetings with facilitators

4:15-4:30pm, Monell Auditorium Graduation and Award Ceremony

4:30-5:00pm Daily and Final Evalua-tion of the Course5:15-5:30pm

Daily evaluation of the course

5:15-5:30pm Daily evaluation of the course



Evening 5:30-7:30pm, Lamont Hall Weather Roulette: How to Make Decisions Given Probabilistic Forecasts Simon Mason, Ashley Curtis

Farewell Party, Lamont Hall

Closing

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Course Overview

Learning Goals by Module

Module I: Basic Concepts in Public Health and Climate (Days 1, 2)To equip trainees to (i) introduce the concept of Climate Risk Management and to promote discussion on how to incorporate it in the participants’ activities in the health sector; (ii) understand how climate, in various temporal and spatial scales, drives the transmission of many diseases and, in particular, the role of climate in driving the transmission of vector-borne diseases, meningitis and cardio respiratory diseases; (iii) Understand how climate may impact public health, in particular through increased hazards and vulnerability, resulting in increased risk; (iv) understand the terms: weather versus climate, climatology, climate variability versus climate change, climate anomalies, and climate data versus climate information (forecast products, monitoring products); (v) understand routine epidemiological measurements and their spatial and temporal resolution in the framework of Public Health Surveillance; and (v) understand the capabilities of the IRI Data Library and how it may be applied as a useful tool for analyzing climate and health data.

Module II: Sources and Tools for Analyzing Climate and Public Health Data (Days 3, 4, 5)To equip trainees to (i) understand time scales and spatial resolution, the benefits and limitations of different climate, health and environmental data sources including remotely sensed data, meteorological data, climate predictions and epidemiological data; (ii) use new tools for accessing climate and epidemiological data, for analysis and mapping through the IRI Data Library, Geographical Information Systems , Google Earth and Excel spreadsheet tools; (iii) select the appropriate type of health data required for different health/climate analyses; (iv) introduce basic concepts of the dynamics climatic drivers of transmission of vector-borne diseases; (v) define, interpret and understand when to use different statistical methods; and (vi) understand the power of maps to display data and as a tool for decision making in Public Health.

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Course Overview

Module III: Use of Climate Information in Decision-making for Climate-Sensitive Diseases (Days 6, 7, 8, 9, 10)To equip trainees to (i) understand the rationale behind different types of predictions and projections with an emphasis on the interpretation and limitations of the available predictive methods; (ii) show how sophisticated statistical modeling ideas can contribute to the solution of real-world public health problems;(iii) understand why climate information needs to be coupled with health information to inform public health decisions; (iv)understand how researchers can help decision makers to understand the sources of uncertainty in forecasts and predictions and what might be done to reduce it; (v) understand the concepts and methods pertaining to vulnerability analysis and adaptation to climate change;(vi)understand how an ENSO-modified seasonal climate can affect society; (viii) demonstrate how to analyze, create and replicate the simulation outputs of several malaria dynamical models using a case study from Colombia. ; and (viii) explore scenario-based integrated risk assessment for climate change and heat-related health impacts

Details on the daily lectures, practical sessions and associated readings per module are provided on the following page

Materials from the SI10 participant package. Francesco/IRI

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Course Overview

Sessions Summaries by Module

Module I: Basic Concepts in Public Health and Climate (Days 1, 2)

Day 1: Monday, May 17, 2010Introduction to the Summer Institute 2010 and to the CIPHAN network, by Madeleine Thomson, IRI

Summary:

In 2008 and 2009 Summer Institutes on Climate Information for Public Health (CIPH) were conducted at the Lamont Doherty Campus to engage professionals from around the world who play a key role in the operational decision-making for climate-sensitive diseases in identifying and evaluating appropriate use of climate information. The CIPH Summer Institute 2010 builds on this experience and that of our partners and alumni who have been testing the tools, methodologies and approach developed in their own institutions.

Recommended reading:

Cibrelus L, Mantilla G. Executive Summary. In: Summary of the Climate Information for Public Health Training Course. Palisades, NY: International Research Institute for Climate and Society at the Earth Institute, Columbia University; 2009. p. 1-5. Available from:

» http://portal.iri.columbia.edu/portal/server.pt/gateway/PTARGS_0_2_4700_0_0_18/SI2009_Summary_web.pdf

Overview of the Course, by Gilma C. Mantilla, IRI

Summary:

The 2010 Summer Institute course on ‘Climate Information for Public Health’ is a two-week training course that offers public health decision makers the opportunity to learn practical methods and tools for integrating climate knowledge into decision-making processes. The course was designed to have three modules : one on basic concepts of climate and public health, the second : Sources and Tools to Analyze Climate and Public Health Data and the last one on the Use of Climate Information in Decision-making for Climate-sensitive Diseases. It also has an evaluation system that relied on on-line open-ended and numeric questions addressing the design and delivery of the course, as well as the opportunities that could arise from the course. The expected benefits of the course will be that the participants could use the knowledge and skills gained during the Summer Institute to train their peers in their own institution and country.


Visit the Web-page of the Climate Information for Public Health Action Network (CIPHAN) at:

» http://ciphan.iri.columbia.edu/

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Course Overview

Climate Risk Management and Development, by Walter E. Baethgen, IRI

Summary:

Introducing and improving climate risk management in the health sector requires full cooperation of climate scien-tists, climate information providers and agents acting at different levels of the health sector. Such cooperation must be oriented to establish interdisciplinary activities that create climate products, information and tools that effec-tively inform planning and decision making in the health sector. Adequate interaction between these communities enhances knowledge exchange, ensures adequate identification of problems/demands, and helps to tailor climate related information and products that effectively assist the health community. The history of the first 15 years of the IRI has taught valuable lessons on the balance needed to maintain scientific excellence and ensure socioeconomic relevance.

Recommended readings:

Baethgen WE. Climate Risk Management for Adaptation to Climate Variability and Change. Crop Science 2010;50(Supplement 1).

Pielke R, Prins G, Rayner S, Sarewitz D. Climate change 2007: lifting the taboo on adaptation. Nature 2007;445(7128):597.

Climate, Vulnerability, and Health: International and National Perspectives, by Ulisses Confalonieri, Oswaldo Cruz Foundation

Summary:

Human health can be affected by global climate change in several ways, mediated by the environment and the social characteristics, which includes the health systems. The IPCC, in its Fourth Assessment Report, has identified a few observed effects of the changed climate on health, mostly in Europe, but several others are projected for the next decades, such as the spatial redistribution of vector-borne diseases, increase in under nutrition, diarrhea in tropical countries as well as accidents caused by weather extremes and respiratory ailments an many parts of the world. The major task for the health sector is to develop adequate adaptation strategies, which means to reduce the vulnerability of societies. This should be made by public policies oriented by quantitative and comparative assessments of vulner-ability that take into account epidemiological, environmental, social and climatic information.


Confalonieri U, Menne B, Akhtar R, Ebi KL, Hauengue M, Kovats RS, et al. Human health. In: Parry ML, Canziani OF, Palutikof JP, Linden PJvd, Hanson CE, editors. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge University Press; 2007. p. 391-431.

Confalonieri UEC, Marinho DP, Rodriguez RE. Public health vulnerability to climate change in Brazil. Clim Res 2009;40:175-186.

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Course Overview

Climate Risk Management in Health, by Madeleine Thomson, IRI

Summary:

During the past decade, the global health community has advocated for, planned and began resourcing global health initiatives focused on the needs of the poor - as indicated by the United Nations Declaration on the Millennium Development Goals (MDGs). The arrival of climate change on the global health centre stage, was marked by the address on climate change and global public health in November 2007 by Margaret Chan Director-General of the World Health organization (WHO) - “Climate change will affect, in profoundly adverse ways, some of the most fundamental determinants of health: food, air, water.”

As societies in general and the health community in particular, start to adapt to climate change, will this new agenda detract from, or support the pro-poor global health agenda that has been so long in the making? Climate knowledge and information can form a bridge between these two agendas - managing the climate related risks of today while improving our understanding of the risks of tomorrow.


Campbell-Lendrum D, Bertollini R, Neira M, Ebi K, McMichael A. Health and climate change: a roadmap for applied research. The Lancet 2009;373(9676):1663-1665.

Connor S, Omumbo J, Green C, DaSilva J, Mantilla G, Delacollette C, et al. WS-1 Climate and human health: Health and Climate - Needs. In: World Climate Conference 3; 2009; Geneva, Switzerland; 2009 (in press).

Kelly-Hope L, Thomson MC. Climate and infectious diseases. In: Thomson MC, Garcia Herrera R, Beniston M, editors. Seasonal Forecasts, Climatic Change and Human Health: Springer Netherlands; 2008. p. 31-70.

Overview of the Data Library, by Michael Bell, IRI

Summary:

The IRI Data Library is a powerful online resource for accessing, analyzing, visualizing, and downloading climate-related data sets. It is capable of relating different types of data sets (e.g. gridded data, station data, geographic shapes) in a common data model such that relationships between gridded climate data and health data collected by geographic region, for example, can be analyzed. Specialized map and analysis tools in the IRI Map Rooms have been developed using Data Library functionality to meet specific needs in the health community and other sectors. This session provides an introduction to the IRI Data Library.


The IRI Data Library: A Tutorial

» http://iridl.ldeo.columbia.edu/dochelp/Tutorial/

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Course Overview

Understanding Data and Data Quality Control, by John del Corral, IRI

Summary:

Precisely describing the time and locale of the data is a major step in the data analysis process. This is particularly true in the instance of geo-referenced climate and health data, that we want to analyze temporally and spatially. Ensuring good data quality includes: 1) ensuring self-consistency, 2) ensuring geographical consistency, and 3) providing with useful and useable metadata. Although this process may appear as quite demanding and time-consuming, it shall not be neglected because it: 1) simplifies subsequent analysis, 2) allows more sophisticated functions to be applied, and 3) allows ready comparison with other datasets.

Day 2: Tuesday, May 18, 2010Introduction to Climate and Climate Information, by Sylwia Trzaska, IRI

Summary:

One of the main issues of multidisciplinary research is that each discipline has its own approaches, methods and terminology, shaped during the development period of the discipline. Those are most often dictated by availability of the data and data acquisition methods, which led the discipline in given direction, sometime influenced by personal choices of people having contributed to the discipline. This lecture introduced the basic concepts in climatology to enable the participants from the Public Health Sector to efficiently interact with the Climate and Meteorological Community. For example, the notion of scale (spatial and temporal) is central to understanding climate and climate analyses and leads automatically to the distinction between climate variability and climate change (e.g., ENSO). Understanding climate/meteorological data acquisition methods and sources, and related constraints on available information as well as the basic distinction between data and information are also necessary steps to build a common understanding of what is possible. The most common analysis methods used in climate sciences were introduced with emphasis on the importance of scale adequacy for the problem at stake.


IPCC 4th Assessment FAQs

» http://www.ipcc.ch/publications_and_data/ar4/wg1/en/faqs.html

FAQ 1.1, 1.2,1.3,2.1, 6.1, 6.2, 10.1

Core Concepts in Public Health and Epidemiology, by Judy Omumbo, IRI

Summary:

Epidemiologists are concerned with the analysis of disease risk within population groups. Disease risk waxes and wanes between populations, geographical areas and in time. This variation is driven by environmental and social change. In the case of climate sensitive diseases, variations in disease risk are also driven by climate variability on a seasonal, annual, inter-annual or even decadal time scale. This seminar described how time and space are used as

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Course Overview

an epidemiological framework to measure and monitor variability in disease risk. Trainees learned how to capture and store spatial and temporal information and what aspects of space and time need to be measured and monitored for disease risk management. The rationale for organizing information, within a time and space framework and identifying patterns and associations, with the aim of providing insight to epidemiological processes was discussed.


Lafferty KD. The ecology of climate change and infectious diseases. Ecology 2009;90(4):888-900

Public Health Surveillance and Opportunities to use Climate Information, by Richard Luce, CDC

Summary:

The main purpose of surveillance is to control a disease or health condition. Therefore, surveillance is the critical foundation of knowledge upon which public health response, programs, and policy depend. Surveillance is the oblig-atory first step that is required to objectively identify a health problem. Once identified it is possible to investigate underlying contributing factors. Quality surveillance ensures appropriate and targeted interventions, more effective use of resources as well as meaningful monitoring and evaluation of control and prevention programs. Collection of surveillance data should be interpreted, analyzed and disseminated and linked to public health action. The use of climate data in surveillance is underdeveloped, but has the potential to enhance the usefulness of surveillance by adding predictive and explanatory power.


Nsubuga P, White ME, Thacke SB, Anderson MA, Blount SB, Broome CV, et al. Public Health Surveillance: A Tool for Targeting and Monitoring Interventions. In: Disease Control Priorities in Developing Countries, 2nd edition; 2006. p. 997-1015.

Centers for Disease Control and Prevention, Department Of Health And Human Services. Malaria Surveillance — United States, 2007. Morbidity and Mortality Weekly Report 2009;58(SS-2):1-17.

History of Climate and Malaria – Does Causality Matter?, by Menno Bouma, London School of Hygiene and Tropical Medicine

Summary:

The empirical association between weather-climate and diseases goes back a few thousand years. However, the attribution of causality has been, as illustrated by the origin of the word “malaria” - and still is, a major challenge. Supra-annual “cycles” observed in parts of the malarial world, offer, if predictable, the possibility to be forewarned and forearmed. Sea surface temperatures and air pressure anomalies in the Pacific related to El Nino, and other climate-weather anomalies, show such promise for malaria and some other diseases. The deterministic mecha-nisms however are not always obvious, and some have even questioned the need to consider climate at all. An overview was given of periodic malaria epidemics on a global scale, and the possible climatic and non-climatic explanations, with some methodological pitfalls and the difficulties in some cases to attribute causality. Understand-ing the precise mechanisms and the contextual determinants are important for Malaria Early Warning Systems to become operationally relevant.

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Course Overview


Bouma MJ, Sondorp HE, Van der Kaay HJ. Climate change and periodic epidemic malaria. The Lancet 1994;343(8910):1440.

Zurbrigg S. Re-thinking the” human factor” in malaria mortality: the case of Punjab, 1868-1940. Parassitologia 1994;36:121-121.

Summarizing Climate and Health Data Using Descriptive Statistics and Map Tools, by Michael Bell, IRI

Summary:

As a first step to understanding or summarizing a data set of observations, whether of climate or health informa-tion, it is often useful to calculate exploratory or descriptive statistics of the data. The IRI Data Library includes functions and options useful for calculating and displaying such statistics. This session presented fundamentals of using Expert Mode in the Data Library and practical exercises to calculate measures of central tendency and spread and spatial averages of gridded data.


Statistical Techniques in the Data Library: A Tutorial

» http://iridl.ldeo.columbia.edu/dochelp/StatTutorial/

Module II: Sources and Tools for Analyzing Climate and Public Health Data (Days 3, 4, 5)Day 3: Wednesday, May 19, 2010Climate and Vector-Borne Diseases Dynamics, by Madeleine Thomson, IRI

Summary:

Vector-borne diseases present serious problems to human health and welfare around the world, especially in tropical and subtropical regions. According to recent reports of the World Health Organization nearly half of the world’s human population is affected by vector-borne diseases; with malaria, schistosomiasis, onchocerciasis and leishmani-asis infecting 270, 200, 90, 18 and 12 million people, respectively.

The role of climate in the transmission dynamics of vector-borne diseases in the context of replication of disease agents in their vectors and breeding, survival, distribution, abundance and longevity of vectors were discussed. Due attention was also be given to the impact of climate change on the pattern of disease transmission and the geographi-cal distribution of some diseases.

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Course Overview


Gage KL, Burkot TR, Eisen RJ, Hayes EB. Climate and vector-borne diseases. American journal of preventive medicine 2008;35(5):436-450.

Malaria Vector Distribution and Rainfall, by Judy Omumbo, IRI

Summary:

Public health practitioners must make decisions based on quick assessments relying on limited information. This exercise uses a map tool to spatially describe the distribution of malaria vectors, enabling decision making on what would work best.

Key determinants of Anopheles mosquito distribution (the malaria vector) are their feeding, resting and habitat preferences, classifying them anthropophilic, exophilic, endophilic or zoophilic. Some studies have shown that where there are cattle around a homestead and malaria vectors are predominantly zoophilic, the human population tends to have less malaria infection. Most mosquitoes prefer to breed in stagnant fresh water but there are a few species that are salt water breeders. These behavior traits, however, are not absolute and a zoophilic vector may feed on humans if animal hosts are not readily available. The behavioral differences displayed by malaria vectors are exploited for targeting interventions for controlling malaria.


Coetzee M, Craig M, Le Sueur D. Distribution of African malaria mosquitoes belonging to the Anopheles gambiae complex. Parasitology today 2000;16(2):74-77

Exploratory Time Series Analysis, by Andrew W. Robertson, IRI

Summary:

Climate and epidemiological data are often recorded as time series of a measurement at some location. Historical records of weather data have lead to much of our understanding of weather and climate, in terms of daily weather fluctuations, seasonality, interannual “climate” variations, and longer term trends. Epidemiological time-series data may show similar and contrasting features, and exploratory analysis of (univariate) time series forms the starting point for more complex statistical analysis, to identify associations between health and climate data, for example.

The lecture illustrated simple exploratory analyses of univariate time series, including how time-averaging can be used to separate different aspects of a climate time series, such as weather, the seasonal cycle, interannual variability, and longer-term variability and trends. It also illustrated the differing characteristics of temperature, rainfall, and malaria count data using an example from Colombia, and considered the implications for defining “normal” and “unusual” features in time series, and identification of associations between climate and epidemiological data.


Tian L, Bi Y, Ho SC, Liu W, Liang S, Goggins WB, et al. One-year delayed effect of fog on malaria transmission:

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Course Overview

a time-series analysis in the rain forest area of Mengla County, south-west China. Malaria Journal 2008;7(1):110.

Briët OJT, Vounatsou P, Gunawardena DM, Galappaththy GNL, Amerasinghe PH. Temporal correlation between malaria and rainfall in Sri Lanka. Malaria Journal 2008;7(1):77.

Malaria Mapping and the Climate Suitability for Malaria Transmission Tool in the Health Map Room, by Judy Omumbo, IRI

Summary:

Disease maps are an important epidemiological tool for understanding the variability of disease distribution in time and in space, which is in part determined by climate. Maps of the suitability of climatic conditions for malaria trans-mission in a region have been applied widely in areas where empirical disease data are sparse, including for malaria control programs. The development of the malaria parasite and the mosquito vectors is sensitive to temperature, rainfall and humidity. Rainfall plays an important role in the distribution and maintenance of vector breeding sites. Temperature regulates the development rate of both the mosquito larvae and the malaria parasite, Plasmodium falciparum, within the mosquito. Relative humidity and temperature play an important role in the survival and longevity of the mosquito. Using historical data under laboratory conditions, Climate Suitability for Malaria Trans-mission is defined as the coincidence of precipitation accumulation greater than 80 mm, mean temperature between 18°C and 32°C, and relative humidity greater than 60 percent.


Craig MH, Snow RW, Le Sueur D. A climate-based distribution model of malaria transmission in sub-Saharan Africa. Parasitology today 1999;15(3):105-110.

Grover-Kopec EK, Blumenthal MB, Ceccato P, Dinku T, Omumbo JA, Connor SJ. Web-based climate information resources for malaria control in Africa. Malaria Journal 2006;5(1):38

Panel Discussion at the Mailman School of Public Health, Columbia University: Creating a “climate-smart” community: How do we Communicate? Who do we Train?

Opening speech: Linda Fried, Mailman School of Public Health (invited)

Facilitator: Madeleine Thomson, IRI

Panelists: Elliot Wayne, Met Office UK ; Richard Luce, CDC, Ethiopia, Field Epidemiology Training Programs Resident Advisor; Patrick Kinney, Columbia Climate and Health Program, Mailman School of Public Health

Summary:

Increasing the health community’s capacity to understand, use, and demand the appropriate climate information is of primary importance to efforts to diminish the health impacts of climate change and climate variability. However, good information is not enough. The health community must also be able to distinguish between different kinds of data to determine what is relevant, at what time scale, to their population.

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Course Overview

To fill the current gaps, we must develop research and professional training in the use of climate information for public health decision-making that can be launched in centers of learning throughout the globe. Here, an expert panel discusses the opportunities and challenges we face in the creation of a “Climate Smart” health community.

Day 4: Thursday , May 20, 2010Remote Sensing as a Tool to Manage Environmental Data, by Pietro Ceccato, IRI

Summary:

Remote sensing is the science of obtaining information about an object through the analysis of data acquired by a device (sensor) that is not in contact with the object (remote). As you read these words, you are employing remote sensing. Your eyes are acting as sensors that analyze the electromagnetic waves (visible light) reflected from this page. The light your eyes acquire is analyzed in your mental computer to enable you to explain the words. Apart from the eyes, more sophisticated sensors have been developed to measure the electromagnetic waves in domains outside the visible. By measuring the electromagnetic waves in domains from Gamma rays to Microwaves, we can retrieve information on objects we want to study.


Ceccato P, Dinku T. Introduction to Remote Sensing (unpublished)

Ceccato P, Connor SJ, Jeanne I, Thomson MC. Application of Geographical Information Systems and Remote Sensing technologies for assessing and monitoring malaria risk. Parassitologia 2005;47(1):81-96.

Introduction to Cluster Analysis, by Andrew Robertson, IRI

Summary:

In multivariate data analysis, identifying any shared behavior between locations or variables is a key simplifying step. This lecture taught how such data can be stratified into groups using cluster analysis, in order to identify patterns, and to facilitate the identification of associations between climate and health data.

The lecture showed how the K-means method partitions a set of observations into sub-groups, based on their similarity according to a measure of the “distance” between them, and so as to minimize the scatter within each cluster. Examples included were July temperatures at US cities, and malaria data gathered for Eritrea.


Ceccato P, Ghebremeskel T, Jaiteh M, Graves PM, Levy M, Ghebreselassie S, et al. Malaria stratification, climate, and epidemic early warning in Eritrea. The American journal of tropical medicine and hygiene 2007;77(6 Suppl):61.

» http://en.wikipedia.org/wiki/K-means_clustering

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Course Overview

Remote Sensing Tools in the Health Map Room, by Pietro Ceccato, IRI

Refer to: Day Four, Morning Sessions, Remote Sensing as a Tool to Manage Environmental Data, by Pietro Ceccato, IRI

Day 5: Friday, May 21, 2010Using GPS, GIS and Google Maps for Public Health, by Mark Becker, CIESIN

Summary:

GPS is an increasingly popular way of collecting location information related to health studies. With GPS we can easily create highly accurate spatial data files to indicate the location of health clinics, schools, transportation routes and patient’s home locations or village location. In this exercise students will learn the proper use of a standard GPS data collection unit and gain an understanding of procedures to insure data accuracy and integrity. Students will also learn what tools are available for downloading their GPS data and converting it into formats accepted by, Google Earth®/Google Maps® and ArcGIS®.


Montana L, Spencer J. Incorporating Geographic Information into MEASURE Surveys: A Field Guide to GPS Data Collection and Demographic and Health Survey GPS Cluster Position Form. Calverton; 2005.

Meningitis and the Environment: Meningitis Environmental Risk Information Technologies (MERIT), by Madeleine Thomson, IRI

Summary:

Meningococcal meningitis is an environmental disease whose spatial and seasonal distribution is readily described by climatic and environmental characteristics. Epidemics of meningococcal meningitis occur throughout sub-Saharan Africa, most frequently in an area, known as the ‘Meningitis Belt’ that stretches from the Sahelian zone of West Africa to the Horn of Africa. This region is a major source of atmospheric dust over most of north and western Africa and has epidemics and seasonal upsurges in endemic disease in the latter part of the dry season, character-ized between November and May by low absolute humidity and the dust-laden Harmattan trade winds. Given the association of the epidemics with a dry and dusty environment and their higher incidence in the ‘Meningitis Belt’, recent research has focused on developing maps that identify the populations at high risk of epidemics and climate-driven early warning systems that could provide longer lead-times for initiating response. The relevance of this work to the implementation of current and future epidemic meningitis control strategies in Africa will be discussed.


Cuevas LE, Jeanne I, Molesworth A, Bell M, Savory EC, Connor SJ, et al. Risk mapping and early warning systems for the control of meningitis in Africa. Vaccine 2007;25:A12-A17.

Roberts L. Infectious disease: an ill wind, bringing meningitis. Science 2008;320(5884):1710-1715.

Additional resources:

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Course Overview

Video: The International Research Institute for Climate and Society at the Earth Institute CU. Climate and Health in Africa. Google Tour;2009. Available from : http://www.google.com/landing/cop15/

Visit the Web-page of the MERIT initiative

» http://Merit.hc-foundation.org

Lagged correlation of Rainfall with Malaria Incidence, by Michael Bell, IRI

Summary:

One challenge of relating climate conditions to epidemiological conditions is to re-express these data in the same spatial and temporal framework. For example, while epidemiological data may be collected by health district, climate data are often available by station or in a gridded format. This session showed how to use the Data Library to put climate and health data into a common spatial and temporal framework, map data by district, and calculate correlations and lagged correlations by district.


Statistical Techniques in the Data Library, A Tutorial:

» http://iridl.ldeo.columbia.edu/dochelp/StatTutorial/

IRI Tony Barnson lectures during the SI10 special Climate Briefing. Francesco/IRI

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Course Overview

Exercises on K-means and Cluster Analysis: Malaria Seasonality, by Pietro Ceccato, IRI

Summary:

Cluster analysis or clustering is the assignment of objects into groups (called clusters) so that objects from the same cluster are more similar to each other than objects from different clusters. Often similarity is assessed according to a distance measure. Clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics.

Module III: Use of Climate Information in Decision-making for Climate-Sensitive Diseases (Days 6, 7, 8, 9, 10)

Day 6: Monday , May 24, 2010Understanding Predictions and Projections in Climate, by Sylwia Trzaska, IRI

Summary:

Climate forecasts or projections are often misinterpreted due to their probabilistic format, often omitted in sectoral applications. There is more and more interest in health impact of the future climate so it is important that the current generation of Public Health professionals understands what the projections can or cannot tell us. The lecture aimed at explaining why forecasts/projections can only be produced in a probabilistic format, which, in fact, attempts to quantify the uncertainty attached to the forecast output. Sources of uncertainty as well as the main forecasting methods will be presented. We will devote some time to a practical interpretation of two examples of forecasts: the seasonal forecast and the Climate Change scenario. An important element for the decision process, forecast verifica-tion, will also be briefly introduced.


