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One Lunar Health One Lunar Health Carl Carl Koppeschaar Koppeschaar BDPH 56, Moon City, 25 October 2069 BDPH 56, Moon City, 25 October 2069

Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

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Talk by Carl koppeschaar on the 1st Symposium of Big Data and Public Health, 2013

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Page 1: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

One Lunar Health

One Lunar Health

Carl KoppeschaarCarl KoppeschaarBDPH 56, Moon City, 25 October 2069BDPH 56, Moon City, 25 October 2069

Page 2: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

Energy crisis

• Needed in 2080/90: 98 TW energy

• Available: 90 TW

• Possible end of industrial development

• Solution: extraterrestrial energy source

Page 3: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

Energy from the Moon

• Solar energySolar energy

• Helium-3

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Lunar Solar Power

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1 tonne helium-3 =

130 milion barrels oil =

$ 300 billion

100 tonnes helium-3 =

$ 30 trillion

Costs of 5 space shuttle loads of 20 tons: $ 5 billion

Page 8: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses
Page 9: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses
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Lunar Explorers Society

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Road map to the lunar future

• 2002-2010: satellites and landers

• 2010-2015: robot missions

• 2015: manned landings

• 2020: permanently manned moonbase

• 2030: more moonbases and industry

• 2040: lunar villages

• 2060: lunar cities

• 2069: Republic of the Moon

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2069 Lunar Olympic Games

Needed: Mass Gathering Medicine

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Continuous surveillance for outbreaks of infectious diseases

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One Martian Health

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One Alien Health …

There might be zillions of viruses and other pathogens out there!

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Carl Koppeschaar

Big Data and Public Health, Rio de Janeiro – October 25, 2013

Disease Radar: self-reported participatory surveillance for influenza and other diseases.

Page 24: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

2003: The Great Influenza Survey

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Project to raise the public awareness on flu

Interactive and participatory combination of science and communication informing the general audience on influenza

Inviting people to become ‘flu-reporters’, filling in their health status voluntarily every week in order to help researchers in finding more information on the spread of the influenza virus

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Recruitment

Media attention Posters, flyersSchool materialFlu games

Page 27: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

How to keep participants ?

Weekly newsletters with the latest ‘flu news’

Informative website: offering ‘flu news’, ‘flu games’, background information, expert interviews, free educational material at all levels for downloading, etc.

Focus on different target groups: laymen, press, school children and their teachers, families, and to a smaller extent, professional health care workers

Communicate results: participants help scientists

Reliable and easily accessible information: expert proven information, maps and graphs

Page 28: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses
Page 29: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

Fast and simple survey

Postal code

Age

Smoker

Transportation

Vaccine

Allergy

Symptoms

Cough

Fever

Sneezing

Muscle pain

...

Start of symptoms

GP consultation

Single intake questionnaire:

Weekly newsletter + personal symptom’s questionnaire:

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Community of ‘flu-reporters’

Blue = common cold

Red = ILI (influenza-like illness)

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Participants in all age groups

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Correction for age

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Loyal participation

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Early results

Bicycle

car

Public transport

With pet animals

Without pet animals

Families with children

Families without children

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“Female flu”

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Incidence in different age groups

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Risk groups in smoking, chronic diseases, but

not in terms of transport means!

Significantly more ILI in:

• children: OR = 1.8 [1.7-2.0]

• parents: OR = 1.4 [1.4-1.5]

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Regional transmission of the flu

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Flu activity by region

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Start of the seasonal epidemic

Baseline

Early signalOnset epidemic

> 350 (95%)

> 500 (99%)

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Early media attention

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Bias in GP’s reporting (1)

Visits many days after start of illness

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Bias in GP’s reporting (2)

Seniors more often visit their GP

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Bias in GP’s reporting (3)

Changes in visits to GP due to media reporting (2009 pandemic)

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Faster than GP’s sentinel posts

A country like the US would need at least 400,000 participants to obtain similar results!