IRI Tutorials on forecasting

» http://iri.columbia.edu/climate/forecast/tutorial and http://iri.columbia.edu/climate/forecast/tutorial2

IPCC 4th Assessment: Introduction to regional projections in chapter 11. Available from:

» http://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch11s11-1-2.html

FAQs:

» http://www.ipcc.ch/publications_and_data/ar4/wg1/en/faqs.html

Spatio-temporal Modeling of Meningitis, by Peter Diggle, Lancaster School of Health and Medicine

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Course Overview

Summary:

Meningitis incidence across the “meningitis belt” of sub-Saharan Africa shows an irregular cyclic pattern, with large year-to-year variations. In the affected countries, incidence data are typically collected weekly at district level, and a local epidemic declared in any district for which incidence exceeds a fixed threshold. Three limitations of this approach are:

1) it is reactive rather than anticipatory;

2) it does not draw on relevant information from incidence in neighboring districts;

3) nor does it make use of patterns of association between incidence and environmental predictors.

In this lecture, data from Ethiopia was used to show how recently developed statistical methodology for spatio-temporally indexed data can be used to develop a predictive approach to meningitis incidence that attempts to overcome the above limitations.


Fanshawe TR, Diggle PJ, Rushton S, Sanderson R, Lurz PWW, Glinianaia SV, et al. Modelling spatio-temporal variation in exposure to particulate matter: a two-stage approach. Environmetrics 2007;19(6):549-566.

Francesco Fiondella/IRI

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Course Overview

Using GIS to Exploring the Links between Poverty and Natural Hazards, by Mark Becker, CIESIN.

Summary:

This is a hands-on GIS laboratory exercise that has students learning to use the analysis tools in ArcGIS® to explore the relationship of poverty levels and exposure to natural hazards. Students will become familiar with the primary spatial data sets used to illustrate poverty and natural hazards across the globe. Students will produce a series of final products including maps and charts to show the results of their analysis.


Warner K, Erhart C, de Sherbinin A, Adamo SB, Chai-Onn TC. “In search of Shelter: Mapping the effects of climate change on human migration and displacement.” A policy paper prepared for the 2009 Climate Negotiations. Bonn: United Nations University Institute for Environment and Human Security, CARE International, and Center for International Earth Science Information Network at the Earth Institute of Columbia University; 2009.

Day 7: Tuesday May 25,2010Climate Change, War and Disease, by Dia El Naiem, University of Maryland

Summary:

The Epidemiology of vector-borne diseases is influenced by climatic factors that affect the ecology of the vectors and the exposure of human populations to the pathogens. This lecture addresses the eco-epidemiology of visceral leishmaniasis (VL, kala-azar), a neglected tropical disease that occurs within a defined climate space and affects some of the poorest communities in the world. One of the notable features of the epidemiology of kala azar in East Africa is that it remains silent for many years and then erupts in severe epidemics that affect the lives of thousands of people. Although environmental information models allowed the prediction of the transmission areas of the VL in Sudan, studies have overlooked the importance of climate-related socioeconomic factors that lead to Darfur War and migration of susceptible populations into kala azar transmission foci.


Elnaiem DA, Schorscher J, Bendall A, Obsomer V, Osman ME, Mekkawi AM, et al. Risk mapping of visceral leishmaniasis: the role of local variation in rainfall and altitude on the presence and incidence of kala-azar in eastern Sudan. The American journal of tropical medicine and hygiene 2003;68(1):10.

Thomson MC, Elnaiem DA, Ashford RW, Connor SJ. Towards a kala azar risk map for Sudan: mapping the potential distribution of Phlebotomus orientalis using digital data of environmental variables. Tropical medicine and international health 1999;4(2):105-113.

Malaria Early Warning and Early Response, by Stephen Connor, IRI

Summary:

Climate informed Malaria Early Warning Systems (MEWS) have been of interest for many years – at least since the beginning of the 20th century. The rationale behind MEWS is simply the pursuit of reliable and timely information

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Course Overview

on any changes in epidemic potential occurring that may be taking place. The information needs to be focal, i.e. applicable to specific geographic regions prone to epidemics; and timely, i.e. able to offer sufficient lead time for health services to be able to mobilize effective prevention and control interventions.

The integrated Malaria Early Warning and Response System approach developed since the inception of Roll Back Malaria in 1998 aims to assemble a set of available indicators from the spectrum between these two extremes, and to use these indicators to build up incremental evidence to stimulate and guide more timely and focal prevention and control of malaria epidemics.


Thomson MC, Doblas-Reyes FJ, Mason SJ, Hagedorn R, Connor SJ, Phindela T, et al. Malaria early warnings based on seasonal climate forecasts from multi-model ensembles. Nature 2006;439(7076):576-579.

DaSilva J, Garanganga B, Teveredzi V, Marx SM, Mason SJ, Connor SJ. Improving epidemic malaria planning, preparedness and response in Southern Africa. Malaria Journal 2004;3(1):37.

Integrated Malaria Surveillance and Control System for Malaria in Colombia, by Daniel Ruiz, IRI

Summary:

Dynamical models have played a significant role in understanding the complexity of malaria transmission dynamics. In the first part of this lecture students were exposed to the framework of several malaria process-based models. In the second part, they were exposed to several of these tools to: (a) explore the role that both climatic and non-climatic factors play in fluctuations and trends in malaria incidence; (b) compare their simulation outputs with actual malaria morbidity profiles observed in a specific malaria-prone region; (c) simulate the impact of intervention campaigns; and (d) assess several changing climate and future scenarios. Finally, the group explored the ongoing efforts of the Colombian Integrated Surveillance and Control System project.


Ruiz D, Connor SJ, Thomson MC. A Multimodel Framework in Support of Malaria Surveillance and Control. In: Thomson MC, Garcia Herrera R, Beniston M, editors. Seasonal Forecasts, Climatic Change, and Human Health: Springer Netherlands; 2008. p. 101-125.

Epidemic Detection and Monitoring using Thresholds, by Patricia Graves, the Carter Center

Summary:

Detailed empirical data on malaria cases in space and time is needed in order to define the normal situation of malaria in a given area and to define epidemics. The geographical units used in the definition should correspond to planning units to facilitate response and prevention. Examples of malaria epidemics are illustrated with reference to a dataset of cases by subzone and month from Eritrea, 1997 to 2003. Several different proposed methods for estimating malaria epidemic thresholds were given, including third quartile, the mean plus 1 or 2 standard devia-tions, the moving average and the C-Sum method. It was emphasized that an epidemic definition is a practical and planning decision, with no objective standard. The participants produced graphs that illustrate the different thresholds estimated for particular subzones and quantify epidemics that occurred in particular time periods as an indicator of malaria control or for relating to climate factors.

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Course Overview

Recommended readings :

Hay SI, Simba M, Busolo M, Noor AM, Guyatt HL, Ochola SA, et al. Defining and detecting malaria epidemics in the highlands of western Kenya. Emerging Infectious Diseases 2002;8(6):555-562.

Cullen JR, Chitprarop U, Doberstyn EB, Sombatwattanangkul K: An epidemiological early warning system for malaria control in northern Thailand. Bull World Health Organ 1984, 62:107-114.

Day 8: Wednesday , May 26,2010Temperature Trends in the Highlands of Kenya, by Bradfield Lyon, IRI

Summary:

Several studies have considered the impact of climate change, and temperature in particular, on the distribution and incidence of malaria in the highland regions of East Africa. The results, however, often led to different conclusions. This was in part related to the fact that they typically used different climate datasets that were either interpolated analyses based on station observations or an insufficient set of station observations, or length of record, for the specific areas of interest.

It is indeed a critical issue to understand the climate (or health) data being used in any study, including limitations in using such data before conducting any analysis. This includes the issue of data quality but also using the appropriate time scale of information (e.g., daily versus monthly rainfall data) for the health question being considered. One needs to take into account the caveats to using gridded data derived from point observations, for example, to avoid drawing potentially inappropriate conclusions from the analysis. Indeed, any analysis should begin with a simple, exploratory step that can subsequently be followed by more sophisticated methods. It is recommended that when undertaking interdisciplinary studies experts from across disciplines are involved to help minimize misinterpretation of the datasets being used.


Hay SI, Cox J, Rogers DJ, Randolph SE, Stern DI, Shanks GD, et al. Climate change and the resurgence of malaria in the East African highlands. Nature 2002;415(6874):905-909.

Patz JA, Hulme M, Rosenzweig C, Mitchell TD, Goldberg RA, Githeko AK, et al. Climate change (Communica-tion arising) Regional warming and malaria resurgence. Nature 2002;420(6916):627-628.

Linking ENSO and Society, by Tony Barston, IRI

Summary:

ENSO (La Niña and El Niño) refers to the year-to-year variation of sea surface temperature in the central and eastern tropical Pacific relative to its long-term average. The state of ENSO is important because it is known to influence the climate throughout various parts of the world, depending on the season, making possible advance warning of above or below average precipitation and/or temperature. Such variations of seasonal climate, in turn, may affect society in many ways. Some of these impacts are obvious, such as a negative impact of below-average

37


Course Overview

rainfall on agricultural yield and on water reservoirs, or of above-average rainfall on malaria incidence in regions of epidemic malaria. Other impacts may be positive, such as reduction in heating requirements for extra tropical regions having a warmer-than-normal winter related to the ENSO state. Here we discuss these and other ways in which ENSO matters to human society, and how its effects can be anticipated and managed—both to minimize negative effects and exploit positive ones.


McPhaden MJ, Zebiak SE, Glantz MH. ENSO as an integrating concept in earth science. Science 2006;314(5806):1740.

Thomson MC, Mason SJ, Phindela T, Connor SJ. Use of rainfall and sea surface temperature monitoring for malaria early warning in Botswana. The American journal of tropical medicine and hygiene 2005;73(1):214.

Climate Change and Vulnerability, by Carlos Perez, IRI

Summary:

Adaptation to the beneficial and deleterious impacts of climate change is a priority, and there is growing attention to integrate adaptation and mitigation as key components of a vision of and a strategy for sustainable development. It is important to identify, develop and implement effective responses to enhance adaptive capacity and reduce vulner-ability of populations, regions and economic sectors. The presentation and discussions among participants focused on themes related to promoting planned and autonomous adaptation in order to improve resilience in a changing climate. The presentation pointed out the important role that the scientific community may play in advancing the information and knowledge base that would help in adaptation.


Heltberg R, Siegel PB, Jorgensen SL. Addressing human vulnerability to climate change: Toward a ‘no-regrets’ approach. Global Environmental Change 2009;19(1):89-99.

Patwardhan A, Downing T, Leary N, Wilbanks T. Towards an integrated agenda for adaptation research: theory, practice and policy: Strategy paper. Current Opinion in Environmental Sustainability 2009;1(2):219-225.

Climate Prediction for Weather Forecast Skeptics, by Simon Mason, IRI

Summary:

In order to predict the weather we need to know (a) what the weather is like now, and (b) how the current weather is likely to evolve. Our lack of knowledge of the exact weather conditions right now is the primary reason why weather forecasts become inaccurate after only a few days, because small errors in that knowledge rapidly grow into large errors in the predicted weather. Although it is impossible to forecast the exact weather at any given moment beyond a few days into the future, it is possible to predict whether wet, or dry conditions, for example, are likely to be unusually frequent and/or intense. These predictions are possible at seasonal scales because in some parts of the world, and at some times of the year, the atmosphere can be affected by unusual conditions at the earth’s surface, especially the surface of the sea.

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Course Overview


Mason SJ. “Flowering Walnuts in the Wood” and Other Bases for Seasonal Climate Forecasting. In: Thomson MC, Garcia Herrera R, Beniston M, editors. Seasonal Forecasts, Climatic Change and Human Health: Springer Netherlands; 2008. p. 13-29.

How to Use Maps as a Tool to Communicate Climate Risks, by Sabine Marx, Center for Research on Environmental Decision Making, and Francesco Fiondella, IRI

Summary:

Maps and other visual representations of data are integral forms of communication used by the climate- and meteorological-services communities. Examples include forecast maps of differing spatial and time scales, and environmental-monitoring data maps for humidity, dust and wind. Maps are powerful tools to bring out spatial distributions and relationships and make it possible to visualize and conceptualize patterns and processes that operate through space. However, in many instances, these visualizations fail at communicating valuable, usable, actionable information because they don’t take into account the needs and intents of the users (health, water, agricul-tural, etc.). It was discussed some of the ways in which climate information can be communicated more effectively to different audiences.


Shome D, Marx S. The Psychology of Climate Change Communication: A Guide for Scientists, Journalists, Educa-tors, Political Aides, and the Interested Public. NY: Center for Research on Environmental Decisions, Columbia University; 2009.

Ishikawa T, Barnston AG, Kastens KA, Louchouarn P. Understanding, evaluation, and use of climate forecast data by environmental policy students. Qualitative Inquiry in Geoscience Education Research 2010.

Weather Roulette: How to Make Decisions given Probabilistic Forecasts, by Simon Mason and Ashley Curtis, IRI

Summary:

A series of ten seasonal forecasts were issued, and the participants were required to make investment choices based on the forecasts. The forecasts were presented in standard format, with three probabilities indicating the chances of “below-normal”, “normal” and “above-normal” rainfall. The forecasts and observations were drawn from a real opera-tional set of forecasts and observations, but the location and years were not revealed so that the participants cannot cheat using any prior knowledge. The participants made profits or losses depending upon the amount invested on the category that occurs. Their profits and losses were accumulated over a ten-year period. The participants worked in pairs, and the team that accumulated the largest profit won.

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Course Overview

Day 9: Thursday, May 27,2010Climate Change and Human Health: Current Impacts and Future Risks, by Patrick Kinney, Mailman School of Public Health

Summary:

One of today’s greatest public health challenges is to enhance population health in the face of emerging risks related to climate change. Scientists predict that climate change may lead to:

• Increasing heat-related deaths;

• Diverse health impacts of more intense storms and flood events;

• Risks to water quality, agricultural productivity, and regional peace due to shifting water resources;

• Worsening air quality and asthma;

• Changing patterns of vector-borne and other infectious diseases.

However, the scientific knowledge base upon which to build strategies to reduce health impacts of climate change is surprisingly sparse. By partnering with climate scientists, health scientists have the ability to make significant scientific advances to understand, anticipate, and prevent adverse health consequences. This lecture provided an introduction to this topic and discussed challenges and opportunities for new research.


Knowlton K, Lynn B, Goldberg RA, Rosenzweig C, Hogrefe C, Rosenthal JK, et al. Projecting heat-related mortality impacts under a changing climate in the New York City region. American journal of public health 2007;97(11):2028-2034.

Pan American Health Organization. Climate change and human health: risk and responses: revised summary 2008. Washington DC; 2008.

Heat Waves in the USA from the Climate Perspective, by Bradfield Lyon, IRI

Summary:

Reasons for studying heat waves were discussed followed by some of the difficulties in defining a heat wave. The concept of a heat index was then introduced. The 1995 heat wave in the US was considered by examining the large-scale atmospheric circulation associated with the heat wave as well as important local-scale features of the heat wave using Chicago as an example. The final segment of the lecture examined how all warming is not “equal” when considering climate change.


Kunkel KE, Changnon SA, Reinke BC, Arritt RW. The July 1995 heat wave in the Midwest: A climatic perspective and critical weather factors. Bulletin of the American Meteorological Society 1996;77(7):1507-1518.

Lebassi B, González J, Fabris D, Maurer E, Miller N, Milesi C, et al. Observed 1970–2005 Cooling of Summer

40


Course Overview

Daytime Temperatures in Coastal California. Journal of Climate 2009;22:13.

Heat Waves and Public Health: a USA Case-Study, by Kim Knowlton, Natural Resources Defense Council, and Department of Environmental Health Sciences, Mailman School of Public Health

Summary:

Heat waves have substantial acute effects on local populations. A large heat-mortality literature has evolved over the years, yet few studies of heat morbidity have been done. Recent work suggests that a single heat wave can have widespread effects. We discussed a US Case Study of morbidity during a 2006 California heat wave (Knowlton et al., 2009). Heat vulnerability factors included biomedical, demographic, housing, and community geographic characteristics. We can use this information to identify the most at-risk communities for climate sensitive health outcomes. Climate models project that the frequency, intensity, and duration of heat waves will increase in the future as climate change continues. The key message of the lectures was that climate-health preparedness can be enhanced by developing strategies that identify vulnerabilities, establish tracking systems, apply climate-smart design, and employ public education to protect the most climate-vulnerable among us today, thereby learning how to provide better climate-health protection for all of us in the future.


Knowlton K, Rotkin-Ellman M, King G, Margolis HG, Smith D, Solomon G, et al. The 2006 California heat wave: impacts on hospitalizations and emergency department visits. Environmental health perspectives 2009;117(1):61.

Harlan SL, Brazel AJ, Prashad L, Stefanov WL, Larsen L. Neighborhood microclimates and vulnerability to heat stress. Social Science & Medicine 2006;63(11):2847-2863.

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Daily Quiz and Personal Projects


Quiz Questions by ModuleTrainees were required to answer quiz questions on the daily basis.

The questions and answers per module are available in a separate appendix.

SI 10 Participants work hard during the morning QnA session. Francesco/IRI

Trainees Personal Projects Guidelines and SummariesThe following guidelines were provided to the trainees:

It is critical to ensure and capture the opportunity for participants of the Summer Institute to explore their own ideas through the course lectures, seminars, exercises and discussions and to demonstrate their newly acquired competency. Therefore, we would like you to begin, from the beginning of the training, to follow through on a personal project that you decide either individually or in a small group with individuals of both the health and climate communities. We are asking you to define your project and (when applicable) form your working group on the second day of the training and to provide this information to the Summer Institute Team during the first session of the third day of the training.

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You will build up your project throughout the entire course, applying what you have learned - using either your own data, when applicable, or some datasets made available to you by the IRI - and linking these results to aspects of your own work or interest. For instance, the projects may explore the relationship between malaria and rainfall in the Kenya Highlands, or between dengue and temperature in Bogota.

We are asking you to develop your project using the results and figures obtained with your data (either personal or provided by the IRI) during the daily practical sessions. A pen drive will be provided to each participant to save these results on a daily basis. Some additional time will also be allocated everyday for you to work on your own projects.

Poster presentations of these projects will be made by the participants on the final day of the course, allowing partici-pants the opportunity to share the learning experience with co-participants, facilitators, distance learners and the climate information for public health network. The poster should include (but not be limited to) the following items: brief overview of the project’s targeted country, objectives, project’s targeted audience/users, hypothesis, methods, results, interpretation (including new hypothesis that arose), tables and figures (when applicable). We are also asking you to frame your project in the context of public health decision-making.

These projects will not be graded but they will be used to share with co-participants, facilitators, instructors and distance learners. There will also be a “Best Poster Prize Committee” awarding outstanding poster presentations.

In addition to the poster, participants will need to write up a 300-word summary which would include the following: title, author(s)’ name(s), author(s)’ affiliation(s), background, objectives, hypothesis and methods, results, interpreta-tion and conclusion. This summary needs to be written on a Word document.

Recommended resources:

The Psychology of Climate Change Communication: A Guide for Scientists, Journalists, Educators, Political Aides, and the Interested Public, by Debika Shome and Sabine Marx, Center for Research on Environmental Decisions, Columbia University, NY, available from:

» http://www.csc.noaa.gov/digitalcoast/inundation/pdf/CRED_Psychology_Climate_Change_Communication.pdf

Advice on Designing Scientific Posters, by Colin Purrington, Department of Biology, Swarthmore College, Pennsyl-vania, available from:

» http://www.swarthmore.edu/NatSci/cpurrin1/posteradvice.htm

Scientific Poster Design, Cornell Center for Materials Research, Cornell University, Ithaca, NY, available from:

» http://sciencetalk.posterous.com/toward-a-better-scientific-poster

Instances of projects conducted by participants to previous Summer Institutes (see next page). Please note that on previous years the assignment slightly different.

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Project Summaries The summaries of the trainees’ projects may be found below. The full poster presentations are available from a separate appendix.

Typhoid Fever and Climate in Uganda: Is there a link?

Betty Abang, Centers for Disease Control and Prevention, Uganda

Typhoid fever is a food and waterborne disease caused by the bacterium Salmonella Typhi. Extreme weather events have been accompanied by outbreaks of typhoid. Populations with poor sanitation infrastructure often experience increased rates of typhoid fever after flood events. Transmission of enteric pathogens is generally higher during the rainy season. Typhoid fever has been reported to have no correlation with climate variables. Symptoms of typhoid fever appear 1-3 weeks after exposure to the bacterium. The mean annual incidence of typhoid fever in Uganda ranges between 10 and 100 per 100,000. The objective of this project was to investigate whether typhoid fever outbreaks vary with climate. The setting of the study was : Kasese district that is located in western Uganda, East Africa. The district has two lakes along its borders, Lake George and Lake Edward. District population in the year 2008 was 646,300.

Data on the number of cases of typhoid fever reported from Kasese district in 2008 were obtained from the Uganda government Ministry of Health. Daily precipitation data from the NOAA NCEP CPC FEWS Africa dataset in the IRI data library were aggregated to generate a monthly average for the year 2008 for Kasese district. Since the symptoms of typhoid fever appear 1-3 weeks after exposure to the bacterium, precipitation data were lagged by one month. These data were then graphed with typhoid fever incidence data.

The conclusions of the study are that there is no clear evidence of a link between occurrence of typhoid fever and rainfall. This analysis was limited by the fact that only one year of data was available to the author. The author recommends further analysis using data for a period of about 10 years. Analyses would include generating a clima-tology for a 10 year period and regression analyses to explore associations between incidence of typhoid fever and rainfall.

Trends of malaria in relation to rainfall at Alamata Hospital in Northern Ethiopia

Wakgari Deressa Amente. School of Public Health, Addis Ababa University, Ethiopia

Malaria is one of the leading causes of morbidity and mortality in Ethiopia. More than 75% of the country’s landmass is malarious, and about 68% (>50 million people) of the total population resides in areas at risk of malaria. Malaria transmission in the country is highly influenced by local weather conditions, seasonal and inter-annual climate variations. The unstable nature of the disease makes all age groups of the population prone to epidemics. Although malaria epidemics are usually associated with rainfall pattern, studies related to the relationship between rainfall and malaria is generally scarce in Ethiopia.

The main objective of this study was to determine the pattern and relationship between malaria and rainfall. In this study it was hypothesized that high rainfall is significantly correlated with high incidence of malaria in the study area.

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This study was conducted in Alamata Woreda (or District) of Tigray Region in Ethiopia. Located in the Southern Zone of Tigray, Alamata was inhabited by an estimated population of 85,000 in 2007. Malaria is the main cause of morbidity and mortality in the district. Historical malaria morbidity monthly data for nine years ( Jan 1999 to Dec 2007) were collected from the OPD of Alamata Hospital. Monthly rainfall data for the district during the same period were retrieved from the Data Library at IRI for Climate and Society at Columbia University. Time series analysis was performed to assess the trend and relationship between malaria and rainfall.

The study revealed the monthly and yearly seasonality of malaria in the study area, peaking from August to Novem-ber each year. High rainfall was recorded each year during the months of June to August. The years 1999 and 2003 experienced heavy rainfall. Following high rainfall during the 2003, malaria epidemics occurred in 2004 and 2005. However, declining trends of rainfall and malaria were observed since 2004 and 2006, respectively. Examination of the annual average of malaria and rainfall reveals a strong correlation between the two variables.

This study demonstrated strong correlation between rainfall and malaria, and high rainfall preceded the occurrence of high malaria incidence. The study also highlighted a possibility for developing malaria epidemics prediction model. The relationship between malaria and other climatic factors such as temperature and humidity should be further investigated.

Malaria Risk Mapping in Oromia Region, 2010, Ethiopia

Yilma Bekele. School of Public Health, Addis Ababa University, Ethiopia

Oromia region has 30 Million Population and 215 Malarious Districts. The malaria incidence rate was 21 per 1000 population based number of cases reported to Federal Ministry of Health of Ethiopia in 2008.

To analysis correlation historical malaria incidence/anomalies, Environmental factors (NDVI &MOUDIS), inter-vention factors and Produce malaria risk maps that can be used by disease control managers at districts.

Sample Size 50 districts that have 10 to 18 years monthly Malaria data selected for the study. The Inclusion Criteria used were: districts that have at least one Health facilities with Microscopic diagnostic facility of malaria, and more than 10 years malaria record and has meteorological station within catchment area of health facilities included for the study. From eligible health facilities 80 located in 50 districts included. Monthly confirmed malaria data collected from 80 facilities in 50 districts in Oromia region from July 1995 to December 2009. Climate Data: - monthly climatic data: temperature (Minimum and Maximum), rainfall and humidity for the study period collected from 76 meteorological Station in selected district of the region from National Metrology Agency of Ethiopia. Environmental data (NDVI, MOUDIS): - used from International Research Institute Data Laboratory (IRI DL). After verification the consistence of data the cleaned data uploaded to IRI DL and analyzed for correlation anomalies malaria incidence with climate anomalies (Temperature, Rainfall, and Humidity), NDVI, MOUDIS and intervention Variables (ITNS, IRS). The Climatic/ Environmental and Intervention factors strongly correlated used as predictors to construct malaria risk mapping.

From 50 sampled districts 33(66%) of collected according to scheduled. The majority of districts 31(93.9%) have more than 15 years confirmed malaria Data and the remaining have 10 years monthly Malaria Data. The mean was 14.45 and range was 6 years. There was strong correlation between Plasmodium falciparum monthly incidence rate and monthly mean Temperature and rainfall(r=0.065, PV<0.00001, 95%) for the year 1995 to 2002 and no correla-tion found from 2003 to 2009 between climate factors and Plasmodium falciparum incidence rate. There was two months lag correlation between malaria incidence anomalies and precipitation anomalies for the year 1995 to 2002.

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The correlation monthly malaria incidence rate and monthly mean temperature and rainfall found for the year 1995 to 2002, and similarly the lag correlation between malaria incidence anomalies and rainfall were better for the year 1995 to 2002. However, is no correlation from 2003 to 2009, may be due to policy change during these period. Therefore, beside the climatic factors to consider the intervention factors recommended for further study.

Mapping of Sand Flies in Tunisia.

Ali Bouattour. Pasteur Institute of Tunis-Tunisia

In Tunisia, 16 species of sand flies have been recorded. Some of them are implicated in the transmission of three species of Leishmania. Sand flies are very small insect (<3mm) and therefore they have an intimate relationship with their environment mainly temperature and humidity. The distribution and the occurrence of sand flies depend on the specific need of each species: habitat suitability. The Mediterranean region is predicted to have increases of temperature and changes in rainfall patterns in the near future (IPCC 2000). These may influence the ecology and biology of sand fly fauna and therefore the epidemiology of leishmaniasis in Tunisia. These two principle climatic factors may affect the distribution of the sand flies. The epidemiology of leishmaniasis in Tunisia has been changing during the last few decades regarding the increase in the spread of the visceral and cutaneous forms toward the south and on the emergence of a new cutaneous form in the north. Based on this new situation there is increasing concern regarding the possible impact of projected climate change on the distribution of sand flies that are involved in leishmaniasis transmission.

The objective of the project was to map the current sand fly distribution using GPS, GIS and Google Maps and Data-Library using climate and environmental variables such temperature, rainfall, relative humidity (RH) and NDVI. What we can concluded is that the mapping, the monitoring of the density and the dynamics of each species correlated with the climatic parameters used (temperature, rainfall and Relative Humidity) but is the vegetation the parameter that can help to predict the risk of high transmission period and then be able to prevent cutaneous leishmaniasis. But for that, there is a need to create a model using in addition to the number and location of each leishmaniasis cases.

Temperature and Mortality in Beijing, China.

Tiantian Li. Institute for Environmental Health and Related Product Safety, Chinese Center for Disease Control and Prevention, Beijing, China

Climate change has led to increasing temperatures in recent decades. A strong association between temperature and mortality has been identified for a number of cities around the world, mostly in Europe and North America. General nonlinear relations have been observed with increased mortality at high and low temperatures. However, the literature on the association between mortality and temperature in China is scarce. The objective of this study was to analyze the relationship between temperature and mortality in Beijing and estimate the impact of climate change on premature deaths in 18 districts in Beijing. The expose-response relationship between temperature and mortality was analyzed using time series Poisson GLM regression method. The summer heat related premature deaths were estimated by integrating the results from the exposure-response relationship and related parameters. A 10% rise in temperature yielded a 8.69% (95% CI: 6.30-11.04%) increase in mortality with the MMT (minimum mortality temperature) at 48.9% in Beijing. The people in different areas in Beijing have different adaptation ability for heat. For example, the people in the city have the worst adaptation ability, as evidence by the smallest MMT and biggest heat slope. Conversely, the people in the outer suburb have the best adaptation ability. The estimated total summer heat related premature deaths in Beijing in 2007 were 5510. The estimation showed that the city and

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the suburb areas closest to the city have very high premature deaths. The outer suburb areas have relatively lower premature deaths. This information may provide policy intervention guidance.

Analysis of the 1996-2007 Malaria Morbidity Data from the Kenyan Health Management Information System

Ayub Manya, Ministry of Public Health and Sanitation, Kenya

Malaria is the leading cause of morbidity and mortality in Kenya. Close to 70% of the population is exposed to the risk of the infection. Approximately 30% of outpatient attendance and 19% of all admissions in public health facilities is due to malaria. Close to 5% of those admitted due to the disease die. The most affected are children below five years of age and pregnant women.

The main source of malaria data is the Health Management Information System (HMIS). Despite its imperfect coverage and incompleteness, HMIS is a potential source of baseline epidemiological information that can be used to target interventions and track disease trends. Outpatient morbidity and climatic data for 1996-2007 were analyzed with the objective of determining malaria trends and establishing the climatic association. The null hypothesis for this study was that there was no relationship between observed malaria morbidity trends and the rainfall pattern.

We reviewed the 1996-2007 HMIS outpatient data from all the provinces. The excel databases were uploaded in the International Research Institute for Climate and Society (IRI) Data Library for analysis. Malaria trends for 1996 to 2007 were established and compared with the trends for all outpatient case. Malaria cases were then mapped according the provinces. Rainfall pattern for the same period was established using data from the IRI Data Library.

The result we found is that the malaria morbidity trend over the years was similar to the general outpatient trend with cases increasing from 1996 up to 2000. A decline of cases was noted from 2000, reaching the lowest peak in 2002. From 2003, there was a steady increase in cases up to 2006. Figures1 and 2 show the trends of the general outpatients and the malaria morbidity respectively.

Blooms of toxin-producing harmful algal Blooms on the Washington State Coast, USA: Climato-logical Patterns, Long Term Trends, and Relationships to Environmental Parameters

Stephanie K. Moore1, Vera L. Trainer, Barbara M. Hickey2

1NOAA’s West Coast Center for Oceans and Human Health, Seattle WA

2University of Washington, School of Oceanography, Seattle WA

The Olympic Region Harmful Algal Bloom (ORHAB) monitoring program began in 2000 to better manage outbreaks of marine biotoxins on the Washington State coast of the United States. The harmful algae and the toxins they produce are measured approximately twice monthly at 6 core locations. The primary phytoplankton species of concern are Pseudo-nitzschia. The toxin (domoic acid) accumulates in shellfish (razor clams) and causes Amnesic Shellfish Poisoning (ASP) is contaminated shellfish are consumed by humans.

Here we investigate seasonal patterns and long-term interannual trends in the abundance of Pseudo-nitzschia on the Washington State coast and determine if there are any relationships with environmental and climatic parameters.

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This is an initial step towards an assessment of the possibility of developing an early warning system for toxigenic blooms of Pseudo-nitzschia on the Washington State coast. An early warning system that integrates cell counts with readily available indices of environmental and climate parameters would benefit State Health Authorities by informing harvesting and monitoring practices in space and time.

We hypothesize that 1) the seasonal development of blooms of Pseudo-nitzschia is related to environmental and climatic parameters, and 2) long-term interannual trends in bloom magnitude are related to anomalies in environ-mental and climatic parameters.

Cell abundances were provided from the ORHAB monitoring program. Seawater was collected from the surf zone at the 6 core monitoring locations. Pseudo-nitzschia cell counts were performed using light microscopy. The frequency of sample collection is patchy, but in general samples are obtained at weekly intervals during the summer-fall bloom season. Samples are obtained less frequently in the winter months, and are generally obtained twice monthly from Dec to Feb. Data are examined here from 2000 to 2008.

Gridded information on mixed layer depth (Behringer et al. 2004), sea surface temperature (Reynolds et al. 2006), and cloudiness (Kalnay et al. 1996) were obtained from the International Research Institute for Climate and Society (IRI) Data Library from Jan 2000 to Dec 2008. Monthly average values were calculated for the area 122°W-125°W and 46°N-49°N, and these values were used to calculate climatological monthly mean values and monthly anoma-lies. Monthly values of the Niño 3.4 index were also obtained to represent the behavior of the El Niño Southern Oscillation (Reynolds et al. 2006). The Niño 3.4 Index is the sea surface temperature anomaly in the region of the equatorial Pacific Ocean 120°W-170°W and 5°S-5°N. Seasonal patterns of bloom development and long-term interannual trends in bloom magnitude were compared to these environmental and climatic parameters.

The conclusions of the study were that Pseudo-nitzschia blooms typically occur in the summer and fall and coincide with shallow mixed layer depths and warm sea surface temperatures in the coastal ocean, as well as little cloud cover. However, no clear relationship could be found between the abundance of Pseudo-nitzschia cells and the environ-mental and climatic parameters when the seasonal pattern was removed. This indicates that other factors may be more important in determining the interannual variability in bloom magnitude. Interactions among parameters and time lags in the system may also be important. Identifying the “drivers” of exceptionally large bloom years on the Washington coast and the refinement of early warning systems remains an active area of research.

Mortality and Climate Variability at the National Hospital of Niamey, Niger

Mouhaimouni Moussa. National Meteorological Office of Niger

During the temperature outbreak that occurred between April and early May 2010 a lot of deaths had been recorded mostly elderly at the national hospital of Niamey. The objective and hypothesis of the study was to seek the link that could exist between the number of deaths and the maximum temperature in order to develop a model that will serve as a tool of early warning related to extreme temperature at Niamey.

Daily data from 1988 to 2009 where used to examine the variability of the maximum temperature and the number of death during that period after determining the threshold of the maximum temperature from witch people could die. There’s a link between the heat waves and the death and it’s getting hotter and hotter. With a threshold of 29°C the risk of death is about 100% mainly on March, April and May

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Understanding Seasonality and Climate Variability as a tool for Disease Attenuation in Nigeria

Andrew Oniarah. Nigerian Meteorological Agency, Oshodi, Nigeria

Malaria is one of the diseases that contributed to health problems in Nigeria and this research intends to look at changes in seasons and the climate variability as it favors the spread of some of these diseases. The objective of this study is to examine the trend and the anomalies in the seasonal rainfall and identify seasons and years that favor the transmission of diseases in Nigeria using the west coast as a case study.

The data used for this study is the monthly rainfall data for 59 years (1951-2009) obtained from the Nigerian Meteorological Agency. The monthly data have been considered for three seasons. These are the Mar-May (MAM), June-August ( JJA) and August-October (ASO) seasons. In each of the seasons, the rainfall trend is examined and the anomalies are deduced using the World Meteorological Organization (WMO) climatological years (1971-2000). The analysis was carried out using Microsoft Excel tool.

The result of the analysis shows that between the periods 1951 and 2009, rainfall had been on a steady increase for the MAM, JJA, and ASO seasons investigated for the coastal areas of Benin, Ikeja, Port-Harcourt and Warri. Ikeja and Benin depict high anomalous (above average) rainfall conditions between the period 1965 and 1970 during the MAM and JJA seasons, and this period coincide with years the area recorded high cases of malaria. In the recent years, Warri and Ikeja had shown more pronounced above average rainfall conditions during the JJA season.

The above average rainfall in MAM and JJA seasons in recent years is so pronounced, thereby, suggesting a favorable condition for the breeding of mosquitoes and hence increased chances of malaria, yellow fever and dengue. Both seasons showed upward trend in rainfall in the coastal areas investigated. We suggest adequate provision of preven-tive measures and malaria drugs, and we also recommend that further studies should be conducted with the aim of arriving at good and adequate

Distribution of Plasmodium vivax and Plasmodium falciparum in Lume district, Ethiopia.

Hiwot Teka1 and Abenet Girma 2

1 USAID /PMI Ethiopia

2 Climate and Health Working Group/Anti-Malaria Association

Malaria is one of the top 10 leading cause of outpatient consultations, admissions and deaths in Ethiopia. Plasmo-dium falciparum and P. vivax malaria are the two species found in Lume district, Ethiopia. Rainfall variability is known to affect the development of mosquito vectors. In this project it is aimed to test the hypothesis that a lagged correlation exists between rainfall and cases of P. vivax and P. falciparum. The objective of the project is to assess the temporal distribution of malaria parasite across Lume district, Oromia region, Ethiopia and to see if there exists a relation between rainfall and P. vivax and P. falciparum. Satellite data of rainfall in Lume district was extracted from the IRI data library to compare against the distribution of P. vivax and P. falciparum cases. Monthly malaria case data from Lume district was used for analysis. Lagged correlation analysis was used to assess the correlation between rainfall and malaria cases.

The results highlight the lagged correlation of malaria cases with rainfall from 1998-2004 though the relationship

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was not strong. Seasonal analysis of rainfall and malaria showed the same trend. The decrease in malaria cases after 2004 could not be explained by the variation in precipitation; other climatic and intensified intervention efforts put in place by the Ethiopian Federal Ministry of Health could be contributing factors.

Relationships between climate and year-to-year variability in meningitis outbreaks: A case study in Burkina Faso and Niger

Yaka P. 1, Sultan B. 2, Janicot S. 2, Broutin H. 3, Philippon S. 1, Fourquet N. 1

1 Direction de la Météorologie, 01 BP : 576, Ouagadougou, Burkina Faso / ProdiG, UMR 8586, 2 rue Valette, 75005 Paris, France

2 IRD – LOCEAN/IPSL (UR 182, UMR 7159 IRD-CNRS-UPMC) Université Pierre et Marie Curie, 4 place Jussieu, 75252 Paris cedex 05, France.

3 G.E.M.I, UMR CNRS/IRD 2724, Equipe « Evolution des Systèmes Symbiotiques »

Institut de Recherche pour le Développement (IRD), 911 Avenue Agropolis, BP 64501 34394 Montpellier Cedex 5, France

Every year, West Africa is afflicted with Meningococcal Meningitis (MCM) disease outbreaks. Although the seasonal and spatial patterns of disease cases are closely linked to climate, the mechanisms responsible for these patterns are still not well identified.

The objective of this study is to investigate the role of climate on the triggering of MCM epidemics by using a long-term dataset and to explore the possibility to include the climate conditions as a predictor of meningitis epidemics.

Our hypothesis, based on literature, is as so: dry and windy weather conditions in early winter might cause damage to the mucous membranes of the respiratory system and/or inhibits mucosal immune and therefore create propitious conditions to the triggering of MCM epidemics

A statistical analysis of annual incidence of MCM and climatic variables has been performed to highlight the relationships between climate and MCM for two highly afflicted countries: Niger and Burkina Faso. We found that disease resurgence in Niger and in Burkina Faso is likely to be partly controlled by the winter climate through enhanced Harmattan winds. Statistical models based only on climate indexes perform well in Niger showing that 25% of the disease variance from year-to-year in Niger can be explained by the winter climate but fail to represent accurately the disease dynamics in Burkina Faso.

The disease resurgences in Niger and in Burkina Faso are linked with an enhancement of the winter conditions, such as enhanced Harmattan winds over Niger in November/December and over Burkina Faso in October.

This study is an exploratory attempt to predict meningitis incidence by using only climate information. Although it points out significant statistical results it stresses the difficulty of relating climate to interannual variability in meningitis outbreaks.

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Course Awards

Course AwardsFor the first time since the implementation of the Summer Institute, award prizes were implemented to acknowl-edge outstanding performances.

As acknowledged by the Poster Prize Committee, the “Best Poster” award was attributed to (by order of merit): Tiantian Li from the CDC of China, Betty Abang, from the Uganda CDC, Office of Uganda and Pascal Yaka from the Burkina Faso Meteorological Office.

The “Excellence in Teaching,” award was attributed by the trainees to Pietro Ceccato, from the IRI. Tony Barston, from IRI, received an award in recognition of his involvement, active interaction and timeliness during the pre course development.

The “Best IT Innovation” prize was attributed to Jeffrey Turmelle, from the IRI, for the development of the CIPHAN Web-page. Sandy Vitelli, from the IRI, received the award for “Best Logistic Support”, and the award for “Best innovation in the development of the course curriculum” was attributed to Laurence Cibrelus, also from the IRI.

The SI10 Evaluation Team (from left to right): IRI Gilma Mantilla, Lancaster School of Medicine Michelle Stanton and IRI Laurence Cibrelus. Francesco/IRI

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Course Evaluation

Course EvaluationAll course participants, including the trainees, facilitators, organizers and support staff, were invited to provide feedback on various aspects of SI 10. This evaluation process was completed online and consisted of various multiple choice and open-ended questions, and was led by Michelle Stanton, a 2008 Summer Institute alumna. The process was entirely anonymous and provided all participants with the opportunity to comment on the design and delivery with the purpose of using this information to improve future climate and health training courses.

The detailed evaluation process is available on a separate document, but the main conclusions are summarized in the next paragraph.

Organizers of SI2010 (from left to right): IRI Stephen Zebiak, IRI Madeleine Thomson, CIESIN Mark Becker, MSPH Patrick Kinney. Francesco Fiondella/IRI

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Conclusions

Conclusions SI 10 was deemed to be a success by both trainees, facilitators, organizers and support staff. The trainees were very satisfied with the contents of the course, and in particular praised the amount of hands-on experience they were able to acquire. Further, the course provided an environment in which members of the public health and climate communities could exchange ideas and form collaborations, which will extend beyond the confines of the course itself. Trainees benefitted greatly from the expert knowledge provided by the course facilitators, and from the experi-ence of the organizers and support staff in addition to expressing enthusiasm about taking these skills to their own institutions in order to train others.

Trainees, facilitators, organizers and support staff regarded the SI 10 very highly. It is clear from the evaluation reports that the greatest strengths of SI 10 are the involvement of experts from a variety of backgrounds in deliver-ing the contents of the course, and the practical experience gained through the afternoon sessions using the Data Library. Through encouraging discussions between the trainees and the facilitators, the SI 10 has facilitated the exchange of ideas, which are likely to lead to future collaborations between members of the climate and health community. Further, SI 10 has provided a framework that trainees intend to follow in order to provide training in their own institutions.

New features of SI 10 included a daily review session lead by a trainee, a discussion of the previous day’s sessions lead by one the facilitators, a daily quiz, giving the trainees the opportunity to use their own data for their projects, developing poster presentations and using the CIPHAN Web-page as a support to the course. On the whole, these additions were very well received and assisted in consolidating the key points of each of the sessions, and further successfully encouraged the trainees to feel more involved in their projects. The facilitators also appreciated the daily review sessions as they aided in reassuring them that their main messages had been successfully conveyed.

In addition to the praise the course received, a number of recommendations to take into account when planning the future courses were proposed. The most frequently mentioned proposition, made by both trainees and facilitators, related to the project and the practical exercises. It was recommended that more time be allocated to complete the practical tasks and to work on the projects. This would improve the trainees’ understanding of the skills that they had been taught, and increase their confidence in using the Data Library. Trainees expressed some confusion relating to what data was required for their projects; hence clearer guidelines for this would also be beneficial. Further, it was suggested that there is a larger staff involvement in the projects. To compliment the increase in time committed to practical sessions, it was suggested that the material covered during the course be scaled back.

The IT support during the course, although adequate, could be improved. In particular, it was suggested that two IT support staff should share the workload each day, with one person being available for the morning sessions and another being available for the afternoon.

The amount of work associated with printing, organizing and binding the course material was stated to be excessively time consuming. The support staff recommended that either this task is outsourced in the future, or the amount of printed material be decreased and alternative methods such as storing documents on pen drives be used.

Further recommendations included getting Mailman School of Public Health more involved in the Summer Insti-tute, and removing lunchtime seminars from the course schedule. In addition, clearer guidelines need to be provided to the facilitators regarding the setting of quiz questions. In particular, it may be suitable to use a multiple choice quiz format only in the future.

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Conclusions

We shall leave the concluding words to the trainees themselves:

“All the speakers were great!”

“It was very good and interactive”

“I have gained amazing knowledge and skill in the use of climate information in public health practice”

“The hands-on experience we got in the practical sessions exceeded my expectations”

“The practical sessions are the backbone of the course”

“This training gave me lots of ideas on how to run training in my own institute”

“I have met people from different countries and disciplines.The interactions were fruitful and I hope to use these contacts

for more collaboration”

“The course for the training was carefully designed and well planned”

“Exposure to the Data Library with hands-on experience and availability of interna-tionally renowned expertise in all aspects of climate and health at

the Summer Institute is the uniqueness of the course”

“The faculty, facilitators and organizers of the course deserve commendation”

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Recommendations

Recommendations

Application Process

Despite the successes of the Summer Institute in rapidly increasing application rates (up 212% since just last year – from 43 in 2009 to 134 in 2010) and attracting well-qualified applicants, the information in the applicants report also sheds light on a number ways in which improvements may be made surrounding the Summer Institute recruit-ment process.

With many applicants learning about the Summer Institute via IRI Communications, including CIPHA Newslet-ters and Summer Institute promotional emails, it would be wise to continue actively expanding the CIPHA Contacts Database. This can be accomplished through a number of activities including network building with members of IRI and IRI affiliates and collaborators, as well as (again) through social media. Linked to such network building and, additionally, building upon word-of-mouth promotion, it is suggested that there be increased efforts aimed at collaborating with, and marketing towards, universities.

It is clear that demand for the Summer Institute workshop far exceeds the limits of face-to-face training that can be effectively supplied by the IRI. There is therefore a need for the rapid development of an online learning network that can educate those applicants who are either not accepted into the Summer Institute or who are otherwise incapable of participating due to such limitations as financing their trip or taking two full weeks away from their work responsibilities. The expansion of this website could also prove a successful new tool for Summer Institute marketing and recruitment efforts

Evaluation Process

It was clear that there was some dissatisfaction with the balance between lectures and practical sessions. There were a number of comments from those involved in organizing the course suggesting that perhaps too much material was being covered, and would be improved by scaling back on the content of the course, and increasing the amount of time available to work on the practical aspects.

Further recommendation in relation to the projects were that there be a greater staff involvement in the projects, hence providing a greater amount of guidance to the trainees regarding what was expected of them. Further, some of the trainees suggested that further information be provided to trainees prior to the start of the course regarding what kind of data would be suitable for their projects.

With respect to the addition of the daily quiz and review session, both were very well received and generally well answered by the trainees, although there were comments that not enough time was available to complete these tasks. In order to overcome this issue, it’s recommended that the quiz questions be limited to multiple-choice questions in order to reduce the amount of time required to answer then. Further, it may be beneficial to extend the session slightly.

Lunchtime seminars were not well received as trainees felt that these sessions were not given their due attention as the course itself is so intensive. Trainees believed that lunchtime would be better spent taking a proper break.

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Recommendations

The support staff expressed some concern regarding the amount of work involved in preparing the printed course material for SI 10. As this was a very time consuming task it was suggested that this task be outsourced. Alterna-tively, the amount of printed material provided to trainees could be reduced by storing some of the non-essential material on a pen drive.

It was also suggested that the number of IT support staff available was inadequate. During SI 10, one member of staff was responsible for the IT support for the whole course. It was recommended that this be increased to two in future years, and each staff member would either be responsible for the morning or afternoon sessions.

A final recommendation made by the course organizers is that Mailman School of Public Health increases their involvement in the course.

Appendixes to this document are available from a separate link.

technical report:

Summer Institute on Climate Information for Public Health 2010: Appendices

Gilma Mantilla, Michelle Stanton, laurence cibrelus

TR10-11


Appendices to:IRI Technical Report 2010 Summer Institute on

Climate Information for Public Health

Summary of the Climate Information for Public Health Training Course

Palisades, New York

May 17- 28, 2010

Gilma Mantilla

Michelle Stanton

Laurence Cibrelus



Palisades, New York, 10964, USA





http://iri.columbia.edu/publications/id=1011

With trainees’ sponsorship by:

Spanish Meteorological Office

Google.org









Contents

Appendix 1: Participants Bios 3

• Trainees 3

• Facilitators 7

• SupportStaff 18

Appendix 2: Sponsors of the Participants 22

Appendix 3: Course Flyer 24

Appendix 4: Application Form 26

Appendix 5: Application Report 28

Appendix 6: Panel Discussion Invitation 50

Appendix 7: Daily Quiz Questions and Answers by Module 51

Appendix 8: Trainees’ Posters 74

Appendix 9: Poster Prize Form 80

Appendix 10: Contact Information 81

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Summer Institute 2010 | Final Report: Appendices

Appendix 1: Participants Bios


Trainees

Betty AbangGIS AnalystThe U.S. Centers for Disease Control and Prevention, UgandaMs. Abang currently serves as a Geographic Information Systems Analyst for the U.S. Centers for Disease Control and Prevention in Uganda where she has recently spent time reviewing location data that has been collected for the investigation of Nodding Disease. Prior to serving in this context, she spent a number of years as a Data Manag-er, also for the CDC in Uganda, a Research Assistant with the International Food Policy Research Institute in Uganda, and a Field Surveyor with Century Bottling Company Limited. Ms. Abang was the recipient of the Individual Franklin Award in 2009 and has authored several peer-reviewed publications. She earned her Bachelor’s degree in Food Science and Technology from Makerere University, Kampala, Uganda.

Wakgari AmenteUniversity InstructorSchool of Public Health, Addis Ababa University, EthiopiaDr. Amente currently holds the title of Assistant Professor of Epidemiology and Public Health at the School of Public Health, Addis Ababa University in Ethiopia. Previously, he has held a number of teaching and non-teaching positions within academia in addition to serving as Malaria Epidemiology Team Leader with the Oromia Regional State Health Bureau and Malaria Control Team Leader with the West Harerge Zone Health Department. Dr. Amente acts as a peer reviewer for several scientific journals, has authored numerous peer-reviewed publications, and was the recipient of the Gold Medal for the 2007 Young Public Health Research Award of the Ethiopian Public Health Association. He earned his B.Sc. in Biology, MPH, and PhD in Public Health from Addis Ababa University in Ethiopia.

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Yilma BekeleResidentAddis Ababa University, EthiopiaMr. Bekele currently serves as a Resident at the Oromia Regional Health Bureau’s Public Health Emergency Management and Research area for his MPH degree through Addis Ababa University in Ethiopia. Prior to this appointment, he was the Communicable Diseases’ Team Leader for the Borena Zone. Mr. Bekele’s ongoing work consists of developing malaria prediction models, in addition to the development of malaria risk mapping. Prior to pursuing his MPH degree, Mr. Bekele earned his Comprehensive Nursing degree from Nekemt Nursing School in Ethiopia, as well as a B.Sc. in Public Health from Jimma University in Ethiopia.

Ali BouattourHead of Medical Entomology LaboratoryPasteur Institute of Tunis, TunisiaDr. Bouattour currently serves as the Head of the Medical Entomology Laboratory at the Pasteur Institute, Ministry of Health, in Tunisia. Previously, he served as the Head of the Parasitology Laboratory for the Veterinary Institute, Ministry of Health, worked as a Scientific Consultant for the Ministry of Environment and Sustainable Develop-ment, and served as Senior Lecturer in Arthropod Vectors and Vector-Borne Diseases at Faculty of Science, Tunis. Dr. Bouattour was the 2006 recipient of the North Africa Veterinary Research Prize and has authored numerous peer-reviewed publications. In addition to a Bachelors degree in the Sciences, Mr. Bouattour earned his DVM in Veteri-nary Medicine from the Veterinary School of Tunis, M.S. in Ecology Parasitology, PhD in Vector Entomology from the Faculty of Sciences Tunis, and HDR in Vector and Vector-Borne Diseases from Pasteur Institute.

Ramesh Chand DhimanScientist/Deputy DirectorNational Institute of Malaria Research, Indian Council of Medical Research, IndiaDr. Dhiman currently serves as Scientist/Deputy Director at the National Institute of Malaria Research in New Delhi, India. Before entering this position, he acted as Assis-tant Director and Senior Research Officer for the National Institute of Malaria Research and held numerous other research positions with various organizations in India. Dr. Dhiman is a Co-Leader for the Global Earth Observation Environment and Health com-munity of practice, has contributed to work on climate change and health, including efforts with the WHO, IPCC, and Indian government, and is widely published. Prior to earning his PhD in Parasitology/Entomology from the Zoological Survey of India in Jodhpur, Dr. Dhiman earned his B.Sc. in Botany/Chemistry/Zoology and M.S. in Zool-ogy with specialization in Entomology from Meerut University.

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Abenet Girma DessalegnProgram CoordinatorClimate and Health Working Group of Ethiopia, EthiopiaMs. Girma Dessalegn currently serves as the Program Coordinator for the Climate and Health Working Group of Ethiopia. Prior to this position, she held Program Coordina-tor positions for the MERIT-Ethiopia case study with the Climate and Health Working group of Ethiopia as well as The Biological Society of Ethiopia, and was the main teach-er for the preparatory class at the School of Tomorrow. Ms. Girma Dessalegn earned her B.Sc. in Animal Science from Alemaya University in Ethiopia and M.Sc. in Ecological and Systematic Zoology from Addis Ababa University in Ethiopia.