How many subgroups of the population do we need to obtain reliable results?

The Netherlands: on average more than 2 weeks

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What can still be improved?1. Number of participants

2. Daily reporting

3. Children

Number of participants

Number of participants per country

Page 48: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

1. Number of participants

2. Daily reporting

3. Children

Number of participants

Italy: Low reliability at 0.002% of the population

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Number of participants

Netherlands and Belgium: e-mail reminders + news letters sent out through the week

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Transmission on a European scale

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From west to east and from south to northPaget WJ, Marquet R, Meijer A, Van der Velden J: Influenza activity in Europe during eight seasons (1999-2007): an evaluation of the indicators used to measure activity and an assessment to the timing, lenght and course of peak

activity (spread) across Europe. BMC Infectious Diseases, 2007; 7: 141.

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What is the true role of transportation?

Van den Broeck, Gioannini, Gonçalves, Quaggiotto, Colizza, Vespignani: The GLEaMviz computational tool, a publicly available software to explore realistic epidemic spreading scenarios at the global scale. BMC Infect. Dis. 11:37. 2011.

Khan, Arino, Hu, Raposo, Sears, Calderon, et al.: Spread of a novel influenza A (H1N1) virus via global airline transportation. N. Engl. J. Med. 361(2): 212–4. 2009.

Sander van Noort, De Grote Griepmeting/Gripenet

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1. Nursery school (crèche, Kindergarten)2. Brothers and sisters => primary schools3. Mothers (traditional role)4. Fathers (commuters)

How does seasonal flu spread?

Sander van Noort

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Seasonal flu as a winter disease

Lipid ordering may contribute to viral stability at lower temperatures which is critical for airborne transmission

Flu viruses survive longer and are more easily transmitted when humidity levels are low

Sander van Noort

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Hurricanes and monsoonsInfluenza activity appears to coincide with the rainy season in some tropical countries

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Do Earth’s seasons cause a “flu conveyor belt”?

Rambaut, Pybus, Nelson, Viboud, Taubenberger, Holmes:The genomic and epidemiological dynamics of human influenza A virus. Nature 453 (7195): 615–9. 2008.

Bahl, Nelson, Chan, et al. Temporally structured metapopulation dynamics and persistence of influenza A H3N2 virus in humans. Proc Natl. Acad Sci. USA 108(48):19359–64. 2011.

Page 57: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

• Influenza is quite likely to be under-reported in the tropics because there are so many other more serious diseases.

• Flu is often being mistaken for malaria in the tropics.

• Assumptions about the low impact of flu in the tropics may also be due to outbreaks which happen at unpredictable and irregular intervals.

• In most tropical countries collecting data is not easy.

Data on tropical influenza remain scarce!

Cécile Viboud, Wladimir J. Alonso, Lone Simonsen: Influenza in Tropical Regions. PLoS Medicine, March 7, 2006.

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“Highways’ in a global circulation pattern

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Portugal Belgium Netherlands

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Lisbon, February 2008 (Epi-Forecast)

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“A multidisciplinary research effort aimed at developing the appropriate framework of tools and knowledge needed for the design of epidemic forecast infrastructures to be used by epidemiologists and public health scientists.”

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Influenzanet.eu

2012/13

2013

Denmark, 2013

2013

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More than ILI alone

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Individual symptoms

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Vaccination uptake

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Risc groups

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Vaccine efficiency

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Side effects of the flu jab

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Where to focus next?