Tiantian LiAssociate ResearcherInstitute For Environmental Health And Related Product Safety, Chinese CDCChinaDr. Li currently serves as an Associate Researcher at the Institute for Environmental Health and Related Product Safety within the Chinese Center for Disease Control and Prevention. Additionally, she is performing postdoctoral training in Environmental Health focusing on climate change and health with the Department of Environmen-tal Health Sciences at Columbia University’s Mailman School of Public Health in New York. Dr. Li has authored numerous peer-reviewed publications, with her academic and research achievements being recognized through several honors and awards. She earned her B.Sc. in Biochemistry from Beijing Union University and PhD in Environ-mental Sciences focusing on air pollution and exposure from the College of Environ-mental Sciences at Peking University.

Ayub Shisia ManyaMedical EpidemiologistDivision of Malaria Control, Ministry of Public Health and Sanitation, KenyaDr. Manya currently serves as a Medical Epidemiologist for the Division of Malaria Con-trol at the Ministry of Public Health in Kenya where he is the Monitoring, Evaluation, and Global fund focal person. He also acts as a part-time lecturer of molecular epide-miology to masters’ students at Jomo Kenyatta University of Agriculture and Technol-ogy. Prior to his current work, Mr. Manya performed a residency with the Field Epide-miology and Laboratory Program and served as District Medical Officer of Health in charge of the districts of Migori and Nyamira, in addition to other previous positions. He has authored peer-reviewed works on the hospitalization of various diseases. Dr. Manya earned his M.B. Ch.B. in Medicine from the University of Nairobi in Kenya and MSC in Epidemiology from Jomo Kenyatta University of Agriculture and Technology.

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Stephanie Kay MooreResearch AssociateNOAA’s West Coast Center for Oceans and Human Health, USADr. Moore currently serves as a Research Associate II for NOAA’s West Coast Center for Oceans and Human Health and the University Corporation for Atmospheric Research. Prior to her current position, she performed her post-doctorate work on the impacts of climate on harmful algae blooms through the University of Washington in Seattle and the University Corporation for Atmospheric Research in Boulder, CO, also serving as an Estuary Officer and Teaching Assistant. In addition to her numerous peer-reviewed publications, Dr. Moore’s academic achievements have been honored with a number of awards. She earned her B.Sc. in Advanced Environmental Science and PhD in Estua-rine Ecology and Nutrient Dynamics from the University of New South Wales, Sydney NSW Australia.

Mouhaimouni MoussaHead of Climatological AnalysesNational Meteorological Office of Niger Republic, NigerMr. Moussa currently serves as the Head of Climatological Analysis for the National Me-teorological Office of Niger Republic. Prior to his current work, he held other positions within the National Met Office, including Climatological Database Manager and Con-tract Staff. Mr. Moussa has authored several peer-reviewed publications. He earned his Bachelor’s degree in Science from Lycee Agabba, DUES in Physics and Chemistry from the University of Niamey, and Engineering degree in Agrometeorology from AGHRYMET.

Hiwot NamagaMalaria AdvisorUSAID, EthiopiaMs. Namaga currently serves as Malaria Advisor with the United States Agency for International Development in Ethiopia. Prior to this role, she acted as Program Coor-dinator for the Climate and Health Working Group/Anti-Malaria Association in addi-tion to malaria project work at the Armauer Hansen Research Institute. Ms. Namaga was the 2008 recipient of the Tore Godal Award for outstanding malaria research. She earned her B.Ed in Biology from Debub University and M.Sc. in Biomedical Sciences from Addis Ababa University.

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Andrew OniarahDeputy General Manager (Investigation)Nigerian Meteorological Agency, NigeriaMr. Oniarah currently serves as Deputy General Manager (Investigation) for the Nigerian Meteorological Agency. Prior to this position, he acted as Assistant General Manager and Chief Meteorologist, among other positions. Mr. Oniarah has authored peer-reviewed work and is currently working on investigating the impacts of climate variability on the people of Nigeria. He earned his B.Sc. in Geography and M.Sc. in Cli-matology from the University of Ibaden in addition to FSLC, WASCE, and HSC degrees.

Dieudonné Pascal Alda YakaChief of “Environment and Bioclimatology” DeskDirection La Météorologie, Burkina FasoDr. Yaka currently serves as Chief of the “Environment and Bioclimatology” Desk with the Direction de la Météorologie in Burkina Faso. Prior to his current position, he was a Lecturer and Research Deputy at the Practical School of High Studies of Paris, worked as a Geographer at the University of Paris VII, and held several scientific positions as a Climatologist and Biometeorologist. Additionally, Dr. Yaka has consulted for the World Bank and World Meteorological Organization, and has authored several peer-reviewed publications. He earned his Bachelor’s degree in Mathematics and Biology from Philippe Zinda Kabore High School in Burkina Faso, Engineering degree in Meteorol-ogy from Hydrometeo Training and Research Institute in Algeria, and PhD in Climatol-ogy from the Practical School of High Studies Paris in France.

Facilitators

Walter BaethgenDirector, Latin America/Caribbean, IRIDr. Baethgen is the Director of the Program for Latin America and the Caribbean at the IRI where he has been establishing regional research programs that aim to improve climate risk assessment and risk management in agriculture, health, water resources, and natural ecosystems. Before joining the IRI Baethgen was a Senior Scientist in the Research and Development Division of the International Soil Fertility and Agricultural Development Center where he worked mainly in Information and Decision Support Systems for the Agricultural Sector (1987-2003). Since 1990 (first with IFDC and now with the IRI) he has been establishing and coordinating regional research programs in Latin America in collaboration He obtained his PhD and M.Sc. degrees in Crop and Soil Environmental Sciences from Virginia Polytechnic Institute and State University, and his B.Sc. in Agricultural Engineering from the University of Uruguay. He has over 100 publications to his credit with National and International organizations.

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Tony BarnstonDirector, Forecasting Climate, Prediction, Outreach, IRIPrior to arriving to the IRI at the end of June 2000, Tony Barnston was an operation-al seasonal climate forecaster and developmental researcher in empirical prediction methodology at the Climate Prediction Center of NOAA for 17 years. He has au-thored atlases, reports and journal papers on weather and climate, the best known of which were on statistical diagnosis of large-scale circulation patterns and on empirical climate prediction. With his forecast staff, he ensures the production and routinely scheduled issuance of a range of IRI forecast products, including monthly forecasts of sea surface temperatures (including an ENSO outlook) and global pre-cipitation and temperature.

Mark BeckerAssociate Director, Geospatial Applications Division, CIESINMark Becker leads the Geospatial Applications Division at CIESIN, and is an adjunct faculty member at the Mailman School of Public Health. His primary interests are the development of GIS applications for public health programs, and improving urban and regional planning through geospatial technologies. At CIESIN he has partnered with numerous departments and programs at Columbia University to assist in the use of geospatial technologies: with the Columbia Center for Children’s Environmental Health, looking at the effects of air pollution on children’s health; with the Columbia Superfund Basic Research Program, developing GIS training programs in Bangladesh; and working with the Research Translation Core of the program to bring the findings and techniques of the project to a wider audience. He holds an M.A. in Geography from Hunter College of the City University of New York.

Michael BellSenior Staff Associate, Climate Monitoring and Dissemination, IRIMichael Bell studied meteorology at the University of Oklahoma and graduated with Bachelor’s and Master’s degrees in 1994 and 2001, respectively. His master’s work involved the study of the decadal and interannual variability of West African rainfall disturbance lines. He joined the IRI in 2001. His research interests include rainfall variability in West Africa and, more generally, the contributions of weather variability to climate. Bell’s responsibilities include contributing to the monthly publication of the IRI Climate Information Digest, support of the IRI Data Library and Map Room, and data acquisition and analysis in support of regional programs and projects.

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Menno Jan BoumaIndependent ScientistDr. Bouma currently acts as an independent scientist, visiting research fellow at the National University of Ireland, and honorary senior lecturer at the London School of Hygiene & Tropical Medicine. Prior to his current work, he has spent time consulting on issues of malaria for numerous organizations including DFID, MSF, Health Net International, WHO, the World Bank, and Oxfam. Other experiences include acting as Project Manager of operational research and control of malaria in Pakistan with MSF, interim country manager for MSF supporting operational research activities for kala azar in Sudan and malaria in Pakistan and Afghanistan, and other medical and public health positions. He holds degrees in Epidemiology & Control of Malaria (PhD), Medicine (MD), Medical Parasitology & Medical Entomology (MSc), Psychol-ogy (BA), and Tropical Medicine and Hygiene (Diploma).

Daniel Ruiz CarrascalGraduate Research Assistant, PhD student, IRIDaniel is participating in the development of one of the components of the Nation-al Integrated Dengue and Malaria Surveillance and Control System, an initiative that has been proposed to mitigate the possible adverse effects of climate change on human health in his home country of Colombia. He is also interested in the poten-tial impacts of climate change on high mountain ecosystems. He is a graduate of Columbia University (M.A., Climate and Society, 2007) and the National University of Colombia (M.S., Water Resources, 2002, and B.S., Civil Engi-neering, 1997.)

Pietro CeccatoAssociate Research Scientist, Environmental Monitoring, IRIPietro Ceccato trained originally as an agronomist and soil science scientist. He ob-tained a Master in Environmental Management using decision-support systems and worked as a research scientist at the Natural Resources Institute in United Kingdom. He worked at the European Commission Joint Research Centre (Ispra, Italy) and used this work to obtain his PhD in Remote Sensing (2001, University of Greenwich, UK). Pietro then joined the UN Food and Agriculture Organization (Rome, Italy) to develop an early warning system for Desert Locust monitoring. He joined the In-ternational Research Institute for Climate and Society in 2004. His current research activities include the development and integration of environmental remote sens-ing products into early warning systems for human health, pest management and fire risk.

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Laurence CibrelusStaff Associate, Public Health, IRIAfter finishing her medical training in infectious diseases and public health in France, Spain and Switzerland at the headquarters of the World Health Organiza-tion (WHO), Laurence Cibrelus furthered her commitment to international health and infectious diseases prevention and control by pursuing a Master of Public Health in the Department of Epidemiology and the Global Health Track of the Mail-man School of Public Health, Columbia University. Laurence completed her mas-ter’s practicum in Niger on the drivers for meningitis outbreaks.

Ulisses ConfalonieriProfessor, FIOCRUZ & Federal University, Rio de JaneiroDr. Confalonieri is a professor at the National School of Public Health of the Oswal-do Cruz Foundation (FIOCRUZ) of the Brazilian Ministry of Health and a professor at the Federal University in Rio de Janeiro. He was trained in parasitology, internal medicine, epidemiology and veterinary medicine. At FIOCRUZ, Confalonieri co-ordinates the Program on Global Environmental Changes and Health. His current research focuses on the effect of changes in climate variability and change, ecosys-tem, biodiversity and land cover changes on human population health, especially on infectious diseases.

He has contributed to the reports of the IPCC, both as lead author and review edi-tor, and is a convening lead author for the Millennium Ecosystem Assessment. Cur-rently he is co-chair of the Earth System Science Partnership´s Global Environmen-tal Change and Human Health Project and Convening Lead Author for the Health Chapter of the IPCC´s Fourth Assessment Report (2004-2007).

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Steve ConnorDirector, Environmental Monitoring ProgramDirector, PAHO/WHO Collaborating Centre on Climate Sensitive Diseases, IRIStephen Connor joined the International Research Institute for Climate and Society in May 2002. Previously, he was based at the Liverpool School of Tropical Medicine and worked extensively in sub-Saharan Africa for the UK Medical Research Council and the UK Department for International Development’s (DFID) Malaria Knowledge Programmes. He has a background in Development Studies/Natural Resource Economics, has specialized in the geography of infectious disease, and has a PhD from the Faculty of Medicine at Liverpool University. Stephen has worked closely with the World Health Organization in Geneva and WHO-AFRO’s Inter-Country Pro-grammes on Malaria Control, providing technical support to Ministries of Health. He has been a frequent advisor to WHO’s Roll Back Malaria Technical Resource Network on Epidemic Prevention and Control. He is currently serving as a member of the World Meteorological Organization Task Force on Socio-Economic Applications of Weather, Climate and Water Services. He is the Director of the Pan America Health Organization/World Health Organization Collaborating Centre on Early Warning Systems for Malaria and other Climate Sensitive Diseases.

John del CorralSenior Staff Associate, Database, GIS, IRIJohn is interested in the role of computers and computational science in the multi-disciplinary areas of geophysical research. This includes high performance comput-ing, graphical techniques, geographical information systems, database technology, and learning the basic science in the areas of research. John is currently in the Climate Monitoring and Dissemination Division at the IRI. He is actively involved in the establishment and maintenance of a mirror site of the IRI Data Library in Taiwan. He has also built a geographical gazetteer database for IRI institute-wide use. This database incorporates OpenGIS geometries for representing political and geographic objects. John also participates in the current and future design and content delivery of the IRI website. He received his computer science degree from the University of Colorado.

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Rémi CousinStaff Associate, Data Library, IRIRémi Cousin received his degree from l’Ecole Nationale Supérieure des Mines de Nancy in engineering with majors in geo-sciences, in 2005. After specializing in physical oceanography through internships in l’Institut de Recherche pour le Dével-oppement and Mercator-Océan, Toulouse, France, and Universidad de Concepción in Chile, he worked for Collecte Localisation Satellite, a subsidiary of CNES, as a con-sultant at Mercator-Océan to develop user friendly tools to run and post-process Mercator ocean models dedicated to operational oceanography. Rémi then worked at the Jet Propulsion Laboratory (JPL), Pasadena, California, to develop a public out-reach and education website on ocean salinity in the context of the co-developed NASA satellite mission Aquarius, and to conduct research to support the activities of the OurOcean group, focusing on regional ocean models. Since 2008, Rémi has been a member of IRI Data Library to develop new functionalities and enable climate information communication and dissemination to end-users.

Peter DiggleProfessor of StatisticsLancaster University School of Health and MedicinePeter Diggle is Distinguished University Professor of Statistics in the School of Health and Medicine, Lancaster University and Adjunct Professor in the Department of Biostatistics, Johns Hopkins University School of Public Health. Peter’s research interests are in the development of statistical methods for spatial and longitudinal data analysis, motivated by applications in the biomedical, health and environmen-tal sciences. He has published 8 books and around 170 articles on these topics in the open literature. Peter is founding co-editor of the journal “Biostatistics,” now in its tenth year of publication. He is also a Trustee of the Biometrika Trust. Peter was awarded the Royal Statistical Society’s Guy Medal in Silver in 1997 and is a former editor of the Society’s Journal, Series B. He is also a Fellow of the American Statisti-cal Association.

Wayne ElliottHead of Health Forecasting, UK Met OfficeWayne is currently Head of the Health Programme at the Met Office in Exeter, hav-ing worked for the organization for 25 years. The work of the health forecasting team involves understanding how weather and other aspects of the environment impact people’s health, then using this knowledge to inform individuals and orga-nizations about the risk. Through the development of health forecasts, the aim is to keep people well and to maximize the effectiveness of healthcare resources. Originally, Wayne trained as a meteorologist, working at many locations across the UK and the world, to provide a range of weather and climate services for customers. As part of this, he presented the weather on BBC television before moving to become a senior lecturer at the Met Office College. In 2003, he became the Chief Press Officer at the Met Office managing the PR and media affairs for the organization.

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Dia-Eldin A. ElnaiemAssociate Professor of Applied Zoology, University of MarylandDr. Dia-Eldin currently works in the Department of Natural Sciences at the Univer-sity of Maryland. His previous work was at the Oak Ridge Associated Universities at the National Institutes of Health where he conducted research on biology of phle-botomine sand flies and transmission and epidemiology of leishmaniasis. He spent 15 years as a professor at the University of Khartoum in Sudan, where he taught courses on medical entomology, parasitology and basic zoology and conducted research on the epidemiology of leishmaniasis and malaria. He received his Ph.D. in Medical Entomology from the Liverpool School of Tropical Medicine.

Patricia GravesEpidemiologist , Carter Center Malaria Control Program,Dr. Graves joined The Carter Center in January 2007. As program epidemiologist, she provides scientific support to the Center’s Malaria Control Program. An epide-miologist and entomologist, Dr. Graves has 25 years experience in applied research and project management in vector-borne disease epidemiology and control, including 11 years advising aid agencies and national governments in Asia, the Pa-cific, and Africa. She contributed key knowledge to malaria transmission dynamics during a large malaria entomological research project in Papua New Guinea, which she directed. Her recent significant contributions include the use of evidence and information to assess and improve the effectiveness of control measures for malaria and filariasis. She received her BA from Cambridge University, her doctorate in sci-ence from the London School of Hygiene and Tropical Medicine and her MPH from the University of Colorado Health Sciences Center.

Patrick KinneyAssociate Professor of Environmental Health Sciences Columbia University, Mailman School of Public HealthDr. Kinney’s teaching and research address issues at the intersection of global environmental change, human health, and policy, with an emphasis on the public health impacts of climate change and air pollution. He has carried out numerous studies examining the human health effects of air pollution. He developed a new interdisciplinary research and teaching program at Columbia examining the poten-tial impacts of climate change on human health. Dr. Kinney was the first to show that climate change could worsen urban smog problems in the U.S., with attendent adverse health impacts. He earned his PhD at the Harvard School of Public Health.

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Kim KnowltonAssistant Clinical Professor of Environmental Health Sciences Columbia University, Mailman School of Public HealthAnd Senior Scientist, Natural Resources Defense CouncilKim Knowlton is Senior Scientist on NRDC’s Global Warming and Health Project. She works with the Health and Environment Program on communicating the health impacts of global warming, and also on advocating for public health strategies to prepare for and prevent these impacts. Her research has looked at heat- and ozone-related mortality and illnesses as well as possible connections between climate, pollen, allergies and asthma. She attended Cornell University and Hunter College/CUNY, and received a doctorate in public health from Columbia University, where she was a postdoctoral research scientist before joining NRDC, and where she is currently Assistant Clinical Professor in the Department of Environmental Health Sciences.

Richard LuceResident Advisor, Ethiopia Field Epidemiology and Laboratory Training Program, Center for Disease Control and Prevention, EthiopiaDr. Luce completed his BA degree at Southern Methodist University and attended veterinary school at North Carolina State University. He completed a clinical intern-ship in large animal medicine and surgery at Texas A&M University. He holds an MA in International Affairs from Columbia University and an MPhil in veterinary science (epidemiology) from the University of Cambridge. He completed the U.S. Centers for Disease Control and Prevention’s (CDC) Epidemic Intelligence Service program as well as the CDC’s Preventive Medicine Fellowship program. He has worked for as an epidemiologist for the Wyoming Department of Health, the CDC Dengue Fever Branch in Puerto Rico and most recently as the Resident Advisor to Ethiopian Field Epidemiology and Laboratory Training Program.

Bradfield LyonResearch Scientist, Climate Diagnostics, Drought, IRILyon received his Ph.D. in meteorology from MIT and joined the IRI in 1999. His research activities are focused on observational and modeling diagnostic studies of climate variability, primarily on time scales associated with seasonal to interan-nual variability but also including climate change. He is particularly interested in investigating causal mechanisms, regional manifestations, prediction, and impacts of drought. While active in climate diagnostic research, he also serves as a liaison and coordinator for climate research studies in the Philippines and Vietnam. With a focus on observational studies of climate variations he participates in monthly updates of “real time” global climate variations including the status and evolution of ENSO. He is involved in a number of IRI’s climate risk management projects and contributes to training and capacity building activities conducted at the IRI and in countries of IRI regional partners.

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Gilma MantillaSenior Staff Associate, Public Health, IRIDr. Gilma Mantilla is a graduate of Columbia University (Climate and Society MA, 2008), Rosario University, Colombia (Epidemiology 1998), Javeriana University, Co-lombia (Master in Health Management, 1993) and Escuela Colombiana de Medicina (Physician Surgeon, 1988). Before joining IRI, she was Colombia’s Public Health Sur-veillance and Control Deputy Manager at the National Health Institute where she worked mainly to establish policies, plans, programs and projects in public health associated with the surveillance and control of infectious diseases; to redesign the National Infectious Diseases Surveillance System and to support operational re-search on issues like epidemics, outbreaks and disasters. In the IRI she is working to establish tools and protocols for creation, integration and dissemination of knowl-edge and information related with climate and public health.

Sabine MarxAssociate Director, Center for Research on Environmental Decision MakingDr. Marx joined CRED in January 2005 after two years of post-doctoral work at the IRI. She received her Ph.D. in medical history from Carnegie Mellon University, and holds Masters degrees in Sociology, Pedagogy, Psychology, and Art Therapy from the University of Cologne, Germany. The work of Sabine Marx falls in the area of decision making under uncertainty with a focus on seasonal climate forecast use, particularly in public health and agricul-ture. She is especially interested in the integration of physical sciences and social sciences, and outreach to decision makers and policy makers. At CRED, Dr. Marx is responsible for the coordination of 20 plus research projects and for building syn-ergy among the various projects.

Simon MasonResearch Scientist, Forecasting, Prediction Research, IRIMason has been involved in seasonal climate forecasting research and operations since the early 1990s. He has extensive experience in the production of seasonal climate forecasts in contexts such as the Regional Climate Outlook Forums, and works closely with the World Meteorological Organization to promote the defini-tion and adoption of forecasting and verification standards through engagement in the relevant WMO Expert Teams and through the WMO CLIPS Capacity Building Workshops. Mason’s primary areas of research include development of methods for diagnosing the quality of forecasts (“forecast verification”), and for recalibrating ensemble predictions. As part of the IRI’s outreach and collaboration with other partners, Mason has been heavily involved in capacity building activities, including leading the development and support of the Climate Predictability Tool.

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Judy OmumboAssociate Research Scientist, Epidemiology, Disease Risk Modeling, IRIDr. Judy Omumbo is an Associate Research Scientist at the International Research Institute for Climate and Society (IRI). Her scholarly work has been mainly on GIS-based mapping of malaria in East Africa using climate data and empirical malar-iometric data. Her current work is on developing risk maps of climate sensitive diseases in Africa including Rift Valley fever, meningitis and malaria. She is a gradu-ate of Oxford University (PhD, 2004), Hebrew University, Jerusalem (Master in Public Health 1993) and the University of Nairobi (Bachelor of Dental Surgery 1987).

Carlos PerezSenior Analyst for Sustainable Development, IRIDr. Carlos A. Pérez is an Ecological Anthropologist who works for the IRI as Senior Analyst for Sustainable Development. His research focuses on the social dimensions of climate variability and economic vulnerability within agriculture and natural resources management, and particularly the strategies that small-farmers use to adapt to economic and climatic risks.

He has 25 years of professional experience in research, design and management, and provision of technical assistance for sustainable development and environment projects. His entire career has been within interdisciplinary collaborative teams, linking science and practice for sustainable development. Before joining the IRI, Dr. Pérez was Associate Director of the Tropical Agriculture Program, at Columbia Uni-versity. Previously he served as the Director of the Collaborative Research Support Program for Sustainable Agriculture and Natural Resource Management (SANREM CRSP) at the University of Georgia, Athens. He has a PhD in Anthropology and MA in Sociology from the State University of NY at Binghamton.

Andy RobertsonResearch Scientist, Predictability, Downscaling, IRIAfter graduating from the University of Leeds, U.K., with a B.Sc. in mathematics and geography, Robertson received an M.Sc. from Imperial College, London in atmospheric physics and dynamics, and a Ph.D. in atmospheric dynamics from the University of Reading in 1984. His research interests include regional climate variability, predictability and change, probabilistic daily rainfall modeling, predict-ability of weather-within-climate, climate downscaling methodologies, and tailor-ing of climate information for use in conjunction with sectoral models for climate risk management. Robertson currently leads the downscaling division within IRI’s Climate Program, and is the climate nodal person for IRI’s Asia-Pacific regional program. His work is focused on bringing climate information into regional projects that seek to demonstrate the value of “climate risk management,” through targeted research, tool development, and training/outreach.

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Michelle StantonPhD Student in Spatio-temporal Epidemiology, Lancaster University School of Health and MedicineMichelle Stanton is a PhD student within the School of Health and Medicine at Lancaster University. Her research interests are spatio-temporal statistical models and their applications in tropical disease epidemiology. In particular, Michelle is involved in building a predictive model for meningitis incidence in sub-Saharan Africa using climate and environmental information. Michelle obtained her Bach-elors of Mathematical Sciences from Bath University, UK in 2005, and her Masters in Medical Statistics from Lancaster University in 2007. She is an alumnus of the Sum-mer Institute 2008.

Madeleine ThomsonSenior Research Scientist, Climate Information for Public Health, IRIMadeleine Thomson is a Senior Research Scientist at the International Research Institute for Climate and Society where she chairs the Africa Regional Programme, directs Impacts Research and supports the IRI-PAHO-WHO collaborating centre ac-tivities. She trained originally as a field entomologist and has spent much of her ca-reer engaged in operational research in support of large-scale health interventions, mostly in Africa. Her research focuses on the development of new tools for improv-ing climate sensitive health interventions. This work has expanded into air-borne infections and she is currently developing a substantive programme for meningitis environmental risk assessment in anticipation of the new conjugate A vaccine. In recent years she has become increasingly interested in improving institutional and human capacity for incorporating climate information into health planning. To help achieve the latter she is working to create a ‘health and climate’ disciplinary interface.

Sylwia TrzaskaAssociate Research Scientist, Climate Variability, Atlantic, IRISylwia has been with the IRI since 2002. Her research interests include climate vari-ability in the tropical Atlantic on the regional scale including Southern America and Africa with special focus on tropical areas, including the Nordeste, Sahel and South-ern Africa. She is also interested in observed, reanalyzed and model data analysis on seasonal to decadal time-scales model sensitivity studies to boundary condition modifications, as well as decadal modifications of the major teleconnections in the tropical Atlantic region. She received her doctoral degree from Université de Bourgogne.

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Support Staff

Ann BinderManager, Staff and Operations, IRI Ann Binder prepares budgets and sub-contracts in support of IRI and its projects. She assembles and consolidates all income streams and affiliated program budgets into a coherent single financial plan to serve the IRI, it’s funding agencies, and collaborative business resources. She coordinates hu-man resources for the IRI and assembles information, documents, and hiring plans in coordination with appropriate divisions of Lamont-Doherty Earth Observatory and Columbia. She also works with governmental organizations that facilitate visitor and post-doctoral programs.

Michael DervinSystem Analyst, Systems Administration, IRIMichael has been working at the IRI for about 2 years. He has been a member of the Computing Support team at the IRI and he is responsible for many of the computer operational services at the IRI. He also provides guidance for data storage systems and software tools.

Francesco FiondellaCommunications Officer, Office of the Director-General, IRIBefore coming to the IRI, Francesco worked as an editor in the Wall Street Journal’s news graphics department and moonlighted as a science/health reporter for the paper as well. He has also freelanced for a variety of publica-tions, including Discover, The Scientist and Reuters Health. Francesco earned his undergraduate degree in environmental science at Brown University, and his master’s degrees in earth and environmental science and in journalism from Columbia. Francesco promotes the IRI’s innovative work primarily by writing features for the Institute’s home page and engaging with journalists, partner organizations and members of the general public. He designs and edits institutional reports, presentations, and flyers. He also maintains the Institute’s media page and news-related email list.

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Rise Fullon Project Coordinator, IRI

Rise is responsible for analyzing and organizing current and pending proj-ect/activities data to maintain some of IRI’s knowledge databases. She inter-acts with staff for contributions and content development for IRI’s internal newsletter as well as various internal and external project reporting require-ments.

Althea MurilloAdministrative Assistant, IRI

Thea has been with the IRI since July 2007. She provides daily administrative support for the IRI staff. This work includes events coordination, arranging travel accommodations, and the handling of various projects. Her degree is in early childhood education.

Barbara PlatzerAfrica Regional Program Coordinator, IRI

Born in Nairobi, a UN kid, Barbara has a long-standing interest in Africa. Prior to joining the IRI, she served as Assistant Director for the Risk Analysis Group of the Columbia Business School and has been working at Colum-bia University since 2004. She holds a Masters of International Affairs from the University of Chicago and a Bachelor of Arts in International Relations from Brown University. Barbara serves as coordinator of the Africa Regional Program at the IRI, contributing to the operational and strategic objectives of the Program, its Committee members and more broadly the institute. Barbara serves as a point of contact for Africa regional activities within the IRI, to Earth Institute and Columbia University officials, as well as to external partners.

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Jason RodriguezProduction Aide, Communications/Graphic Design, IRI

Jason Rodriguez is a graphic designer specializing in web layout design, xht-ml, css, and traditional print design. His past experience includes his work as a Production Assistant for JTP Creative in NYC organizing photo shoots and creating casting websites. He also was owner director of Residue Gallery, a contemporary arts space in Jersey City, NJ. Jason earned his BA in Computer Arts and Design from Oneonta University (SUNY). In the role of Production Aide, Jason is responsible for assisting communications officer, Francesco Fiondella, with layout, design, and production on a variety of print and web features promoting the IRI’s innovative work.

Jeffery TurmelleSenior System Analyst/Network ProgrammerSystems Administration, IRIJeffrey Turmelle received his B.S. degree in Computer Science from the University of Lowell, MA in 1987 and a Masters of Technology Management from Columbia University in 2007. Jeffrey worked in graphics research for the University of Lowell’s Graphics Research Laboratory before getting involved in Image Processing at a small startup: Paragon Imaging. He then became involved in large-scale development working on medical applications for Sony Electronics. In 1996 he joined Lamont-Doherty Earth Observatory to become the Data Reduction Manager on the R/V Maurice Ewing (Columbia University’s Research Vessel). Since 2001, Jeffrey has been a member of the Computing Support team at the IRI and is responsible for many of the com-puter services at the IRI, including email, directory services and web services.

Cathy VaughanProject Coordinator, IRICathy Vaughan is a project coordinator at the IRI. She holds master’s degrees in International Relations (Yale 2007) and Climate and Society (Columbia 2008). Cathy has worked for organizations including the Global Roundtable on Climate Change, the Mission of Dominica to the United Nations, and the Austin Chronicle; from 2003 until 2005, Cathy served with the US Peace Corps in Zambia. She is the author of Climate Change: A Reference Hand-book, published earlier this year.

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Sandy VitelliAdministrative Assistant, Administrative Support, IRI

Sandy provides day-to-day administrative support for the organization. She handles special projects with staff and visitors, organizing professional con-ferences and meetings. She coordinates events, arranges travel accommoda-tions, and manages reimbursements related to expenses and the dissemina-tion of reports. She also ensures overall effectiveness and efficiency, while interacting with diversified groups within and outside the IRI.

Scott WoodClimate and Society Graduate Student, Columbia University

Scott is a full-time graduate student and has worked at the IRI since Fall 2009 as part of a work-study program through Columbia University’s M.A. program in Climate and Society. His work with the IRI includes contributions to the development of the CIPHA Network and the 2010 Summer Institute. Prior to his graduate studies and IRI affiliation, Scott worked at New England Research Institutes as a Clinical Data Manager and spent time volunteering on environmental and public health projects in Urubamba, Peru with Nexos Voluntarios. He earned his B.A. in Applied Psychology from Bryant University.

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Appendix 2: Sponsors of the Participants


Agencia Estatal de Meteorología, AEMET (translated from Spanish as the State Meteorological Agency) is the Spain Meteorological Service, affiliated to the Ministry of Environment, Rural and Marine Resources. AEMET aims to develop, implement and deliver meteorological services, and to support other public or private initiatives related to the safety of people and goods and to the sustainable development of the Spanish society.

» Adapted from: http://www.aemet.es/es/portada

The Center for Disease Control and Prevention (CDC) is the US premier health promotion, prevention, and preparedness agency and a global leader in public health. CDC′s Mission is to collaborate to create the expertise, information, and tools that people and communities need to protect their health – through health promotion, prevention of disease, injury and disability, and preparedness for new health threats. CDC works with states and other partners to provide a system of health surveillance

to monitor and prevent disease outbreaks (including bioterrorism), implement disease prevention strategies, and maintain national health statistics. CDC also guards against international disease transmission, with personnel stationed in more than 25 foreign countries.

» Adapted from: http://www.cdc.gov/

The Deutsche Gesellschaft für Technische Zusammenarbeit (GTZ) is a federally owned organization. GTZ works worldwide in the field of international cooperation for sustainable development. GTZ′s mandate is to support the German Government in achieving its development objectives. The organization provides viable, forward-looking solutions for political, economic, ecological and social development in a

globalised world. Sometimes working under difficult conditions, GTZ promotes complex reforms and change processes. Its corporate objective is to improve people′s lives on a sustainable basis.

» Adapted from: http://www.gtz.de/en/

Since 2004, Google.org uses Google’s strengths in information and technology to build products and advocate for policies that address global challenges. Google.org is an integral part of Google Inc., and works closely with a broad range of “Googlers” on projects that make the most of Google’s strengths in technology and information; examples of this approach include Flu Trends, RechargeIT, Clean Energy 2030, and PowerMeter.

» Adapted from: http://www.google.org/

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The University Corporation for Atmospheric Research (UCAR) promotes partner-ship in a collaborative community dedicated to understanding the atmosphere—the air around us—and the interconnected processes that make up the Earth system, from the ocean floor to the Sun’s core.

» Adapted from: http://www.ucar.edu/

The United States Agency for International Development (USAID) is an indepen-dent federal government agency that receives overall foreign policy guidance from the Secretary of State. USAID’s work supports long-term and equitable economic growth and advances U.S. foreign policy objectives by supporting: economic growth, agricul-ture and trade; global health; and, democracy, conflict prevention and humanitarian assistance. USAID provides assistance in five regions of the world: Sub-Saharan Africa; Asia; Latin America and the Caribbean, Europe and Eurasia; and The Middle East.

» Adapted from: http://www.usaid.gov/

The National Institute of Malaria Research (NIMR) was established in 1977 as ‘Malaria Research Centre’, which was renamed as ‘National Institute of Malaria Research’ in November 2005. NIMR is one of the institutes of the Indian Council of Medical Research (an autonomous body under Department of Health Research, Ministry of Health & Family Welfare, Govt. of India). The primary task of the Institute is to find short term as well as long term solutions to the problems of malaria through basic, applied and operational field research. The Institute also plays a key role in manpower resource development through trainings/workshops and transfer of technology.

» Adapted from: http://www.mrcindia.org/

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Appendix 3: Course Flyer


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26



Appendix 4: Application FormApplication Form: May 17 – May 28, 2010

General Information

Family Name: First Name:

Institution/Organization:

Occupation:

Nationality:

Date of Birth (mm/dd/yyyy): Sex:

Address for correspondence:

City:

Country: Postal Code:

Telephone: Fax:

Mobile: Email:

Application for two-week training course: May 17 – May 28, 2010

I would like to participate at the two-week training course.

I will have funding resources to cover the cost of attendance* plus air travel: ___Yes ___No If yes, please provide details on funding resources:

On behalf of my institution, I commit to partner in the development of similar trainings in my home-country: ___Yes ___No I am willing to facilitate future trainings on Climate Information for Public Health using my experi-ence of the Summer Institute: ___Yes ___No

My institution will provide me with a dataset** that I will use during the practical sessions of the Summer Institute: ___Yes ___No If yes, please provide details on this dataset:

*A limited amount of scholarships are available for applicants**This dataset is to be used only by the participant and only for the purpose and duration of the training.

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Profile of the applicant

Language skills

Mother tongue(s):English proficiency: Speaking:

Reading:Writing:

BasicBasicBasic

GoodGoodGood

Very goodVery goodVery good

Computer skills

Knowledge of: Excel®: Basic Good Very good

SAS®: Basic Good Very good

Stata®: Basic Good Very good

SPSS®: Basic Good Very good

R®: Basic Good Very good

MathLab®: Basic Good Very good

Other (Specify): Basic Good Very good

Prior knowledge on health and climate

Do you have a degree in health? Yes No

If yes, specify:

If no, detail your experience in public health:

Do you have a degree in climate/meteorological science? Yes No

If yes, specify:

If no, detail your experience in climate/meteorological science?

In addition to this application form, please provide the following documents:

1. Short Curriculum Vitae (CV) of maximum 2 pages, including a recent photo. See template attached.

2. Brief statement on how this course will benefit you, your organization and the broader community (300 words maximum)

3. Support letter from your institution acknowledging its commitment to partner in the de-velopment of similar trainings in your country

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Appendix 5: Application Report

» Application submissions online at: http://iri.columbia.edu/education/summerinstitute10

If you have difficulties submitting the application online, please contact:Gilma MantillaInternational Research Institute for Climate and Society Address: The Earth Institute, Columbia University, Lamont Campus, 61 Route 9W, Monell Building, Palisades, NY 10964-8000, USA Tel.: +1 845 680 4485 ; Fax: + 1 845 680 4864 ; Email: [email protected]

Signature: Date:


2010 Summer Institute on Climate Information for Public Health

Applicants Report by Scott Wood

The International Research Institute for Climate and Society received 134 applications for this year’s 2010 Climate Information for Public Health Action Summer Institute. Applicants spanned the globe, with the continent of Africa leading in number of application submissions. By region*, the applicant pool broke down as follows:

• Africa: 78 Applicants (58%)

• Asia: 24 Applicants (18%)

• Europe: 13 Applicants (10%)

• North America: 11 Applicants (8%)

• Latin American and Caribbean: 7 Applicants (5%)

• Southwest Pacific: 1 Applicant (1%)

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*See Appendix A for more in-depth regional analyses

Applicants indicated a variety of means by which they became interested in the Summer Institute. A near-tie existed between those learning about the Summer Institute via Internet (33%) and IRI Communication (32%) (IRI Communication includes the CIPHA Newsletter and IRI-generated emails). Of those indicating the Internet as their source of promotion, almost half (48%) reported the IRI’s website as their specific point of learning about the Summer Institute. Roughly a quarter of those indicating the Internet pointed to Eastchance.com as their means of learning about it. Only 9% of such (Internet) applicants learned of the Summer Institute via a social networking website such as Facebook.com or Twitter.com. 28% of applicants heard about the Summer Institute from friends or colleagues. One applicant even went on to specify “A colleague at work, who attended the training in 2008, sent me the flier. I wrote a joint paper on malaria with him. The paper was largely informed by his training in your institute.”

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Applicant Occupations

Within the applicant pool, the majority of applicants reported holding positions of program management or direc-torship (19%). Also well represented amongst applicants were members of academia, including graduate-level students (17%) and professors of varying experience (14%). Researchers and scientists followed (13%), along with project officers (12%) and meteorologists (7%). Other professions were also represented (see below table for details).

Position Title Number of Applicants

Program Manager/Director/ Officer/Leader 22

Student/Resident 20

Teacher/Professor/Lecturer 16

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Researcher/Scientist 15

Project Officer/Coordinator/Manager 14

Meteorologist 8

Program Advisor/Assistant 6

Information/Data Management/GIS Professional 3

Consultant 2

Lawyer 1

Other 8

Applicant Funding Capacity

In response to the question “Will you have funding resources to cover the cost of attendance plus air travel?”, 13% of applicants indicated an ability to acquire such funding, while the majority (83%) reported a lack of complete funding.

Of those indicating funding ability, various sources of funding were provided (see below). Of those indicating a lack of full funding, some applicants reported having partial funding available and many indicated plans to seek out and apply for such funding.

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ApplicantFundingSources:

• Addis Ababa University

• CDC, Ethiopia

• Ethiopian Public Health Association

• FELTP program and the Ethiopian Public Health Association

• German Technical Cooperation (GTZ) in Tunisia

• Kenya Field Epidemiology and Laboratory Training Program

• Nigerian Meteorological Agency

• NOAA’s West Coast Center for Oceans and Human Health

• Self funding

• World Health Organization, Ethiopia Country Office

• AEMET

Applicants’Commitment

Applicants overwhelmingly agreed to pass along to others the knowledge gained from the Summer Institute. When asked if willing to facilitate future trainings on Climate Information for Public Health using their experience from the Summer Institute, virtually all (98%) of applicants responded “Yes”. When asked if willing to commit to partner in the development of similar trainings in their home country on behalf of their institution, 94% agreed to do so.

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Data

Most applicants (60%) indicated an ability to bring relevant datasets, provided by their relative institutions, to the Summer Institute for use during practical sessions. Many such applicants indicated having access to a range of data, including data on disease, climate, ecology, water, agriculture, population, and other social datasets. Of data on disease, numerous disease-types were indicated including:

• Acute Respiratory Infections

• Cholera

• Dengue Fever

• Diarrheal Diseases

• Giardia

• Malaria

• Measles

• Meningitis

• Nodding Disease

• Typhoid Fever

• West Nile Virus

Climate data included such variables as temperature, precipitation, and humidity. A full breakdown of the data available to those applicants indicating an ability to provide such datasets is provided below.

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English Language

Applicants exhibited a high level of English language skills. Most applicants indicated “Very Good” skills for level of English Speaking (63%), Reading (86%), and Writing (77%).

Computer Skills

Applicants displayed a large array of computer skills, with most (90%) indicating either “Good” or “Very Good” level of skill with Microsoft Excel. Skill varied considerably across different statistical packages, with SPSS being the most familiar such software among applicants. Numerous other computer skills were indicated (see below) beyond the selection criteria of the application.

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Skill Level Excel SAS Stata SPSS R Epi-Info Matlab

None 0% 61% 65% 25% 75% 52% 76%

Basic 10% 24% 20% 31% 18% 21% 10%

Good 32% 10% 10% 28% 4% 19% 7%

Very Good 58% 5% 4% 17% 3% 7% 6%

OtherComputerSkills:

AMOSArcGISArcInfoArcViewAtlas tiC++CLICOMCPTCropwat

Epi MapEpidataErdasEviewsFortranGPSGrAdsGraph Pad PrismIDI

IdrisiIlwisImagineINSTATLeapMapInfoMathCadMind ManagerMiniTab

MS OfficeNvivoPhotoshopStatisticaStatwiew 512+SurfurSystatVISI

Education

Applicants were of diverse educational background, with 45% holding a degree in a health-related discipline and 28% indicating a degree in Climate.

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Appendix A: Regions

Africa

Representing Africa were 78 applicants from 15 countries. The greatest number of applicants came from Ethiopia (29), Nigeria (16), Kenya (7), and Madagascar (6). Program management (16), project officers (11), and professors (9) were the most represented professions from Africa. Applicant referees included university department heads, organization directors, and others.

AfricanCountries

Countries Represented Number of Applicants

Ethiopia 29

Nigeria 16

Kenya 7

Madagascar 6

Egypt 3

Ghana 3

Uganda 3

Tanzania 2

Tunisia 2

Zimbabwe 2

Burkina Faso 1

Cameroon 1

Congo (Kinshasa) 1

Niger 1

Senegal 1

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ApplicantProfessions(Africa)

Titles Number of Applicants

Program Manager/Director/Of-ficer/Leader 16



Meteorologist 8

Student/Resident 7

Program Advisor/Assistant 6

Information/Data Management; GIS Prof. 5

Other (Dentist, Environmental-ist, Volunteer) 3


Lawyer 1

ApplicantReferees(Africa)

Last Name First Name Organization Title Number of Referrals

Mitike Getenet Addis Ababa University Head, School of Public Health

7

Phillippe Velo Chargee de la Sante Publique Conseiller Affaires Etrangeres

4

Mihretie Abere Anti-Malaria Association Director of AMA/Secretary of Cli-mate and Health Working Group

3

Adesina F.A. Obafemi Awolowo University Dean 2

38



Haile Tesfaye Ethiopian Meteorological Soci-ety

Manager of EMIB-AMA

2

Nafo-Traore Fatoumata World Health Organization - Ethiopia

WHO Representa-tive

2

Omolo Jared Ministry of Public Health and Sanitation

Program Coor-dinator, Field Epidemiology and Laboratory Training Program

2

Shanko Dula National Meteorological Agency of Ethiopia

A/D/Director Gen-eral

2

Abass Hassan Wajir District Hospital Nursing Officer in Charge

1

Adeiga Dr. Nigerian Institute of Medical Research

Deputy Director, Research

1

Ademola Olayioye Unique Environ Concept Limited 1

Akinyeye P.S. Center for Disaster Risk Manage-ment and Development Studies; Federal University of Technology

Director DRM & DS 1

Akol Dr. A Makerere University Head, Department of Zoology

1

Awoyinka Isa The European Union Mission in Nigeria

Project Officer 1

Babu Amare National Meteorological Agency of Ethiopia

Head of Meteoro-logical Analysis and Forecast Depart-ment

1

Boakye Daniel University of Ghana Head, Parasitology Department

1

Dar Bahir Jerusalem children and commu-nity Development Organiztion

1

Desalagn Firew

Ato Tena Kebena Ginfile Cleaned Association

Vice President/Pro-gram Manager

1

39



Edom Egbala Government of Cross River State, Ministry of Agriculture & Natural Resources

Assistant Director of Administration

1

Farag Mohamed Mansoura University Professor and Chariman

1

Garane Ali Jacques Civile et de la Meteorologie Meteorology Office Director

1

Gissila Tesfaye National Meteorology Agency of Ethiopia

Head, Develop-ment Meteorology Department

1

Haile Mariam Damen Addis Ababa University Professor/Associ-ate Dean, College of Health Sciences

1

Ibraheem R.O. National Planning Commission Assistant Director 1

Ikamari Lawrence University of Nairobi Centre for HIV Prevention and Research

1

Issa Ahmed Mo-hamed

Somali Regional State Health Bureau

Head of SRS Health Bureau

1

Jima Daddi Ethiopian Health and Nutrition Research Institute

Deputy Director General

1

Kayode Akamo

Lateef Global Network for Environment and Economic Development Research

Chairman, Board of Governing Council

1

Kiluva Steven Ministry of Public Health and Sanitation

1

Kiriba Deodatus Environmental Watch Associa-tion of Tanzanie

EWAT Chairperson 1

Kongoti James Ministry of Environment & Min-eral Resources

1

Kura Bukar Bana Kanuri Development Association President 1

Lo Gueye Maimouna Ministere de L’Agriculture Le Directeur 1

40



Louzir Mohamed Hechmi

Institut Pasteur de Tunis Le Directeur Gen-eral

1

Louzir Mohamed Hechmi

Institut Pasteur de Tunis Le Directeur Gen-eral

1

Mafuta Clever Southern African Research and Documentation Centre

Director SARDC IMERCSA

1

Malamba Samuel Centers for Disease Control and Prevention, Uganda Virus Research Institute

Chief, Informatics Branch

1

Mohamed Salat Wajir District Hospital Medical Superin-tended

1

N-A Dodoo Francis University of Ghana Professor/Director, Regional Institute for Population Studies

1

Nimusiima Alex Makerere University Ag. Coordinator, Geography De-partment

1

Odaibo A.B. University of Ibadan Professor/Head of Department of Zoology

1

Onokala P.C. University of Nigeria Dean 1

Ravaoalima-lala

Vololomboah-angy

Institut Pasteur de Madagascar Director 1

Reithinger Richard President’s Malaria Initiative, USAID/Ethiopia

Team Leader/Ma-laria Advisor

1

Segor F.K. MOI University Head, Chemistry & Biochemistry

1

Taiwo V.O. University of Ibadan Dean, Veterinary Medicine

1

Usmael Abdurahman Harari People National Regional State Health Bureau

Head, Health Bureau

1

Wasike Paul International Rescue Committee Nutrition Pro-gramme Manager

1

41



Zakariyya M. A.G. Bayero University, Kano Faculty of Medi-cine

1

Zhakata Washington Climate Change Office Coordinator

1

Asia

Representing Asia were 23 applicants from 12 countries. The greatest number of applicants came from India (6), Pakistan (4), Bangladesh (3), and Thailand (2). Program management (5) and professors (4) were the most represented professions. Applicant referees included organization presidents, members of parliament, and others.

AsianCountries


India 6

Pakistan 4

Bangladesh 3

Thailand 2

Armenia 1

Azerbaijan 1

China 1

Jordan 1

Lebanon 1

Mongolia 1

Nepal 1

Philippines 1

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ApplicantProfessions(Asia)


Program Manager/Director/Officer/Leader 5


Student/Resident 3

Other (Health Policy Expert, NGO Professional, Banking) 3



ApplicantReferees(Asia)


Aziz Sijal Women Empowerment Literacy and Development Organization

Executive Director 2

Akhtar Javed Just Peace International Chief Executive 1

Arun Malik World Health Organization, Thailand

Technical Officer 1

Babloyan Ara National Assembly of the Repub-lic of Armenia, Standing Com-mittee on Health Care, Maternity and Childhood

Member of the Parlia-men, Chairman of the Standing Committee on Health Issues of the National Assem-bly of RA

1

Dhiman R C National Institute of Malaria Research

Director-in-Charge 1

Dhiman R C National Institute of Malaria Research

Director-in-Charge 1

43



Islam Monsurul Government of the People’s Republic of Bangladesh, Upazila Health and Family Planning

Office of the Upazila Health and Family Planning Officer

1

Reddy Srinath Public Health Foundation of India

President 1

Rinchin Mijiddori Mongolian University of Science and Technology

Executive Director, Center for Ecology & Sustainable Develop-ment

1

Singh V K International Institute of Health Management Research

Director 1

Su Changhe Shanghai International Studies University

Professor/Dean, School of Interna-tional and Diplomatic Affairs

1

Zeitoun Abbas Baran Renewable Energy Com-pany

General Manager 1

- - Institute of Marine Sciences and Fisheries

Director 1

Europe

Representing Europe were 13 applicants from 12 countries. The greatest number of applicants came from Sweden (2) and the United Kingdom (2). Students (6) and Researchers/Scientists (4) were the most represented professions. Applicant referees included professors and organization directors.

EuropeanCountries


Sweden 2

United Kingdom 2

Albania 1

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Belgium 1

Bulgaria 1

Germany 1

Portugal 1

Romania 1

Russia 1

Serbia 1

Switzerland 1

Ukraine 1

ApplicantProfessions(Europe)


Student/Resident 6




Other (Social Worker) 1

ApplicantReferees(Europe)


45



Henry Sabine University of Louvain - Namur Professor, Department of Geography

1

Petrova Stefka Ministry of Health, National Cen-ter of Public Health Education

Director 1

Ganaba Rasmane Groupe de Recherche, d’Expertise et de Formation en Sante pour le Developpement

Executive Director 1

Burgess Jacquie University of East Anglia Professor, School of En-vironmental Sciences

1

North America

Representing North America were 11 applicants - 9 from the United States and 2 from Canada. Researchers/Scientists (5) and students (2) were the most represented professions. Applicant referees included organization directors, university department directors, and others.

N.AmericanCountries


United States 9

Canada 2

ApplicantProfessions(N.America)



46



Student/Resident 2



Other (Architect) 1

Consultant 1

ApplicantReferees(N.America)


Dowlatabadi Hadi Institute for Resources, Environ-ment and Sustainability

Canada Research Chair & Professor

1

Liu Fan Chinese Center for Disease Con-trol and Prevention

Department Direc-tor, Institute for Environmental Health and Related Product Safety

1

Ngoc Khanh Hoang Hue Forest Protection Director 1

Stein John NOAA, National Marine Fisheries Service, Northwest Fisheries Sci-ence Center, West Coast Center for Oceans and Human Health

Deputy Science and Research Director

1

Zurayk Rami American University of Beirut Associate Dean, Ag-ricultural and Food Sciences

1

47



Latin America & Caribbean (LAC)

Representing Latin America and the Caribbean were 7 applicants - one each from 7 different countries. Students (2) were the most represented profession. Applicant referees included university department directors, organization founders, and others.

LACCountries


Bolivia 1

Brazil 1

Ecuador 1

El Salvador 1

Jamaica 1

Mexico 1

Peru 1

ApplicantProfessions(LAC)


Student/Resident 2


Consultant 1


ApplicantReferees(LAC)

48




Azoh Barry Jose Investigacion & Accion Founder/Coordina-tor

1

Hilgert Nancy Universidad Espiritu Santo Director, School of Environmental Sci-ences

1

Luiz Ramos Barbosa

Wagner Universidade Federal do Para Nucleo de Meio Ambiente

Director Adjunto 1

Rodriguez Rojas

Roberto Comision Centroamericana de Ambiente y Desarrollo

Coordinador 1

Villanueva Jaime Ministerio de Planificacion del Desarrollo, Viceministerio de Planificacion Territorial y Ambi-ental

1

49



South Pacific

Representing Oceania was 1 applicant, a lecturer from the Solomon Islands. The applicant was referred by the head of the School of Finance and Administration from Solomon Islands College of Higher Education.

OceaniaCountries


Solomon Islands 1

ApplicantProfessions(Oceania)



ApplicantReferees(Oceania)


Matapaza William Solomon Islands College of Higher Education

Head of School of Finance and Admin-istration

1

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Appendix 6: Panel Discussion Invitation

Appendix 6: Panel Discussion InvitationColumbia University’s Mailman School of Public Health, International Research Institute for Climate & Society (IRI) and Center for International Earth Science Information Network (CIESIN) are pleased to invite you to a panel discussion:

Creating a “Climate Smart” Global Health Community: How do we communicate? Who do we train?

Wednesday, May 19, 2010 Hess Commons, Allan Rosenfield Building

4:00-7:30pm (including reception)

Increasing the health community’s capacity to understand, use, and demand the appropriate climate information is of primary importance to efforts to diminish the health impacts of climate change and climate variability.

However, good information is not enough. The health community must also be able to distinguish between differ-ent kinds of data to determine what is relevant, at what time scale, to their population.