• Contact paternsMobile apps, Facebook, Twitter

• Swabs for virologySweden, Belgium 2012

• Survey: social and societal impacts of outbreaks of re-emerging infectious diseases (proposal phase)

• Cooperation with non-European countriesVS (Flu Near You), Australia (Flu Tracking)… Central America, Brasil, Asia, India, Africa

• One Health approachHuman (infectious) diseases, slow epidemics, zoonoses

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Flu app

Flu mobile app

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Flu app

Full medical apps Lab on a chip

Future technology

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International conferencesDigital Disease Detection I, Harvard Medical School, Boston, USA

International Workshop on Participatory Surveillance I, San Francisco, USA

Prince Mahidol Award Conference 2013, Bangkok, Thailand

4th International Meeting on Emerging Diseases and Surveillance - IMED 2013, Vienna, Austria

International Workshop on Participatory Surveillance II, Amsterdam, the Netherlands

WWW 2013 - Participatory Health in the Digital Age, Rio de Janeiro, Brasil

International Workshop on Digital Epidemiology, Torino, Italy

EPIHACK, Phnom Penh, Cambodia

Digital Disease Detection II, San Francisco, USA

Big Data and Public Health, Rio de Janeiro, Brasil

Page 74: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

International Workshop on Participatory Surveillance, July 2012

“I am thrilled! I’m witnessing the birth of a new science.

I foresee a whole new magazine, on self-reported participatory surveillance."

Larry Brilliant

Page 75: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

AMSTERDAM, 15-17 APRIL 2013

2nd International Workshop on Participatory Surveillance

2nd International Workshop on Participatory Surveillance (IWOPS 2), Amsterdam, April 2013

Influenzanet (EU) – Flu Near You (USA) – Flutracking (Australia)

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Platform for seasonal influenza

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Checklist for early signals of outbreaks

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AMSTERDAM, 15-17 APRIL 2013

2nd International Workshop on Participatory Surveillance

EPIHACK, Phnom Penh, August 2013

Page 79: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

AMSTERDAM, 15-17 APRIL 2013

2nd International Workshop on Participatory Surveillance

Doctor Me (Thailand)

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AMSTERDAM, 15-17 APRIL 2013

2nd International Workshop on Participatory Surveillance

Flu surveillance network organization

Page 81: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

Great Pneumonia Survey (GLM)

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GLM- Real Time Monitoring of Community Acquired Pneumonia

Week 1 2013

Week 2 2013

Week 3 2013

Week 4 2013

Page 83: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

GLM : Goals

Scientific goals:

• Early detection of abnormal repiratory infectious “outbreaks”• Measuring the impact of CAP in the Dutch population• Exploring seasonal influences on infectious respiratory disease• Exploring effect of pneumococcal vaccination on disease impact

Public information goal:

• Informing patients and health care workers on infectious respiratory disease

Page 84: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

GLM - Figures

• 24 Months online

• 1,724 unique participants

• 35 % female, 65% male• Mean age 66 yrs (SD 17)

• 13,000 measurements

Page 85: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

GLM – Take home messages

• Real time monitoring system for Community Acquired Pneumonia

• Possible tool for early detection of legionella and Q-fever

• Scientific analyses in progress: Publication of 1st results Dec. 2013

More info (Dutch): www.degrotelongontstekingmeting.nl

Page 86: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

GLM - Team

Carl KoppeschaarScience & content

Ronald SmallenburgFinance & organisation

Antwan WiersmaWebmaster & technical support

Dirk-Jan EnklaarAnalyses & reports

Advisory Board: Prof. Dr. Marc J.M. Bonten, Dr. Menno M. van der Eerden, Prof.dr. Jan C. Grutters, Dr. René E. Jonkers, Prof. Dr. Mattijs E. Numans, Prof. Dr. Jan M. Prins, Prof. Dr. Theo M.J. Verheij

Page 87: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses
Page 88: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

“Disease radar”

(Infectious) diseases & behaviour

1. Self diagnosis

2. Surveillance of pertussis and mumps (waning immunities), Lyme, hay fever, norovirus, Q fever, etc.

3. Stress related to labor, slow epidemics (obesity)

4. Medication and side effects

Page 89: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

Prediagnostic tool

(in close cooperation with the Dutch College of General Practitioners (NHG)