To fill the current gaps, we must develop research and professional training in the use of climate information for public health decision-making that can be launched in centers of learning throughout the globe. Here, an expert panel discusses the opportunities and challenges we face in the creation of a “Climate Smart” health community.

Opening remarks: Linda Fried, Mailman School of Public Health

Facilitator: Madeleine Thomson, IRI

Panelists:

Wayne Elliott, Met Office UK

Richard Luce, CDC, Ethiopia, Field Epidemiology Training Programs Resident Advisor

Patrick Kinney, Columbia Climate and Health Program, Mailman School of Public Health

This event is integrated to the Summer Institute 2010 course on Climate Information for Public Health, which offers public health decision makers and their partners the opportunity to learn practical methods for integrating

climate knowledge and information into decision-making processes.

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Appendix 7: Daily Quiz Questions and Answers by Module


Module I: Basic Concepts in Public Health and Climate (Days 1, 2)

Day 2: Tuesday, May 18, 2010Questions related to the talks given on Monday May 17. Introduction to the Summer Institute 2010 and to the CIPHAN network, by Madeleine Thomson, IRI

Who can be a member of the CIPHAN network? Any alumni from CIPH courses, any member of a Climate and Health Working Group, and any professional involved in climate and health research, field work, education or training can be part of the CIPHAN network, upon approval of the application

How do the CIPH alumni stay in touch? Through participating to writing, translating and circulating the CIPHA newsletter; through the implementation of CIPH trainings involving their fellow trainees; and through using and populating the CIPHAN Web-page.

Climate Risk Management and Development, by Walter E. Baethgen, IRI

Describe two key lessons learned in the history of the IRI and link them to your own institution’s activities (in other words, are they relevant for your work?)

Examples:

• In order to have societal impact research must be demand-driven and problem-focused.

• Work must engage stakeholders from the very beginning (to ensure relevance, uptake, ownership, continuity, etc)

• The main niche for the IRI is in scientific research, but must ensure that some of that research is oriented to “translating” climate information and products into information and products tat are relevant for the different sectors (health, water, agro)

• The most successful work is achieved when we use existing “chains of information” (if chains are not present we need to help to develop and strengthen them)

• Using climate information and products in the different sectors, needs that sectorial experts have a minimum understanding of climate. It also needs researchers working in the interface of climate and sectors.

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What is wrong with the following statements?

(a) “The next season will be dry and therefore we do not expect major outbreaks of infectious diseases”, (b) “Based on the best available climate models, precipitation in my country in the year 2080 will be 25% higher than in the present”.

Key issues are missing in both statements. In (a) they need to add “probabilities”. In (b) they need to add “uncer-tainty”

Climate, Vulnerability, and Health: International and National Perspectives, by Ulisses Confalonieri, Oswaldo Cruz Foundation

Which of the following elements may influence the way climate impacts public health?

a. Environmental conditions

b. Social conditions

c. Collapse of the public health system

d. Change in health policy

e. All of the above

f. Only a and b

Answers: e)

Define the following terms:

Adaptation to climate change - The “adjustment in natural or human systems in response to actual or expected climatic stimuli or their effects, which moderates harm or exploits beneficial opportunities” (IPCC, 2007).

Mitigation to climate change - Measures implemented to decrease the intensity of radiative forcing in order to reduce climate change (e.g.: reducing the sources or sinks of greenhouse gases).

Climate Risk Management in Health, by Madeleine Thomson, IRI

What is climate risk management?

Climate Risk Management is a term referring to how do you approach a climate-sensitive decision, making it increasingly seen as the way of dealing with climate variability on the one hand, and climate change on the other.

How might a climate change health agenda detract from a pro-poor global health agenda?

By focusing attention on longer-term challenges while ignoring immediate problems.

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How does climate change differ from climate variability?

Focus is on long-term trends rather than near term variability.

What is the decision-time frame for national malaria control planners?

Mostly one year – Maximum four.

Overview of the Data Library, by Michael Bell, IRI

Name two image file formats in which maps or graphs can be downloaded from the IRI Data Library.

A correct answer would include two of the following: Gif, jpeg, PostScript, PDF, PNG

Name one difference between the appearance or structure of a gridded data set compared to a station data set in the Data Library.

Station data sets will include a map of station locations, a grid will index the stations using an identifier, and any station latitude/longitude information will appear as dependent variables. In gridded data sets, there is no station map and latitude and longitude are typically grids, or independent variables.

Understanding Data and Data Quality Control, by John del Corral, IRI

What are the 2 independent variables needed to correlate Health data with climate data?

Time and location

What is the difference between a collection of numbers and data?

A collection of numbers can be interpreted or mis-interpreted in many ways. Data should be ordered, consistent, and described in such a way as to be interpreted in only one way(the way that the data provider intended).

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Day 3: Wednesday, May 19, 2010Questions related to the talks given on Tuesday May 18

Introduction to Climate and Climate Information, by Sylwia Trzaska, IRI

What is ENSO and how can you explain its worldwide impacts?

ENSO (El Nino-Southern Oscillation) is a mode of interannual variability in climate. It manifests itself in Sea Surface Temperature anomalies in equatorial Pacific and alteration of the mean atmospheric general circulation structures, mostly the Walker (zonal) cell. During the El Nino phase waters are warmer than usual in the eastern equatorial Pacific and the Walker cell reduced with weaker trade winds over eastern equatorial Pacific and weaker subsidence, leading eventually to rainfall in the usually dry areas centered on the coast of Peru. In western Pacific the usually abundant precipitations are reduced. The situation is reversed in the La Nina phase with colder waters, enhanced trade wind and subsidence and expanded dry areas in the East and enhanced precipitation in the West. Because atmospheric (and oceanic) circulations are organized in well-defined patterns due to differences in Energy the surface receives, availability of moisture and land-ocean thermal gradients, any perturbation in one of the organized cells affects other cells. Therefore changes in the large-scale circulation patterns over the Pacific affect atmospheric circulations elsewhere which in turn affects temperature, moisture advection and conditions favorable for rainfall in some areas. For more info on ENSO check IRI’s ENSO Web at: http://portal.iri.columbia.edu/portal/server.pt?open=512&objID=491&PageID=0&cached=true&mode=2&userID=3794

What is the difference between climate data and climate information? Cite 3 most common procedures to extract climate information.

Climate data is a collection of numbers relative to climate variables recorded in a given location over a given period of time. Climate information is extracted from those data with a given goal in mind – it can be a climatology, departures from a given value/threshold, correlation between health variable and climate variable etc. Most common procedures include time and space averages, anomalies from the mean or another threshold, differences in means between locations, estimations of amplitude of variations (such as standard deviations), frequency related measures (pdf etc).

Core Concepts in Public Health and Epidemiology, by Judy Omumbo, IRI

True or false:

• The malaria parasite ratio is a commonly used measure of the risk of malaria in a defined population.

• Climate sensitive diseases co-vary in the same time and space scales as climate.

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• ENSO is a feature of climate variability that may affect climate sensitive diseases in the same time scale.

Answer: False, True, True

Public Health Surveillance and Opportunities to use Climate Information, by Richard Luce, CDC

Among the common uses and applications public health surveillance are:

a. Detecting changes in infectious agent

b. Evaluating prevention and control measures

c. Monitoring long-term trends

d. Planning future resource needs for prevention

e. All of the above

Answer: e)

Routine analysis of surveillance data would likely include which of the following (Circle all that apply):

a. The number of cases of a disease reported this week and during the previous 5 weeks.

b. The number of cases of a disease reported this week and the number reported during the comparable week from each of the previous 5 years.

c. Person-time incidence rates among reported cases.

d. The number of cases by age and sex.

e. The number of cases by district.

Answer: a) b) d) e)

Summarizing Climate and Health Data Using Descriptive Statistics and Map Tools, by Michael Bell, IRI

Of the following choices, what does an “M” in the Data Library Expert Mode grid-matching notation tell you?

a. That two variables match along a grid

b. That two variables do not match along a grid

c. That two variables are offset along a grid

d. That you have multiplied two variables together

Answer: a)

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Name some types of statistics that would be useful for describing the distribution of a variable.

Mean, median, range, standard deviation, root mean square anomaly -- others

Module II: Sources and Tools for Analyzing Climate and Public Health Data (Days 3, 4, 5)

Day 4: Thursday, May 20, 2010Questions related to the talks given on Wednesday May 19

Climate and Vector-Borne Diseases Dynamics, by Madeleine Thomson, IRI

a. Ambient temperature affects

b. Parasite development rates in vectors

c. Parasite development rates in humans

Answer: a)

Malaria Vector Distribution and Rainfall, by Judy Omumbo, IRI

How would you describe mean rainfall across Africa?

It varies over space and in time. Some areas have more rainfall on average and others are always drier on average, i.e. trainee should be able to point to variability in average conditions over space and variations in time (seasonality) within those average conditions.

What do you notice about the distribution of different species?

Their distribution varies in space.

How would you describe the relationship between annual precipitation and vector distribution by species?

An. gambiae prefers wetter habitats, An. arabiensis is distributed in arid areas.

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What did you notice about the habitat preference of An. melas and An. merus?

An. merus and An. melas are limited to coastlines of West and East Africa respectively.

How would this information help you to select an anti-malaria intervention?

Vector control program in arid areas can use climate information to time interventions to coincide with the seasons of maximum vector abundance. Resting preferences of the vectors (inside vs. outside) are also important considerations.

How frequently should measurements of disease be taken?

In general more observations give more information. However, very frequent measurement taking is not practi-cal for most disease control programs. Measurements should be able to at least capture the level of variability of interest to the disease control program. e.g. if the seasonal time scale is relevant for malaria control decisions, then observations of malaria need to be taken at each season.

Trends and Time Series Analysis, by Andrew W. Robertson, IRI

Describe in words what is meant in a climatic time series by an “anomaly” and how could it be calculated.

An anomaly is a deviation of the quantity from its long-term average. One needs to (calculate long-term average and) subtract it from the values in question.

Describe in words what is meant by a trend in a climatic time series and 2 ways in which it could it be defined and calculated.

A trend is a long-term systematic increase or decrease in a time series, which can be obtained thanks to: (1) linear regression “straight line fit”, (2) low-pass filter, such as a moving average.

Malaria Mapping and the Climate Suitability for Malaria Transmission Tool in the Health Map Room, by Judy Omumbo, IRI

How is the year to year variability of rainfall likely to affect malaria transmission?

(Consider an anti-malarial intervention that is delivered in Tanzania over a 12-month period beginning in January 1986. The success of this intervention is to be determined after 2 years).

Discuss the possible implications of the variability of precipitation for assessing the impact of the intervention?

These questions are a discussion so there are no right or wrong answers.

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Day 5: Friday May 21, 2010Questions related to the talks given on Thursday May 20

Remote Sensing as a Tool to Manage Environmental Data, by Pietro Ceccato, IRI

Assignment:

You are responsible for providing relevant information to the Kenyan Ministries of Health and Agriculture on Rift Valley Fever risk in Kenya in the latter half of 2006.You will consider information that would have been available to you during the latter half of 2006 (available monitored climate/environmental informa-tion).

Prepare one summary that you would have provided to the Ministries to asses the situation in terms of risk for the Rift Valley Fever in North Kenya during the rainy season (in the beginning of December 2006). Summary should be about half a page text and should include graphics/maps on NDVI and Rainfall.

Answer: The answer might vary but in general would like to have the following answer (with one figure on NDVI and one figure on rainfall) The past 2.5 months have been anomalously wet for Kenya this year. This is seen in the Normalized Difference Vegetation Index (NDVI), comparing October (figure 1) with December (figure 2). Recent rains have caused a dramatic increase in vegetation, particularly in the eastern part of the country. Increased vegetation is associated with higher soil moisture, leading to more suitable habitat for mosquito breeding sites. This is validated by figures 3 and 4, which compare rainfall patterns and amounts between 2005 and 2006. Due to the high level of rainfall that has occurred over the country – particularly in the eastern part of the country home to a large percentage of pastoralists – vigilant monitoring of possible outbreaks is advised.

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Figure 1: NDVI Oct 2006 Figure 2: NDVI Dec 2006

Figure 3: Monthly Rainfall Estimate Dec 2005 Figure 4: Monthly Rainfall Estimate Dec 2006

The use of the NDVI and rainfall products would have led the relevant authorities to take certain precautionary measures to prepare for this large outbreak of Rift Valley Fever in late December. Forecasts showed above normal

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rainfall creating the ideal conditions for mosquito breeding and disease transmission. If this potential threat of an outbreak was realized, then many decisions could have been made to protect the population and lessen the devastating effects. Specifically, authorities could have sprayed breeding areas and the insides of homes and public buildings, and provided bed nets. Additionally, the livestock could have been vaccinated.

Introduction to Cluster Analysis, by Andrew Robertson, IRI

What is meant by a “cluster” in cluster analysis? A group of relatively homogeneous cases or observations

The K-means method finds K means, where K is the number of clusters that needs to be chosen in advance. What do these “means” refer to? The average of the cases or observations in the group

Day 6: Monday May 24, 2010Questions related to the talks given on Friday May 21

Using GPS, GIS and Google Maps for Public Health, by Mark Becker, CIESIN

Name three basic considerations when planning a GPS data collection survey

Answer: Level of Accuracy required, Knowing what Datum and Projection system to set the unit, Schedule data collection time for optimal arrangement of satellites (DOP values)

What program will let you easily download your GPS data from the receiver and save it in formats in which it can easily be loaded into Google Maps/ Google Earth of ArcGIS?

DNRGarmin

Meningitis and the Environment: Meningitis Environmental Risk Information Technologies (MERIT), by Madeleine Thomson, IRI

When does meningococcal meningitis transmission occur in the Sahel?

a. In the rainy season

b. In the dry season

c. Throughout the year

Answer: c)

How might dust contribute to the occurrence of meningococcal meningitis epidemics (choose one)?

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a. By transporting the bacteria from one person to another

b. By aggravating the nose and throat and allowing the bacteria to cross into the blood stream

c. Through its impact on temperature

Answer: b)

Lagged correlation of Rainfall with Malaria Incidence, by Michael Bell, IRI

Which of the following is an appropriate reason for calculating monthly anomalies of a time series of monthly precipitation data using a 1971-2000 climatological base period?

a. To remove a possibly confounding multi-year linear trend from the time series

b. To remove a possibly confounding mean annual cycle from the time series

c. To correct for changes in variance (heteroscedasticity) in the time series

Answer: b)

Why is it sometimes useful to calculate lagged correlations between climate data and epidemiological data?

There may be a cause-effect relationship between a climate variable and an increase in the occurrence of a disease, such as between an increase in rainfall and an increase in malaria incidence. But while the climate variable may be a triggering mechanism, it may take time for other processes to occur (such as in the life cycle of the disease vector, or pathogen, or in transmission) that ultimately lead to an increase in disease incidence. A lagged correlation may be able to reveal this kind of relationship.

Exercises on K-means and Cluster Analysis: Malaria Seasonality, by Pietro Ceccato, IRI

What is the aim of this analysis?

The aim of this analysis is to understand the spatial and temporal distribution of malaria in Eritrea and Madagas-car in order to understand the relationship between malaria and environmental factors and to take decisions about control strategies.

Can these results help you target your interventions? How?

Open question leading to open answers.

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Module III: Use of Climate Information in Decision-making for Climate-Sensitive Diseases (Days 6, 7, 8, 9, 10)

Day 7: Tuesday May 25, 2010Questions related to the talks given on Monday May 24

Understanding Predictions and Projections in Climate, by Sylwia Trzaska, IRI

Describe, interpret and comment the slide entitled ‘ENSO Forecast’ – copied below

Although there is no comment and not much of a legend on the figure, here are the main elements allowing to read and interpret it: the figure shows multiple lines, color areas, seasonal labels on the X axis, SST Nino3.4 anomalies on the Y axis, a list of dynamical and statistical models and the title indicates ‘Model Forecast of ENSO from May 2008’.

• The multiple lines and multiple models listed tell us that this is a multi-model forecast, a so-called ‘plume’, showing forecasts from all the models participating in the exercise.

• The forecasts d variable are the SST in the Nino3.4 region (cf. http://iri.columbia.edu/climate/ENSO/background/monitoring.html#sst check ‘The Nino regions’.)

• The forecast was made in May ie using observed SST from April (hence the single line from FMA to Apr and the dot in Apr) for the following 10 3-months seasons.

• 14 dynamical models (lines with filled symbols) and 8 statistical models (lines with empty symbols) are represented. The grey line is the multimodel average.

• The three different colors areas represent the different climatological terciles for the Nino3.4 index and are given as reference to help interpret the plume. Note that the boundaries of the terciles change with seasons

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showing a larger amplitude of the middle category in winter, when ENSO reaches its highest amplitude.

• The multimodel mean and most of the model outputs in the plume lie within the ‘normal’ category for the following seasons, giving high confidence that the Nino3.4 SST (and ENSO more generally) are going to be in close to average conditions.

It is important to look at the whole plume to see how close the forecasts from different models are to each other to assess the confidence in the forecast (the larger the spread the less agreement there is among different models, the less confidence we can have that the mean of the forecasts or any of the forecasted scenarios is going to happen; if all the lines are close together we can have high confidence that the actual conditions will be close to those forecasted).

For more info on climate forecasting refer to:

» http://iri.columbia.edu/climate/forecast/tutorial2/

Describe, interpret and comment the slide entitled ‘Temperature, precipitation, consensus map’ – copied below

The series of maps presents projections of temperature and rainfall in Africa for the 2080-2100 period relative to 1980-2000 period (ie in terms of departures from the end of 20th century conditions). The simulations are for the SRES A1B scenario.

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The top 3 maps present departures in temperature for annual mean and DJF and JJA seasons. All of temperature projections show increase in temperature of more than 3C over the continent and over 3.5 C in the arid and semi-arid areas. The increase is projected to be stronger in JJA.

The middle row shows projected departures from ‘current’ state for rainfall. The picture is more contrasted than for temperature with some areas being projected to get more rainfall (‘equatorial’ areas) and some less rainfall (arid areas).

The 3rd row presents the number of models, out of 21 models, projecting increase in rainfall: green-ish colors indicate that the majority is projecting increased rainfall in the given area, brown-ish colors indicate that only a minority is projecting increased rainfall (ie majority is projecting reduced rainfall). White areas show that similar number of models project reduction and increase in rainfall.

It is important to pay attention to the 3rd series of map as they indicate the agreement between models in produc-ing given outcome. Note how wide the white areas are (where approx half of the models project one outcome and half the other), especially during the rainy seasons in the Sahel ( JJA) or Southern Africa (DJF). This tells us that we should take the results for rainfall with a lot of caution. This also tells us that we cannot rely on one single model for the projections because there is no evidence that its projection is more likely to happen that others…

Spatio-temporal Modeling of Meningitis, by Peter Diggle, Lancaster School of Health and Medicine

What is the difference between a static and a dynamic regression model?

In a static regression model, the regression coefficients have fixed, but unknown values, i.e. they are PARAM-ETERS. In a dynamic regression model, the regression coefficients are generated by stochastic processes and their values therefore change over time. Example: A static harmonic regression model for a seasonal phenomenon, Y(t) say, might take the form Y(t) = A + B cos(wt) + C sin(wt) +Z(t) where w is such that the sine-cosine terms show an annual cycle, and Z(t) is a time-sequence of independent residuals. A dynamic version this model would replace some or all of A, B and C by stochastic processes; for example a model with a constant mean but dynamically varying amplitude and phase for the seasonal variation might specify B(t) = B(t-1) + U(t) , C(t) = C(t-1) + V(t), where U(t) and V(t) are time-sequences of independent residuals.

What determines whether prediction of disease incidence in one district can be improved by knowledge of disease incidence in other districts?

If the incidences from all districts in any given week are independent random variables, prediction of disease incidence in one district cannot be improved by knowledge of disease incidence in other districts. If the incidences from all districts in any given week are dependent, it may be possible to obtain better predictions in any one district by taking account of incidences in neighboring districts. The extent to which this is achievable in practice depends on the nature of the spatio-temporal correlation in the incidence process and the investigator’s ability to model the correlation structure accurately.

Using GIS to Exploring the Links between Poverty and Natural Hazards, by Mark Becker, IRI

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Are people living in extreme poverty more exposed to natural hazards?

Yes, this analysis shows that people living in extreme poverty have an increased exposure to natural hazards.

Name one of the ways that we can create a consistent and comparable map of poverty across the globe? We have used infant mortality as a proxy measure for levels of poverty.

Day 8: Wednesday May 26, 2010Questions related to the talks given on Tuesday May 25

Climate Change, War and Disease, by Dia El Naiem, University of Maryland

Climate change is expected to influence the epidemiology of kala azar by affecting:

a. The vector populations

b. Leishmania strains

c. Socioeconomic status of human populations and their exposure to the disease

d. All of the above is correct

e. Only a) and c) are correct

Answer: d)

Within the study areas covered in the lecture, Climate change is expected to result in an:

a. An overall increase in the incidence of kala azar

b. An overall decrease in the incidence of kala azar

c. Either an increase or a decrease in the incidence of kala azar, depending on a complex interaction of environ-mental and socio-economic factors.

d. No effects on kala azar

e. Unknown effects on kala azar incidence

Answer: e)

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Malaria Early Warning and Early Response, by Stephen Connor, IRI

The major advantage of seasonal climate forecasting over case surveillance in malaria early warning system is due to its:

a. Timeliness

b. Accuracy

c. Cost effectiveness

d. None of the above

Answer: a)

If seasonal forecasts can warn of increased risk of malaria epidemics several months in advance – what is the advantage of environmental/meteorological monitoring?

a. Accuracy

b. Cost effectiveness

c. Confirmation of forecast warning

d. None of the above

Answer: c)

Integrated Malaria Surveillance and Control System for Malaria in Colombia, by Daniel Ruiz, IRI

What is the main purpose of system dynamics?

The main purpose of the field of System Dynamics (SD) is to understand the behavior of dynamic systems in which feedback mechanisms and time delays play a significant role. The field of SD provides techniques and tools to investigate (and improve) current decision-making processes and to help decision-makers learn. The aim is to help people make better decisions when confronted with complex dynamic systems (SD helps to understand what is otherwise perceived to be complex and advanced). The modeling language (stocks, flows, and feedback loops) is intuitive and it is common for all kinds of applications.

Why malaria process-based models are useful?

Malaria process-based models are useful because they: (a) provide insights into the complexity of malaria transmis-sion; (b) allow us to estimate the timing and severity of malaria outbreaks; (c) help us to analyze the key variables/confounders behind the onset of malaria outbreaks; (d) allow us to pose and answer “what if ” questions; (e) help us to investigate current decision-making processes and provide quantitative goals for effective interventions; and (f ) help decision-makers learn.

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Epidemic Detection and Monitoring using Thresholds, by Patricia Graves, the Carter Center

What are the advantages and disadvantages of the third quartile as an epidemic threshold?

Advantages:

Simple to estimate; can be easily done without a computer

Sensitive – will give an alert in 25% of years on average (epidemics will not be missed)

Disadvantages:

Not specific – may overestimate the number of epidemics and give false alerts

Needs five years of past data by month for area under consideration.

Using the threshold of a) third quartile 2) mean plus two standard deviations, quantify how many districts of Eritrea experienced malaria epidemics by month during 2003. Answer depends on which years are picked as the baseline “non-epidemic” years. So multiple answers are possible as long as they are justified.

Day 9: Thursday May 27, 2010Questions related to the talks given on Wednesday May 26

Temperature Trends in the Highlands of Kenya, by Bradfield Lyon, IRI

Consider a gridded analysis of temperature derived from irregularly spaced station observations. From the list below, select all that should be a concern to someone considering using data from a single grid point in analyzing temperature variability at that location:

a. If the spatial resolution of the grid may be less than the distance between some stations, thus the grid point values may be based solely on interpolation.

b. If over the time period covered by gridded data set there may have been a different number of stations used in its construction.

c. If the latitude of the grid point selected is between 30 deg. N and 40 deg. N.

d. If the data set has no documentation available on how it was constructed.

Answer: a) b) d)

When looking at a time history of surface air temperature data it is important to know when an observing station was moved just 100 m from its original location because:

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a. The station name may have changed as well

b. The weather instruments may have been damaged during the move

c. Even seemingly slight changes in location can affect temperature readings

d. All of the above

Answer: d)

Linking ENSO and Society, by Tony Barston, IRI

Which of the following are typical seasonal climate effects that occur during El Nińo?

a. Above-average rainfall from October to December in Indonesia

b. Below-average rainfall in southern Africa from November to March

c. Below-average rainfall from October to December in eastern equatorial Africa (e.g., Kenya)

d. Below-average rainfall in the Sahel during July to September

e. Above-average monsoon rainfall in India from July to September.

Answer: b) d)

Which of the following are likely impacts of a moderate to strong El Nińo on society?

a. Greater stress on the anchovy fishing industry in Peru

b. Increased risk of forest fire outbreaks in Indonesia

c. Likelihood of increased malaria epidemic severity in Botswana and northeastern South Africa

d. Heightened risk of poor summer crop yields in central and northern Ethiopia

e. Increased bleaching of corals in the tropical Pacific and other tropical oceans

f. Reduced snowpack and reservoir water in the southwestern U.S.

g. Tendency for more tropical cyclone damage to the Caribbean islands, Mexico, and the U.S.

Answer: a) b) d) e)

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Useful and Usable Climate Products, by Ousmane Ndiaye, IRI

In order to develop useable products should it be ‘science driven’ or ‘ demand driven’? Why, what are the pros and cons? (Designing the product).

This is an open discussion. Science driven is for example you got good results (it can be results found at another place) or has an ‘interesting’ scientific question and want to address it through a project or working group. The other approach demand driven is to ask first the question what and where are the users’ needs and try to address through interaction and iteration. Coming at the end with a product that the users recognize themselves with and will take it.

Which approach works better from your experience a bottom up approach or a top down approach? What are the advantages and disadvantages for each approach? (Implementing the product).

This a follow up question similar to the first one BUT instead of looking at the product you deal with the approach/implementation : the best way to make change to happen. In other words if we want to make a change where to start. For the top down approach you assume the best way to change things is by acting/intervening at the upper level of the ladder. By approaching the administration at the higher level (ministry level, services). The decision is always taken at the management level down to the executive and the user. The bottom up implementation is to say an actual change should always start from the end-users end. The starting point or the level to work is always at the user level. Going to the field facing the reality of the terrain and making change. You have to build first a trust with the user: they know you, they believe in you, in your product and they are ready to take action.

Climate Change and Vulnerability, by Carlos Perez, IRI

Define hazard and risk.