Lifestyle

Test yourself

Medical encyclopedia

Mobile app

Discussion forum

Top ten of health issues

Real time maps

Page 90: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

Also includes zoonoses

Over 60% of human pathogens originate from animals: influenza virus H5N1, H3N7, anthrax, SARS, HIV, leptospirosis, rabies, Lyme, Nipah virus, dengue, malaria, hantavirus, MERS coronavirus, …

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Lifestyle & Prevention

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Online Health Community

Robust system• Participatory

• Real time

• Geographic information

• Integrated

• Threat verification

• Early signal detection

Integrated:

National institute for Public Health

Community Health Services

College of General Practitioners

Ministry of Health

ProMed, HealthMap, CORDS

CDC, ECDC, WHO, FAO

With our Disease Radar we want to build an

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Threat verification (1)Measles in the Netherlands

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Threat verification (2)Mumps amongst students in the Netherlands

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Threat verification (3)Q fever in the Netherlands

> 4,000 sick

19 fatal

> 800 chronic

Retrospective analysis of hospital discharge data [van den Wijngaard et al. 2011 Epi. & Inf.] showed several plausible Q-fever clusters preceding the recognised beginning of the outbreak in 2007, 2006 and even in 2005, suggesting that had real-time syndromic surveillance been in place, the Q-fever clusters could have been detected up to two years earlier.

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Early signal detectionInfluenzanet.eu

Analysis:

Sander van Noort

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Compare with Google Flutrends

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Sustainability

• Government

• Pharmaceutical companies

• Advertising

• Grants

• Health insurance companies

• Foundations

Millions of insured persons

Economic crisis

Less money available for PR

Small money

Zoosurv in the Netherlands?

These could help a lot

Disease Radar could have been in operation more than a year ago should we have had the proper funding!

Page 99: Carl koppeschaar: Disease Radar: Measuring and Forecasting the Spread of Infectious Diseases and Zoonoses

References

R.L. Marquet, A.I.M. Bartelds, S.P. van Noort, C.E. Koppeschaar, J. Paget, F.G. Schellevis, J. van der Zee: Internet-based monitoring of influenza-like illness (ILI) in the general population of the Netherlands during influenza seasons 2003-2004, BMC Public Health 2006, 6:242.

S.P. van Noort, M. Muehlen, H. Rebelo de Andrade, C. Koppeschaar, J.M. Lima Lourenço, M.G.M. Gomes: Gripenet: an internet-based system to monitor influenza-like illness uniformly across Europe, Eurosurveillance, Volume 12, Issue 7-8, July/August, 2007.

IHM Friesema, CE Koppeschaar, GA Donker, F Dijkstra, SP van Noort, R Smallenburg, W van der Hoek, MAB van der Sande: Internet-based monitoring of influenza-like illness in the general population: experience of five influenza seasons in the Netherlands, Vaccine, Volume 27, Number 45, 23 October 2009, pp. 6353-6357. ISSN 0264-410X.

Sander P. van Noort, Ricardo Águas, Flávio Coelho, Cláudia Codeço, Daniela Paolotti, Carl E. Koppeschaar & M. Gabriela M. Gomes: Influenzanet: ILI trends, behaviour and risk factors in cohorts of internet volunteers, 2003 - 2013. In revision.

Marit M.A. de Lange, Adam Meijer, Ingrid H.M. Friesema, Gé A. Donker, Carl E. Koppeschaar, Wim van der Hoek: Comparison of five surveillance systems of influenza-like illness during the influenza A(H1N1)pdm09 virus pandemic and their link to media attention. BMC Public Health, 2013, 13:881 doi:10.1186/1471-2458-13-881.

Paolo Bajardi, Daniela Paolotti, Lorenzo Richiardi, Alessandro Vespignani, Sebastian Funk, Ken Eames, John Edmunds, Clement Turbelin, Marion Debin, Vittoria Colizza, Ronald Smallenburg, Carl Koppeschaar, Ana Franco, Vitor Faustino, Annasara Carnahan: Effect of recruitment methods on attrition in Internet-based studies. Submitted.

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Contact:

[email protected]