Hazard is a possible source of danger (the potential to cause harm), while risk is the likelihood of harm (probability that the hazard or its consequences will take place). In the context of climate change, hazard refers specifically to physical manifestations of climatic variability or change, such as droughts, floods, storms, episodes of heavy rainfall, long-term changes in the mean values of climatic variables, potential future shifts in climatic regimes and so on. Climate hazards may be defined in terms of absolute values or departures from the mean of variables such as rainfall, temperature, wind speed, or water level, perhaps combined with factors such as speed of onset, duration and spatial extent. Hazards are also referred to as climate events.

Risk is defined as either: (i) the probability of occurrence of a hazard that acts to trigger a disaster or series of events with an undesirable outcome, or (ii) the probability of a disaster or outcome, combining the probability of the hazard event with a consideration of the likely consequences of the hazard.

Define the difference between biophysical vulnerability and social vulnerability, and explain the role of hazards and adaptive capacity under both definitions

Biophysical vulnerability is the degree to which a system is susceptible to, and unable to cope with, adverse effects of

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climate change, including climate variability and extremes. Biophysical vulnerability focuses on physical factors, and is as a function of hazard, exposure and sensitivity. Social vulnerability, on the other hand, is all inherent properties of a system, independent of the hazard to which it is exposed, that mediate the outcome of a hazard event. Social vulnerability is one of the determinants of biophysical vulnerability. Under the biophysical vulnerability definition, hazard is assumed to cause an outcome (generally a damage). The adaptive capacity of a system tends to be ignored as a factor that mediates (buffers or magnifies) the outcomes of a hazard. Under the social vulnerability definition, hazards may or may not cause an outcome depending on the inherent capacities of a system, including its adaptive capacity.

Define adaptive capacity and adaptation.

Adaptive capacity is the ability or capacity of a system to modify or change its characteristics or behavior so as to cope better with existing or anticipated external stresses. Adaptive capacity represents potential rather than actual adaptation. Adaptation is adjustments in a system’s behavior and characteristics that enhance its ability to cope with external stresses. Adaptation is not automatic. The direct effect of adaptation is to reduce social vulnerability.

Explain why development planning should incorporate climate concerns, and why a precautionary approach is needed when integrating adaptation into development programs?

Development planning efforts typically do not pay explicit attention to climate change, often not even to climate variability. Climate changes, however, are accelerating and their impacts are increasingly evident. Poorer social groups are the most at risk. Development planners need information at the local level that climate models cannot provide due to their coarse spatial resolution. They also need better understanding of the risks and potential direct and indirect impacts facing poor communities and households, and strategies to effectively lower vulnerability. Given these uncertainties, a careful, precautionary and no-regrets approach is needed. No regret interventions are those that that yield benefits regardless of future trends in greenhouse gas emissions and climate scenarios. Planners must avoid rushing to adopt interventions that may be of little value or may result in maladaptations and increased vulnerability.

Climate Prediction for Weather Forecast Skeptics, by Simon Mason, IRI

What would you consider the most important information if you had to make a forecast for the following timescales:

a. Tomorrow

b. Next 3 months

c. Next 10 years

d. Next century

Answer: The weather now, Sea-surface temperatures, Sub-surface ocean temperatures, Atmospheric composition

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Why can we not forecast the weather accurately beyond a few days?

The basic principle is that we don’t know the weather exactly right now so the small errors in our knowledge grow rapidly into large errors over time. Initially, over a short time range, we see errors in predicted timing and intensity of weather events and going forward into the future the errors become greater and greater. After about two weeks the forecast and observed weather have nothing more in common than an accidental resemblance.

How to Use Maps as a Tool to Communicate Climate Risks, by Sabine Marx, Center for Research on Environmental Decision Making, and Francesco Fiondella, IRI

Which of the following isn’t a principle outlined in Psychology of Climate Change Communication?

a. Know your audience!

b. Translate data into concrete experience!

c. The more colors, the better!

d. Address uncertainties!

Answer: c)

Explain how the concept of “ less is more” can help you make a map that successfully communicates your information.

It forces you to consider simplifying your design so that only the most essential elements are left on the map. The map user should be able to find the key information easily. Include too much information, and the user will get distracted, confused. To effectively implement “less is more” you need to first understand what the goal of your map is (what questions is it meant to answer), and who it’s meant for.

Weather Roulette: How to Make Decisions given Probabilistic Forecasts, by Simon Mason and Ashley Curtis, IRI

Describe a sensible strategy for investment allocations in a “weather roulette”-type scenario.

If we can assume the forecast is reliable (e.g. a category forecast for 40% likelihood actually occurs 40% of the time) you can maximize growth in profits by using the Kelly strategy. The Kelly strategy involves allocating investments directly proportional to the forecast categories (e.g. putting 40% of your investment to category forecast with 40% likelihood, etc). This strategy has been mathematically demonstrated to give you the maximum GROWTH of profits but not maximum EXPECTED profit. The maximum expected profit could be reached by betting 100% on the category with the highest probability. The problem with this strategy is that even though you have a very small chance of making a huge profit, you have a very high chance of going bankrupt.

If the forecast is NOT reliable than we need to hedge our investment. In the game it is not difficult to see the forecasts are hedged, but then you need to guess how it has been hedged to adjust your allocation accordingly.

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Day 10: Friday May 28, 2010Questions related to the talks given on Thursday May 27

Climate Change and Human Health: Current Impacts and Future Risks, by Patrick Kinney, Mailman School of Public Health

In its 2007 report, the IPCC stated that climate change would have negative impacts on which of the follow-ing health outcomes, with high confidence? (Choose one)

a. Dengue hemorrhagic fever

b. Asthma

c. Undernutrition

d. Diabetes

Answer: c)

Historically in the U.S., which of the following weather factors has been responsible for the most fatalities?

a. Cold

b. Hurricanes

c. Winter storms

d. Heat

Answer: d)

Heat Waves in the USA from the Climate Perspective, by Bradfield Lyon, IRI

It is difficult to come up with a single definition of a heat wave because (circle all that apply):

a. Average temperature conditions can vary greatly from one region to another making it difficult to select an absolute temperature threshold (e.g., 35C) as a criterion.

b. It is not clear how many consecutive days temperatures need to remain above a given level to be considered a heat wave.

c. Heat waves are not of interest to some people.

d. The ability of the body to cool depends on humidity as well as temperature.

Answer: a) b) d)

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Appendix 8: Trainees’ Posters

Local factors that can influence the physical characteristics of heat waves include the following (circle all that apply):

a. The urban “heat island”.

b. Proximity to a large water body.

c. Types of building materials and land surface condition at the location (e.g., cement structures, pavement, bare soil, etc.)

d. Proximity to a restaurant serving very spicy food.

Answer: a) b) c)

Heat Waves and Public Health: a USA Case-Study, by Kim Knowlton, Natural Resources Defense Council, and Department of Environmental Health Sciences, Mailman School of Public Health

Circle two key findings of the California heat wave morbidity study.

a. The Central Coast region, which has relatively cooler temperatures relative to other parts of the state, had by far the highest Rate Ratios of heat-related Emergency Room visits;

b. Children 0-4 years old, as well as the elderly, had high Rate Ratios of ED visits for some causes;

c. There were 1,600 excess Emergency Department visits and almost 1,200 additional hospitalizations across the state during the two-week heat wave; there have been very few prior morbidity studies during such large-scale heat waves, so this was useful information.

d. There were significant increases in respiratory hospitalization rates during the 2006 heat wave in California, relative to rates typical of 2003-2005 summers.

Answer: a) b)

Name three of the four elements of Heat Wave Preparedness/Adaptation plans. Answer: Major points of any three of these four answers:

a. Indentifying vulnerabilities (Assessment of environmental and/or demographic vulnerability);

b. Tracking (or Surveillance of disease and/or environmental conditions);

c. (Climate-smart) Design (of communities and/or buildings);

d. (Public) Education (in personal and/or community preparedness steps).

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Appendix 9: Poster Prize Form

Appendix 9: Poster Prize Form

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Title

Names & affiliations

Targeted country

Objectives

Audience/users

Hypothesis

Methods

Results

Interpretation

Tables & figures

Rate the following from 1 to 5, 5 being the highest score

Is the objective clearly stated?

Does the objective relate to climate and health?

Is the project framed in terms of decision-making?

Do the findings support the objective?

Are the findings well illustrated?

Are climate and health terms and definitions uses appropriately?

Are tables and figures clear?

Are descriptions clear and concise?

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Appendix 10: Contact Information

Appendix 10: Contact InformationTrainees

Betty AbangCDC UVRI Plot 51-59 Nakiwogo RoadP. O. Box 49Entebbe, UgandaPhone: 256-414-321834Fax: 256-414-321457Email: [email protected]

Wakgari AmenteSchool Of Public Health, Addis Ababa UniversityBlack Lion Hospital 2nd Fl.Addis Ababa, EthiopiaPhone: +251-011-5157701Fax: +251-011-5517701Email: [email protected]

Yilma BekeleAddis Ababa University School of Public HealthAddis Ababa, EthiopiaPhone: 251958007719Fax: 251112758634Email: [email protected]

Ali BouattourInstitut Pasteur, BP 74 Place pasteur 1002 Tunis-BelvedereTunis, TunisiaPhone: 002167189340Fax: 0021671791833Email: [email protected]

Ramesh Chand DhimanNational Institute of Malaria Re-search (Indian Council of Medical research), Sector-8 DwarkaNew Delhi -110077IndiaPhone: 911125364701Fax: 911125364701Email: [email protected]

Abenet Girma DessalegnAnti-Malaria AssociationPo Box 27279Addis Ababa, EthiopiaPhone: 251-11-157 54 55Fax: 251-11-157 53 76Email: [email protected]

Tiantian Li60 Haven Ave, B-1 Department of Environmental Health SciencesNew York 10032USAPhone: +1 347 217 2616Email: [email protected]

Ayub Shisia ManyaDivision Of Malaria Control, Ministry Of Public Health And SanitationP. O. Box 19478-00202Phone: +254722221266Fax: +254202716935Email: [email protected]

Stephanie Kay MooreNOAA Northwest Fisheries Science Center 2725 Montlake Blvd. E. Seattle WA 98112USAPhone: +1 206 860 3327Fax: +1 206 860 3335Email: [email protected]

Mouhaimouni MoussaNational MetOffice Of Niger Repub-licBP 218Niamey, NigerPhone: (227) 20 73 21 60Fax: (227) 20 73 38 37Email: [email protected]

Hiwot NamagaUnited States Agency for Inter-national Development Riverside building P. O. Box 1014 Addis Ababa, EthiopiaPhone: +251-115-510088Fax: +251-115-510043Email: [email protected]

Andrew OniarahInvestigation Section Research and Training Centre Nigerian Meteoro-logical Agency P. M. B. 1215 OshodiLagos, NigeriaPhone: +234-803-617-7252Fax: +234-9-8100339Email: [email protected]

Waltaji Terfa KutaneWorld Health OrganizationP.O. Box: 3069 UNECA Compound Addis Ababa, EthiopiaPhone: +25115534777Fax: +251115514037Email: [email protected]

Dieudonné Pascal Alda YakaDirection La Météorologie01 BP 4413 Ouagadougou 01,Burkina FasoPhone: 00226 50356032Fax: 0022650356039Email: [email protected]

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Facilitators

Walter Baethgen , IRI124 Monell61 Route 9WPalisades, New York 10964Phone: +1 845 680 4459Fax: +1 845 680 4864Email: [email protected]

Tony Barnston, IRI111 Monell 61 Route 9WPalisades, New York 10964USAPhone: +1 845 680 4447Fax: +1 845 680 4864Email: [email protected]

Mark Becker, CIESINP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 3658980Fax: +1 845 365 8922E-mail: [email protected]

Michael Bell, IRI101A MonellP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 680 4511Fax: +1 845 680 4864E-mail: [email protected]

Menno Jan BoumaLodge, Puckane, Nenagh, Co. Tip-peraryIrelandPhone: 353 67 24952Email: [email protected]

Daniel Ruiz Carrascal, IRI61 Route 9WPalisades, New York 10964USAPhone: +1 845 680 4465

Fax: +1 845 680 4864Email: [email protected]

Pietro Ceccato, IRI225 MonellP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 680 4424Fax: +1 845 680 4865E-mail:[email protected]

Laurence Cibrelus, IRI133 Monell 61 Route 9WPalisades, New York 10964USAPhone: +1 845 680 4465Fax: +1 845 680 4866Email: [email protected]

Ulisses Confalonieri, ENSP-FIO-CRUZAv. Brasil, 4036/703Rio de Janeiro, BRAZILEmail: [email protected]

Steve Connor, IRI119 Monell 61 Route 9WPalisades, New York 10964USAPhone: +1 845 680 4458Fax: +1 845 680 4864Email: [email protected]

John del Corral, IRI107 Monell61 Route 9WPalisades, New York 10964USAPhone: +1 845 680 4437Fax: +1 845 680 4864Email: [email protected]

Rémi Cousin, IRI13D Monell61 Route 9WPalisades, New York 10964USAPhone: +1 845 680 4422Email: [email protected]

Peter Diggle, Division of MedicineLancaster UniversityLancaster, LA1 4YBUnited KingdomPhone: +44 (0)1524-593957Fax: +44 (0)1524-592681E-mail: [email protected]

Wayne Elliott, Met OfficeFitzRoy RoadExeter EX1 3PBUnited KingdomPhone: +44 (0)1392 886159 Fax: +44 (0)1392 885681E-mail: [email protected]

Dia-Eldin A. ElnaiemOARU Program at NIH (LMVR/NIAID)Twinbrook III, Room 2E3212735 Twinbrook PkwyRockville, MD 20852-8132USAPhone: + 1 301 594 5547Email: [email protected]

Patricia GravesCDC Division of Parasitic Diseases4770 Buford Highway, MS F-22Atlanta, GA 30306USAPhone: + 1 770 448 4634Fax: + 1 770 488 4521E-mail: [email protected]

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Facilitators (cont’d)

Patrick Kinney, Columbia UniversityMailman School of Public Health, SPH/EHS 60 Haven Ave., B1-113ANew York, NY 100232USAPhone: +1 212 305 3663Fax: +1 212 305 4012E-mail: [email protected]

Kim Knowlton, Columbia UniversityMailman School of Public Health, SPH/EHS60 Haven Ave. B1New York, NY 100232USAPhone: +1 212 305 3464Fax: +1 212 305 4012E-mail: [email protected]

Richard Luce, C/O US EmbassyEntoto RoadP.O. Box 1014Addis Ababa, EthiopiaPhone: 251-11-278-1111Fax: 251-11-278-1200Email: [email protected]

Bradfield Lyon, IRI110 MonellP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 680 4475Fax: +1 845 680 4864E-mail: [email protected]

Gilma Mantilla, IRI133A MonellP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 680 4501Fax: +1 845 680 4865E-mail: [email protected]

Sabine Marx, CREDColumbia University 406 Schermerhorn Hall,MC 5501 1190 Amsterdam Ave New York, NY 10027Phone: +1 212 854 8760Email: [email protected]

Simon Mason, IRI232 MonellP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 680 4514Fax: +1 845 680 4865E-mail: [email protected]

Stephen Morse, Columbia Univer-sityMailman School of Public Health722 West 168th Street New York, NY 10032 USAPhone: +1 212 305 8054Fax: +1 212 543 8793 E-mail: [email protected]

Ousmane Ndiaye, IRI133 Monell61 Route 9WPalisades, NY 10964USAPhone: +1 845 680 4503Fax: +1 845 680 4864Email: [email protected]

Judy Omumbo, IRI 105C MonellP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 680 4457Fax: +1 845 680 4864E-mail: [email protected]

Carlos Perez, 139 Monell61 Route 9WPalisades, New York 10964Phone: +1 845 680 4460Fax: +1 845 680 4864Email: [email protected]

Andy Robertson, IRI230 MonellP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 680 4491Fax: +1 845 680 4864E-mail: [email protected]

Michelle Stanton, Lancaster UniversityLancaster, LA1 4YBUnited KingdomPhone: +44 (0)1524-593957Fax: +44 (0)1524-592681E-mail: E-mail: [email protected]

Sylwia Trzaska, IRI208 MonellP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 680 4532Fax: +1 845 680 4865E-mail: [email protected]

Madeleine Thomson, IRI104 MonellP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 680 4413Fax: +1 845 680 4864E-mail: [email protected]

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Support Staff

Ann Binder, IRI130A MonellP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 680 4481Fax: +1 845 680 4866E-mail: [email protected]

Michael Dervin, IRI207B MonellP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 680 4528Fax: +1 845 680 4864E-mail: [email protected]

Francesco Fiondella, IRIP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 680 4476Fax: +1 845 680 4866E-mail: [email protected]

Rise Fullon, IRI130 61 Route 9WPalisades, New York 10964USAPhone: +1 845 680 4418Fax: +1 845 680 4866Email: [email protected]

Thea Murillo, IRIP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 680 4448Fax: +1 845 680 4865E-mail: [email protected]

Barbara Platzer, IRI123A MonellP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USA

Phone: +1-845-680-4426Fax: +1-845-680-4866E-mail: [email protected]

Jason Rodriguez, IRI113C MonellP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 680 4512Fax: +1 845 680 4866E-mail: [email protected]

Jeffery Turmelle, IRI229 MonellP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 680 4529Fax: +1 845 680 4865E-mail: [email protected]

Cathy Vaughan, IRI113B MonellP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 680 4502Fax: +1 845 680 4866E-mail:[email protected]

Sandy Vitelli, IRI140 MonellP.O. Box 1000, 61 Route 9WPalisades, NY 10964-8000USAPhone: +1 845 680 4485Fax: +1 845 680 4864E-mail: [email protected]

Scott WoodColumbia University1200 Amsterdam Ave554 SchermerhornNew York, NY 10027USAPhone: +1 508 241 9627E-mail: [email protected]

technical report:

Summer Institute on Climate Information for Public Health 2010: Evaluations

Gilma Mantilla, Michelle Stanton, laurence cibrelus

TR10-11


Evaluation of the 2010 Summer Institute on Climate Information for Public Health

Palisades, New York

May 17- 28, 2010

Gilma Mantilla

Michelle Stanton

Laurence Cibrelus



Palisades, New York, 10964, USA





» http://iri.columbia.edu/publications/id=1011

With trainees’ sponsorship by

Spanish Meteorological Office

Google.org









ContentsOverview of the Course Evaluation 4

Methods 4

Results 5

• TraineesEvaluation 5

• OrganizersEvaluation 13

• FacilitatorsEvaluation 14

• SupportStaffEvaluation 17

Evaluation Survey 18

• Pre-CourseQuestionnaire 18

• DailyEvaluation 19

• WeeklyEvaluation 20

• EndofCourseEvaluation 22

• QuestionnairetotheOrganizers 31

• QuestionnairetotheFacilitators 34

• QuestionnairetotheSupportStaff 38

4

Summer Institute 2010 | Final Report: Evaluations

Overview of the Course Evaluation

Overview of the Course Evaluation All course participants, including the trainees, facilitators, organizers and support staff, were invited to provide feedback on various aspects of SI 10. This evaluation process was completed online and consisted of various multiple choice and open-ended questions, and was led by Michelle Stanton, a 2008 Summer Institute alumna. The process was entirely anonymous and provided all participants with the opportunity to comment on the design and delivery with the purpose of using this information to improve future climate and health training courses.

MethodsPrior to arriving at the Summer Institute, all of the 13 trainees were asked to fill out a pre-course questionnaire in order to gain information on their background, and in particular their prior knowledge of the relationship between climate and health (refer to the end of the document)

During the SI itself, time was allocated at the end of each day for trainees to complete the online daily evaluation. This brief evaluation asked the participants to give their opinion on the content of the day. Further, at the end of week one and week two, the trainees were asked to complete an overview of what they had gained from the respec-tive week overall. At the end of the two-week course, trainees completed a detailed end of course evaluation where there opinion was asked on all aspects of the course. A copy of each of these evaluation forms is available in at the end of this document

Following the Summer Institute, the facilitators, organizers and support staff who had any involvement in SI 10 were invited to complete an online evaluation. The purpose of these evaluations was to gain further insight into how the contents and delivery of the course were perceived, as well as acquiring their opinions on more specific topics such as how well planned SI 10 had been, their workload associated with SI 10 etc. These evaluations are provided at the end of this document.

The evaluation forms themselves were designed using Google Docs (http://docs.google.com). Questions were open-ended, yes/no or multiple choices. Some aspects of the course were rated on a numeric scale of 1 to 5, where 5 represented the highest rating. Further, nominal scales from 1 to 5 were also used, where in general the highest score represented the most positive response. For example, level of agreement from Disagree (1) to Agree (5), usefulness from Not at all useful (1) to Very Useful (5).

This report presents some descriptive statistics relating to the yes/no and multiple questions included in the evalua-tion forms, in addition to a summary of the participants’ responses to the open-ended questions.

5


Results

Results

Trainees Evaluation

Pre-Course Questionnaire

Of the 9 SI 10 trainees who completed the pre-course questionnaire, 4 stated their profession as a researcher, one a medical epidemiologist, one a climatologist, one worked for the government, one was an informatician and one was a university instructor. The number of years spent in their current profession ranged from three to twenty-six years. Of the nine respondents, six stated they worked in the area of public health, three worked in the climate sector and one responded as ‘Other’.

The trainees were asked various questions in order to gauge their awareness of issues relating to the course such as climate sensitive issues, and various climatological terms (see at the end of the document). The majority of trainees were involved in projects relating to vector-borne diseases such as malaria, and issues relating to food security such as flooding and droughts. A number of trainees were also aware that meningitis is climate sensitive disease. One participant specializes in oceanography and ocean health in the US, hence their experiences were related to this sector.

The trainees’ knowledge of the differences between the climate and the weather appeared to be quite extensive, as was their interpretation of the terms ‘climate forecast’ and ‘probability’. The concepts of climate change and climate variability also seemed well understood. However, the trainees seemed unclear of the characteristics of spatial data/information.

Trainees were familiar with the use of malaria early warning systems, health risk assessment tools and the use of linear regression as tools for assessing the relationship between the climate and particular diseases. However, tools for climate forecasting were not well identified.

Daily Quiz

Overall the daily quiz was well received and generally well answered. There were some issues relating to the format and contents of the quiz however. Due to facilitators having to prepare the quiz questions prior to their session, then being under time constraints during their session, occasionally questions were asked in the quiz on topics that weren’t covered during the session. Further, only 10 minutes per day was allocated to answering the quiz questions, and some questions did not fit into this framework i.e. required extensive amounts of writing. Further, due to language barriers, some participants had difficulties in understanding exactly what questions were asking. The bar chart below presents a summary of the quiz responses. Note that there was no quiz for Day 8 of the course.

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Results

Percentage of quiz questions in the daily quiz answered correctly, incorrectly or with missing answers

Daily Evaluation

Response Rates: A 15-minute session at the end of each day was allocated to complete the online daily evaluation form. Response rates varied between 46% and 100%, with the rate generally decreasing as the course progressed.

The daily evaluation consisted of 6 statements, and the trainees were asked to Disagree/Agree with each statement on a scale of 1 to 5. Trainees were also invited to provide any further comments on the day’s lectures.

Overall the comments were very positive. In general, the trainees found the contents of the lectures and practical sessions interesting and informative. In particular there were positive comments on the lectures relating to the trans-mission dynamics of vector bourne diseases, remote sensing and malaria early warning systems. Initial comments regarding the practical sessions and the use of the Data Library were that it was a little overwhelming and confusing. However, as the course progressed these issues seemed to be resolved. There was praise for the cluster analysis, epidemic detection and GIS practical sessions. There were a number of comments relating to the scheduling of the afternoon sessions as the trainees were frustrated that they did not have enough time to work on their own projects.

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Results

Percentage of trainees who completed each daily evaluation

Weekly Evaluation

Response Rates: All trainees completed the Week One evaluation, whereas 11/13 completed the Week Two evaluation.

The weekly evaluations consisted of four statements which trainees were asked to Disagree/Agree with, and six aspects of the course that were rated in terms of the effectiveness. All ratings were on a scale of 1 to 5. Further, trainees were invited to give their comments on various aspects of the course.

The levels of satisfaction expressed by the trainees over the two evaluations were fairly similar. The trainees strongly agreed with the statements that the sessions accomplished their stated objectives, and that the lectures and other activities were relevant. They felt challenged by the material included in both weeks of the course, and anticipated incorporating the methods learned in their ongoing work.

During the first week, the main aspects of the course that trainees anticipated they would incorporate were the data upload and download facilities within the Data Library and the use of GPS tools. During the second week, the trainees anticipated that they would apply techniques learned to determine epidemic thresholds and, more generi-cally, use the skills they had learned to examine the relationship between the climate and various diseases.

In terms of effectiveness, the reading materials were considered to be on the whole effective, although their relevance seemed to increase in week two in comparison to week one. Lectures and practical exercises were generally consid-ered to be effective, although the effectiveness of the practical exercises seemed to reduce between the end of week one and the end of week two.

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Results

Week One: Reading Materials Week Two: Reading Materials

Effective Ineffective Effective Ineffective

Week One: Practical Exercises Week Two: Practical Exercises


The daily summary and the daily quiz were new features of the Summer Institute. In both of the weekly evaluations these new features were generally considered effective, although one or two trainees disagreed with this statement. Facilitators were largely considered to be effective.

9


Results

Week One: Daily Summary Week Two: Daily Summary


Week One: Daily Quiz Week Two: Daily Quiz

Effective Innefective Effective Innefective

Trainees were invited to include any additional comments they may have regarding the course. Some very positive statements were made. For example, “The balance between class work and social activities is excellent! All those involved in arranging the logistical side of things have done a great job.”, “Congratulations to everybody for doing the maximum for us”. Again, further comments were made regarding the time constraints of the course. In particu-lar it was suggested that lecturers provide a brief description of the additional reading material they have provided in the course pack as the participants didn’t have time to read them during the two-week course. Further, more time was requested to complete the practical exercises.

End of Course Evaluation

Response Rates: 10 out of the 13 trainees completed the end of course evaluation.

The end of course evaluation was a fairly extensive document covering the topics of Course Objectives; Course Content; Additional Course Activities; Practical Sessions; The Project; Global Transferability of the Course Contents; Course Design; Course Delivery; General

Course Objectives: The trainees strongly agreed with the statements that the objectives of the course were clearly

10


Results

stated, and with respect to these their expectations were met or exceeded. In particular they were impressed with the amount of information held within the Data Library, and the hands-on experience that they gained in utilizing it.

Course Contents: The trainees agreed that the contents of the course were covered in a sufficient amount of depth, and they found the contents very engaging. When asked to specify the topics which were not covered enough, the trainees requested that more case studies were considered during the course such as West Nile Virus and tick borne diseases. One trainee commented that climate change was not sufficiently covered.

Additional Course Activities: The additional activities that were arranged during the course such as the panel discus-sion at Mailman School of Public Health and the Weather Roulette game were appreciated by the trainees. However, several trainees commented that the lunchtime seminars weren’t as successful as they weren’t able to concentrate during these sessions and would have appreciated a proper lunch break more.

Practical Sessions: Most trainees agreed that the course was enhanced by the practical sessions although there were mixed opinions regarding whether or not there was a good balance between these sessions and the lectures. The majority of trainees who completed the evaluation (7/10) neither agreed nor disagreed with the statement that the data library was easy to use. When asked to comment further, many of the trainees requested that more time be made available to learn to navigate through the data library and enhance their ability to utilize its features.

I thought there was a good balance between lectures and practical exercises I found the Data Library easy to use

Disagree Agree Disagree Agree

The Project: The majority of trainees strongly agreed that there was value is using their own data for the project (9/10), which was an innovation of this year’s Summer Institute. The exercise of producing a poster was considered to be slightly more useful than the production of the 300-word summary, but both exercises were valued. When asked whether or not they thought adequate time was given to work on the project, the response was quite mixed.

Adequate time was given to work on the project

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Results

Disagree Agree

When asked for additional comments on the project, the trainees requested more detailed guidelines on what the project involved, and what sort of data would be suitable to use for the project. Several commented that more time should be dedicated to producing the poster, whereas the summary exercise was redundant.

Global Transferability of the Course Contents: This section included many open ended questions regarding how useful the trainees found the course contents with respect to their ongoing work. When asked to comment on which of the course’s topics were most instructive to them, the trainees listed a vast array of topics, and several commented that they found all topics in the course equally instructive. Most trainees found the contents of the course relevant to their geographical region and organization. Topics listed as being most valuable were again varied, and hence a single topic cannot be identified. With respect to the topic that was least relevant to their work, several trainees cited the heat waves in the USA session. Suggestions made by participants on how the course could be changed to enhance their learning experience included replacing some of the lectures with more practical sessions, and to have a more gradual scale with respect to the difficulty of the practical exercises.

Further, it was suggested that more case studies from other non-African countries be incorporated into the course. All participants agreed that aspects of the course could be incorporated into the training program of their organiza-tion. The majority of trainees believed that they would change their working practices as a result of this course. Several trainees stated that they will incorporate climate information in their future health research, and the Data Library was quoted as a valuable source from which climate data could be obtained free of charge. In addition, a number of trainees commented that, following the information they had gained during the course, they would endeavor to strengthen their collaborations between the public health and climate communities.

All trainees agreed that they had increased their network within the climate and health community by attending the course. Trainees comments on this subject included “In the event that my organization embarks on implementing an early warning system, I will know who to contact for input”, “All of our teachers were highly qualified and specialists in their field” and “I have met people from different countries and disciplines. The interactions were fruitful and I hope to use these contacts for more collaboration”.

Course Design: Trainees agreed that the course was well structured and the course design, on the whole allowed them to learn at their own pace. The course was deemed to be just the right length.

12


Results

What is your opinion of the length of the course? There was enough time to engage in practical, hands-on work?

Too Long Too Short No Yes

As in previous sections, some trainees disagreed that there was enough time to engage in the practical work. Most of the participants (8/10) stated that they had enough time to read at least some of the reading material provided in the manual. Of those who read the material, the majority of participants believed that the reading materials were valuable and would recommend them to others.

The morning review sessions were generally considered to be useful in enhancing the trainees’ understanding of the course, as were the morning discussions of the previous day’s material which were lead by at least one of the relevant facilitators. Most trainees agreed that the morning quiz sessions were useful in helping them to understand the content of the course, although there were comments that the answers to some of the quiz questions had not been taught during the course.

The morning quizzes were useful in helping me to understand the content of the course

Disagree Agree

Out of the 10 trainees who completed the evaluation, four had taken a similar course previously. When asked to compare the Summer Institute with these other courses, the trainees preferred the SI due to the hands-on experi-ence the gained using the Data Library, the contents of the course, and the use of internationally renowned experts.

13


Results

The majority of participants agreed that the sessions began and finished on time, and that the course materials and facilities were adequate.

There was high praise of the course facilitators, organizers and support staff, with trainees strongly agreeing that they were in general available for answering questions and discussions when required. When asked to comment on the course delivery, trainees stated that “The faculty facilitators and organizers deserve commendation” and “The course delivery and organization was perfectly scheduled and I hope to accomplish the same in training I will undertake in the future.”

General: Trainees agreed that the food they received during the course was enjoyable, although there were some comments that at times too much was provided. The accommodation received a lot of praise. The extra activities undertaken outside of the learning environment such as the nature walk and trip to Manhattan were well received. When asked whether they experienced any significant problems throughout the course, such as language barriers or the course material being too challenging/not challenging enough, nine of the ten respondents said ‘No’. There were comments regarding ground transportation to and from the airport as some trainees found the experience a little overwhelming, and further would’ve liked this expense to be included in the course fees.

Organizers Evaluation Response rates: Of the five organizers invited to complete the questionnaire, four responded. Of these, three indicated that they were heavily involved in organizing the SI, while one indicated only light involvement.

The organizers were asked to rate participant selection, the content of the curriculum, the course scheduling, the interaction of the planning committee with the lecturers and/or the support team, overall coordination and technical support out of 5, with 5 representing the highest score. All four of the responders rated each category as 4 or 5. When asked to identify the strengths of the SI, many features were listed including experience gained from previ-ous Summer Institutes, having a member of staff dedicated to specific activities i.e. curriculum development and the amount of interaction incorporated into the course. The major area of improvement identified by the organizers was an increase in the number of IT support staff from one person overall to one person in the morning and another person in the afternoon. Further, the organizers suggested that the SI facilitators need to be more involved in the trainees’ projects.

Two respondents had viewed the trainees’ projects, and commented on the high quality of them. Further, one respondent believed that giving the trainees the opportunity to use their own data had empowered them, and enabled them to better demonstrate the amount of additional knowledge that had acquired through attending SI 10. Three respondents had been present during at least one of the morning review sessions and found them very useful, believing they had greatly assisted in emphasising the ‘take home’ messages of each of the sessions. However several respondents commented that some of these sessions required more time than that available, and therefore may benefit from being moved to later in the morning.

All four respondents agreed that the SI had provided them with new research project insights or opportunities for collaboration, commenting that there was an opportunity to write a paper on ‘knowledge sharing’ using the SI as an example of this.

Overall, the four respondents rated the SI highly, and recommended that for future years the IT support is improved, and further the involvement of the Mailman School of Public Health is increased.

14


Results

Facilitators EvaluationResponse Rates: Of the 27 facilitators invited to complete this questionnaire, 19 responded (67%). Of the respondents, ten described themselves as core lecturers, nine lead or assisted in a practical session, one lead a lunchtime seminar, and three described their involvement as ‘Other’. Note that respondents could check more than one option.

Firstly, the facilitators were asked to rate a number of planning components on a scale of one to five, where five represented the highest score. Overall, the components were rated highly, although there were indications that the participant selection process and the interaction between the planning committee and the lecturers/support team could be improved.

Participant Selection Contents of the curriculum

Lowest score Highest score Lowest score Highest score

Course Scheduling the lecturers and/or support team

Interaction of the planning committee with


Overall Condition Technical Support

15


Results


The facilitators were then asked to comment on their ratings. Overall there was high praise of the way in which the course was organized and delivered. Some commented that perhaps the course was too heavily loaded and that trainees would have benefitted from having the opportunity to focus on fewer activities. Further, there were comments on the technical support. Although overall things ran well, one facilitator commented that the SI would benefit from having two technical support people who would take care of the morning and afternoon sessions separately, rather than have one person do everything.

The majority of respondents (18/19) believed that their lectures/practical sessions matched the objectives of the course, and further that they addressed the expectations of the students. Several of the facilitators commented that the trainees were very engaged and asked lots of questions regarding their session(s).

Of the seven respondents who said they were involved in the daily question and answer sessions, all rated the usefulness of this activity highly. One facilitator commented that “I think the summaries given by the participants and the question/answer sessions were EXTREMELY useful in revising the concepts that were discussed during the previous day”. Of the six respondents who said they were involved in the projects, most agreed that allowing the trainees to use their own data was useful with respect to how engaged they were in their projects.

The workload associated both with the preparation for the SI and the delivery of the SI varied between facilitators. Of the 19 respondents, 16 (84%) believed that they received sufficient information regarding their role in the SI prior to it starting.

How would you rate the work load associated with the delivery of the Summer Institute?

How would you rate the workload with the prepara-tion of the Summer Institute?

Light Heavy Light Heavy

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Results

I received sufficient information regarding my role in the Summer Institute prior to the start of the course

Disagree Agree

Fifteen (79%) of the respondents believed that the SI had provided them with new research project insights or opportunities for collaboration. When asked to comment further, several of the facilitators cited specific examples of how they plan to collaborate either with SI trainees or IRI staff.

Thirteen (68%) of the respondents agreed that the interaction with the participants and/or other facilitators during the SI had challenged them to think in new ways. A common response to how they had been challenged was related to the variety of different backgrounds of the trainees, both culturally and professionally, and how best to communicate clearly in these situations.

The facilitators’ response to how they would rate the SI is presented below. The majority of respondents rated the SI highly.

How would you rate the overall SI 2010

Excellent Poor

When asked to comment on ways in which the SI could be improved in future years, the main recommendations were that the amount of material covered during the course be scaled back in order for the trainees to have more time to concentrate on their projects. Further, it was recommended that the number of staff involved in the course be

17


Evaluation Survey

increased. In particular, more technical support, additional support with the administrative tasks such as compiling the course material and more staff to assist in the trainees’ projects was requested. A less formal welcome session was also suggested to enable the trainees to introduce themselves more clearly in a less intimidating environment.

Support Staff EvaluationResponse rate: Of the 14 members of the support staff invited to complete this evaluation, 10 (71%) responded.

The respondents were asked to rate the following planning components out of 5, with 5 being the highest score: Guidelines from the planning committee for preparing their support; Support from the planning committee before and during the delivery of the Summer Institute; Overall Coordination. Each of the respondents rated these catego-ries as either a 4 or a 5. When asked to comment on the planning committee, the praise given by the support staff was high, with commendation given to their clear specifications and amount of interaction that took place. There were a few comments that a scaling down of the amount of material introduced to the trainees would be advisable.

The workload of the respondents both prior to and during the SI was very varied.

How would you rate the work load associ-ated with the preparation of the Summer Institute?

How would you rate the workload with the preparation of the Summer Institute?

Light Heavy Light Heavy

Overall the SI was rated highly by the support staff. When asked to provide comments or suggestions, a number of issues were raised. Several respondents raised the issue of the amount of work involved in printing and organizing the course material, suggesting that in the future this task is outsourced. An additional suggestion was that the majority of the course material could be stored on a pen drive, hence reducing the amount of printing necessary.

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Evaluation Survey

Evaluation Survey

Pre-Course QuestionnairePlease answer the following questions regarding your prior knowledge to the best of your ability. If you do not know an answer to a question, move on to the next question. Your responses will be used to help us evaluate your learning. All responses will be kept confidential.

Your InformatIonProfession (e.g. Government official, researcher, etc…): Years in current profession: _______Sector: Climate_______, Public Health______, Other ______

QuestIons1. List any climate-sensitive problems you are aware of: (You may include details about the issues you deal with in your country)

2. Describe the following terms in one sentence each:a. weather:b. climate:c. climate forecast:d. probability:e. seasonality:

3. Describe the difference between climate change and climate variability.

4. There are various methods used in predicting the effect of climate on disease. Please de-scribe those you are familiar with in the space below.

5. The study of climate-sensitive diseases requires analysis of data across space and across time. List those geographic features you are aware of that are used to characterize information across space. In other words, what features are characteristic of spatial data/information?

6. Climate data is described using a variety of units of measure. How is rainfall measured?a. Millimeters / dayb. Millimeters / monthc. Millimeters / every six daysd. Millimeters / ten dayse. all of the abovef. none of the above

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Evaluation Survey

7. How are climate forecasts produced? (i.e. What methods and tools are used?)

8. How are climate forecasts used? (i.e. by non-climate professionals, such as public health experts)

9. Besides climate, what other factors play a role in your decision making? (e.g. National economy, availability of funding, etc…) Please list four primary factors (which may include the examples given) in your decision-making and rank your answers as MORE important, LESS important, or EQUAL in importance than climatic factors.

FACTORS IMPORTANCEa. ___________________ MORE EQUAL LESS b. ___________________ MORE EQUAL LESS c. ___________________ MORE EQUAL LESSd. ___________________ MORE EQUAL LESS

Comments:Final Questionnaire to the Trainees (includes a Daily, Weekly and Overall Course Evaluation)

Daily Evaluation What is your major area of expertise/professional Activity *

Climate Public Health

The lecture speakers were clear and easy to understand *

1 2 3 4 5

Disagree Agree

Today’s lecture challenged me to think in new ways *

1 2 3 4 5

Disagree Agree

The lectures fulfilled my expectations *

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Evaluation Survey

1 2 3 4 5

Disagree Agree

The scheduling and sequence of the lectures made sense *

1 2 3 4 5

Disagree Agree

The resources, references and other materials were appropriate and helped me understand the content *

1 2 3 4 5

Disagree Agree

The visual aids used in the lecture were appropriate and helpful *

1 2 3 4 5

Disagree Agree

Please provide any additional comments on today’s lectures:

Weekly EvaluationOverall, the sessions have accomplished their stated objectives throughout the week *

1 2 3 4 5

Disagree Agree

Over the past week I have found the contents of the lectures and other activities relevant *

1 2 3 4 5

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Evaluation Survey

Disagree Agree

The lectures and activities of the past week have challenged me to think in new ways *

1 2 3 4 5

Disagree Agree

I expect to incorporate methods learned over the past week in my ongoing work *

1 2 3 4 5

Disagree Agree

If applicable, please comment on how you intend to incorporate methods learned in your ongoing work. Please rate the overall effectiveness of each of the following over the past week: Reading materials:

1 2 3 4 5

Disagree Agree

Lectures:

1 2 3 4 5

Disagree Agree

Practical Exercises:

1 2 3 4 5

Disagree Agree

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Evaluation Survey

Daily summary by participant: *

1 2 3 4 5

Disagree Agree

Daily quiz: *

1 2 3 4 5

Disagree Agree

Facilitators and Instructors:

1 2 3 4 5

Disagree Agree

Please add any additional comments you may have relating to the course over the past week below:

End of Course Evaluation

Course objeCtIves The objectives of the course were stated clearly *

1 2 3 4 5

Disagree Agree

My expectations, with respect to the objectives of the course were met or exceeded *Please comment below

1 2 3 4 5

Disagree Agree

Please comment

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Evaluation Survey

Course Contents

The contents of the course fulfilled my expectations *

1 2 3 4 5

Disagree Agree

The course went into a sufficient amount of depth *

1 2 3 4 5

Disagree Agree

The course was delivered in a way that was easy to understand *

1 2 3 4 5

Disagree Agree

The contents of the course agreed with the objectives of the course *

1 2 3 4 5

Disagree Agree

I found the contents of the course engaging *

1 2 3 4 5

Disagree Agree

There was an agreement between the course objectives and the course contents *

1 2 3 4 5

Disagree Agree

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Evaluation Survey

What topics do you think were not covered fully enough? Please add any additional comments you may have relating to the course contents below: addItIonal Course aCtIvItIes

I found the course was enhanced by the additional activities (such as lunchtime seminars, panel session at Mailman School of Public Health, Weather roulette) *

1 2 3 4 5

Disagree Agree

Comments on additional course activities:

PraCtICal sessIons

I found the course was enhanced by the practical sessions *

1 2 3 4 5

Disagree Agree

I thought there was a good balance between lectures and practical sessions *

1 2 3 4 5

Disagree Agree

I found the Data Library easy to use *

1 2 3 4 5

Disagree Agree

I found the practical sessions engaging *

1 2 3 4 5

Disagree Agree

Please add any additional comments you may have relating to the practical sessions below:

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Evaluation Survey

the ProjeCt

I found the option to use my own data for the project valuable *

1 2 3 4 5

Disagree Agree

Prior to starting the course you were given the Project Guidelines. How useful did you find these guidelines? *

1 2 3 4 5

Disagree Agree

During the course you were given a template for the poster. How useful did you find this tem-plate? *

1 2 3 4 5

Disagree Agree

Adequate time was given to work on the project *

1 2 3 4 5

Disagree Agree

Producing a poster was a valuable exercise *

1 2 3 4 5

Disagree Agree

Producing a 300-word summary was a valuable exercise *

1 2 3 4 5

Disagree Agree

Please provide any comments relating to the project below:

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Evaluation Survey

Global transferabIlItY of the Course Contents

Which topics of the course did you find most instructive to you?

Was the content of the course valuable to your geographical region and your organization?(Please provide details on what was and was not relevant.) What part of the course was MOST valuable to your work? What part of the course was LEAST valuable to your work? What would you change about the course to enhance your learning experience? Bearing in mind the diversity of the course participants, what additional course content would you recommend to be developed for this course for the future? Do you think these aspects of this course could be incorporated into the training program of your organization? *

Yes NoPlease explain your answer: Do you think you will change any of your working practices as a result of this course? *

Yes No Don’t Know

If yes, please comment further

I think I have increased my network within the climate and health community by attending this course *

1 2 3 4 5

Disagree Agree

Please provide further comments:

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Evaluation Survey

Course desIGn

The course was well structured *

1 2 3 4 5

Disagree Agree

The design of the course allowed me to learn at my own pace *

1 2 3 4 5

Disagree Agree

What is your opinion of the length of the course? *

1 2 3 4 5

Too Short Too Long

During the course I was given the opportunity to reinforce my understanding of the content *

1 2 3 4 5

Disagree Agree

28


Evaluation Survey

The scheduling of lectures, lunchtime seminars and practical sessions was intuitive and made sense *

1 2 3 4 5

Disagree Agree

There was enough time to engage in practical hands-on work *

1 2 3 4 5

Disagree Agree

Did you have enough time to read the reading materials provided in the manual *

Yes, I read most of the manual Yes, I read some of the materialNo, I did not have enough time

If you answered ‘Yes’ above do you agree with the following statement: The reading materials added value to the presentations

1 2 3 4 5

Disagree Agree

If you answered ‘Yes’ above do you agree with the following statement: I would recommend the reading materials to others

1 2 3 4 5

Disagree Agree

The morning review sessions (presented by a selected participant) were useful in helping me to understand the content of the course *

1 2 3 4 5

Disagree Agree

29


Evaluation Survey

The morning quizzes were useful in helping me to understand the content of the course *

1 2 3 4 5

Disagree Agree

The morning discussions (lead by a facilitator from the previous day) were useful in helping me to understand the content of the course *

1 2 3 4 5

Disagree Agree

The course evaluation process was suitably designed *

1 2 3 4 5

Disagree Agree

Additional comments on the course design:

Course delIverY

Have you taken a course like this before? *Yes No

If yes, how does this course compare? All activities began/finished on time *

1 2 3 4 5

Disagree Agree

Course materials were appropriate and helped me to learn the course contents *

1 2 3 4 5

Disagree Agree

30


Evaluation Survey

Course facilities (i.e. computers, meeting spaces) were appropriate for the course *

1 2 3 4 5

Disagree Agree

Course facilitators were available to answer questions when needed *

1 2 3 4 5

Disagree Agree

IRI researchers and staff were available for networking and discussion *

1 2 3 4 5

Disagree Agree

IRI staff/facilitators were helpful in addressing my questions regarding travel, accommodation and other personal matters *

1 2 3 4 5

Disagree Agree

Please provide us with any additional comments you may have regarding the course delivery

General

I enjoyed the food that was provided throughout the course

1 2 3 4 5

Disagree Agree

Additional comments Suitable accommodation was provided for the course (i.e. the hotel facilities, location etc.)

1 2 3 4 5

Disagree Agree

31


Evaluation Survey

addItIonal Comments The extra activities undertaken during the course (nature walk, celebrity walk, tour of Manhat-tan etc) were successful

1 2 3 4 5

Disagree Agree

Did you experience any significant problems during the course? i.e. was language a problem, was the course content/materials too challenging or not challenging enough? *

Yes No

If yes, please elaborate in the space below:

If you have any additional comments on the course please provide them below. Thank you for your response, and we hope you enjoyed being a part of the Summer Institute 2010, and we hope you enjoy being part of our Climate and Health community. Keep in touch!

Questionnaire to the Organizers

Rate your opinion of the following planning components, where ‘5’ represents the highest score. Participant selection

1 2 3 4 5

Content of the curriculum

1 2 3 4 5

32


Evaluation Survey

Course Scheduling 1 2 3 4 5

Interaction of the planning committee with the lecturers and/or support team 1 2 3 4 5

Overall Coordination

1 2 3 4 5

Technical Support

1 2 3 4 5

Please comment on the ratings given above Please identify the strengths of the Summer Institute In your opinion, which areas need to be improved and which gaps need to be filled. Please provide detail (e.g. logistics, design of the curriculum, objectives, choice of participants, ability to improve field decision-making). How would you describe your involvement in the Summer Institute? *

1 2 3 4 5

Light involvement Heavy involvement Did you have the opportunity to view the participants’ projects/posters *

Yes No

If ‘yes’, how useful do you think the use of their own data was with respect to how well the par-ticipants engaged in their projects

1 2 3 4 5

Not at all useful Very useful

Any further comments with respect to the projects:

33


Evaluation Survey

Were you present for, or involved in any of the morning sessions of the course, during which a summary and discussion of the previous day’s events were held?

Yes No

If ‘yes’, please rate how useful these sessions were in relation to improving participants’ involve-ment in the course

1 2 3 4 5

Not important Very important

Any further comments on the morning sessions: Did you participate in any of the social activities that were arranged during the course (i.e. nature walk, celebrity walk etc.)

Yes No

If ‘yes’, how useful were these activities in improving your relationship with the course partici-pants?

1 2 3 4 5


Do you anticipate being involved in the Summer Institute next year? *

Yes No Don’t Know

How would you rate the workload associated with the preparation of the Summer Institute (i.e. before it started)? *

1 2 3 4 5

Light involvement Heavy involvement

How would you rate the workload associated with the delivery of the Summer Institute (i.e. during the SI)? *

1 2 3 4 5

Light involvement Heavy involvement

34


Evaluation Survey

Did the Summer Institute provide you with new research project insights or opportunities for collaboration? *

Yes No

Please comment further Did the Summer Institute and the interaction with the participants and/or other lecturers chal-lenge you to think in new ways? *

Yes No

Please comment further How would you rate the overall Summer Institute 2010? *

1 2 3 4 5

Excellent Poor

Please, provide any comments and/or suggestions that you think would be useful to better pre-pare and implement the next Summer Institute below .

Questionnaire to the FacilitatorsWere you responsible for: *Please tick all applicable answers

A core lecture A practical session A lunchtime seminar Other:

Rate your opinion of the following planning components, where ‘5’ represents the highest score.

Participant selection 1 2 3 4 5


1 2 3 4 5

Course Scheduling

35


Evaluation Survey

1 2 3 4 5

Interaction of the planning committee with the lecturers and/or support team

1 2 3 4 5


1 2 3 4 5

Technical Support

1 2 3 4 5

Please comment on the ratings given above Do you feel that your lecture(s)/practical session(s)/talk matched the objectives of the Summer Institute? *

Yes No

Please explain your answer Do you think that your lecture(s)/practical session(s)/talk addressed the expectations of the students? *

Yes No

Please explain your answer Were you involved in the question and answer sessions which were conducted each morning? *

Yes No

Were you present for any of daily summary presentations which were prepared by a course participant each morning? *

Yes No

36


Evaluation Survey

If you answered ‘yes’ to at least one of the two questions above, please rate how useful you think these activities were in relation to improving the participants’ involvement in the course

1 2 3 4 5


Any further comments Were you involved in the participants’ projects or, did you have the opportunity to view their posters? *

Yes No

If ‘yes’, how useful do you think the use of their own data was with respect to the way in which the participants engaged in their projects?

1 2 3 4 5


Any further comments

Did you participate in any of the social activities that were arranged during the course (i.e. nature walk, celebrity walk etc)? *

Yes No

If ‘yes’ , how useful were these events in improving your relationship with the course partici-pants?

1 2 3 4 5



1 2 3 4 5

Light Heavy

37


Evaluation Survey

I received sufficient information regarding my role in the Summer Institute prior to the start of the course *

1 2 3 4 5

Disagree Agree

The amount of information regarding your role in the Summer Institute prior to the start of the course was sufficient *

1 2 3 4 5

Disagree Agree


1 2 3 4 5

Light Heavy


Yes No

Please comment further Did the Summer Institute and the interaction with the participants and/or other lecturers chal-lenge you to think in new ways? *

Yes No

Please comment further How would you rate the overall Summer Institute 2010? *

1 2 3 4 5

Excellent Poor

Please, provide any comments and/or suggestions that you think would be useful to better pre-pare and implement the next Summer Institute below.

38


Evaluation Survey

Questionnaire to the Support Staff

Rate your opinion of the following planning components, where ‘5’ represents the highest score.

Participant selection 1 2 3 4 5


1 2 3 4 5

Course Scheduling 1 2 3 4 5

Interaction of the planning committee with the lecturers and/or support team

1 2 3 4 5


1 2 3 4 5

Technical Support

1 2 3 4 5

Please comment on the ratings given above

Please identify the strengths of the Summer Institute In your opinion, which areas need to be improved and which gaps need to be filled. Please provide detail (e.g. logistics, design of the curriculum, objectives, choice of participants, ability to improve field decision-making).

39


Evaluation Survey

How would you describe your involvement in the Summer Institute? *1 2 3 4 5

Light Heavy

Did you have the opportunity to view the participants’ projects/posters *

Yes No

If ‘yes’, how useful do you think the use of their own data was with respect to how well the par-ticipants engaged in their projects?

1 2 3 4 5


Any further comments with respect to the projects: Were you present for, or involved in any of the morning sessions of the course, during which a summary and discussion of the previous day’s events were held?

Yes No

If ‘yes’, please rate how useful these sessions were in relation to improving participants’ involve-ment in the course

1 2 3 4 5


Any further comments on the morning sessions: Did you participate in any of the social activities that were arranged during the course (i.e. nature walk, celebrity walk etc.)

Yes No

If ‘yes’, how useful were these activities in improving your relationship with the course partici-pants?

1 2 3 4 5


40


Evaluation Survey

Do you anticipate being involved in the Summer Institute next year? *

Yes No Don’t Know


1 2 3 4 5

Light Heavy


1 2 3 4 5

Light Heavy


Yes No Please comment further Did the Summer Institute and the interaction with the participants and/or other lecturers challenge you to think in new ways? *

Yes NoPlease comment further How would you rate the overall Summer Institute 2010? *

1 2 3 4 5

Excellent Poor

Please, provide any comments and/or suggestions that you think would be useful to better pre-pare and implement the next Summer Institute below.

Documents

Summer Institute on Climate Information for Public Health 2010