Collaborative Platforms for Disease Surveillance · Mapping West Nile Virus risk: ... Yellow Fever....

John Brownstein, PhDAssociate Professor

Children’s Hospital Boston, Harvard Medical School@johnbrownstein

Collaborative Platforms for Disease Surveillance

2nd Annual ESRI Health GIS Conference

May 2003Arlington, VA

Mapping West Nile Virus risk: Evaluating surveillance and environmental Data

Emerging and re‐emerging infections, 1996‐2010

Venezuelan Equine EncephalitisDengue Haemorrhagic Fever

CryptosporidiosisHuman MonkeypoxE.Coli O157

nvCJD

Ebola Haemorrhagic FeverMarburg Haemorrhagic FeverRoss River VirusHendra VirusReston Virus

West Nile VirusLegionnaire’s DiseaseSevere Acute Respiratory 

Syndrome (SARS)MalariaTyphoidCholeraBSELassa FeverYellow Fever

Lyme BorreliosisEchinococcosisDiphtheriaInfluenza A (H5N1)Nipah VirusRVF/VHFO’Nyong‐Nyong FeverBuruli UlcerMultidrug Resistant Salmonella

Outbreak Database (1996‐2009)

• Disease / Location• Date of onset of risk factor• Date of local mass gathering• Date of associated wildlife 

outbreak• Date of exposure• Date of symptom onset• Date of outbreak start• Date of hospitalization or 

medical visit• Date of outbreak detection• Date of death

• Date of laboratory confirmation 

• Date of announcement by a local 

• Date of any earlier mentioned report

• Date of ProMED, GPHIN, HealthMapreports

• Date of WHO notification

• Date of DON report (official)

• Date of mass immunization campaign

• Date of implementation of vector control)

• Date of declaration of an epidemic raised

• Date of declaration of end of epidemic

Δt2

Characterize global spatial‐temporal trends in the timeliness of outbreak detection and reporting

Outbreakstart

Δt1

Outbreakdiscovery

Publiccommunication

Global Surveillance Capacity Assessment

48 days (95% C.I. [40;56])

35 days (95% C.I. [32;47])

32 days (95% C.I. [28;38.5])

23 days (95% C.I. [18;30])

MEDIAN

Figure 2 . Boxplots of the median time (and inter‐quartile range) between outbreak start and various outbreak “milestones” for a set of WHO‐confirmed outbreaks during 1996‐2009. 

Chan et al. 2010. Proceedings of the National Academy of Sciences.

World Bodies

(UN, WHO, FAO, OIE)

5

Ministry of 

Health

4

Local Officials

Labs

3

Public health

practitioners

Healthcare workers,Clinicians

2

Public

1

Traditional Public Health Reporting

Public

1

Public health

practitioners

Healthcare workers,Clinicians

2

Local Officials

Labs

3

Ministry of 

Health

4

World Bodies

(UN, WHO, FAO, OIE)

5

World Bodies

(UN, WHO, FAO, OIE)

Ministry of 

Health

Local Officials

Labs

Public health

practitioners

Healthcare workers,Clinicians

Public

Traditional Public Health Reporting

54321

Digital Disease

DetectionWorld Bodies

(UN, WHO, FAO, OIE)

5

epidemic curve

Potential of Digital Disease Detection

SMS Messaging

Micro Blogging

Emailing

Internet Searching

Social Networking

Internet Chatting

Blogging

Online News Reporting

Video/Radio Reporting

Health Expert Reporting

0

50

100

150

200

1996 2000 2004 2008

Number of days from outbreak start to outbreak discovery

Year of Outbreak Start

Time in Day

s

20in 2010

days

167in 1996

days

Chan et al. 2010. Proceedings of the National Academy of Sciences.

The Rise of Digital Disease Detection

1st  infectious disease social network

1st  infectious disease web crawler

precisely placed in

locations

resulting in

alerts per day

the number of public and private sources we useto access more than 50,000 sites

in 10languagesevery hour

24/7

Typhoid  cases  in  Mufulira have  

reached  2, 227  with  health  authorities  

calling  for  increased  efforts  to  prevent  

new  infections  in  Mupambe Township.

Articles are scanned for key information usingnatural language processing

MufuliraTyphoid

MupambeTownship

2, 227

#

4800disease patterns

10,500locations

#Case and Death Counts

species220

Old News

Context

Not disease related

Breaking News

Warning

Articles are categorized using more than 19 million phrases

BayesianFiltering

91% accuracy

with

Breaking News

Warning

Text matching, similarity score, and rating value determine the significance of the alert

Old News

Context

Not disease related

Articles are categorized using more than 19 million phrases

BayesianFiltering

91% accuracy

with

Global spread of H1N1 with informal sources

Brownstein et al. 2010. New England Journal of Medicine.

Number of foodborne illnesses reported each year in the US

By the Centers for Disease Control and Prevention

By HealthMap

1000

10,000

Foodborne Outbreaks Reported to HealthMap in past year

Professional social networks to support disease reporting

Human networks has proven value

Professional networks play key roles in discovery and validation

2 Examples:ProMED ISIDGeoSentinel ISTM

Professional Networks and Epidemic Intelligence

Collaborations

Automated ExtractionAutomated Feed

Community Input 

Added Value(1) Discovery of new content(2) Provides two‐way contextualization(3) Validation studies

Next Generation Public Health: Participatory Epidemiology

HealthMapOutbreaks Near Me

reporting

> 100k downloads

AndroidPotential for increased global coverage

HealthMap Hotline

919‐MAP‐1‐BUG (627‐1284)Leave a voicemail or Send SMS

Reporting through the website

worldwide user submitted reports

Chikungunya in India – July 22, 2011

• A London‐based doctor reported via HealthMap’s“Outbreaks Near Me” mobile application that his family in Jamshedpur, Jharkhand, India was ill with Chikungunya

• Report went on to say that local hospitals were full, and that the MOH was not reporting cases or providing information on prevention or treatment 

• HM was able to enhance surveillance capabilities for this disease and location, and provide users with this information earlier than any other source

iPhone Submissions vs CDC sentinel surveillance

CDC Sentinel Physician Network (%ILI)Outbreaks Near Me iPhone app (%H1N1 submissions/Downloads)

R2=0.74

Future of Outbreaks Near Me Mobile

Engaging the users throughrecognition

Providing key public healthmessaging

Improved visualization 

And building a disease detectivenetwork…

Undiagnosed Events in HealthMap

Validating Undiagnosed Events by Mobile Phone

Validating Undiagnosed Events by Mobile Phone

Geo‐localized push messages  Validate event

New Applications of Digital Disease Detection

CDC Yellow Book: Dengue

2011 Yellow Book

2008 Yellow Book Risk Areas2011 Yellow Book Risk Areas

2011 Yellow Book

Model Performance

Cholera Surveillance in Haiti

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HealthMap Pilot, Haiti

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Oct-20 Nov-17 Dec-22 Jan-19 Feb-16

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Chunara et al. 2012. American Journal of TropicalMedicine and Hygiene.

Using Social Media to Build an Epidemic Curve

Estimate Reproductive Number (R0)

Phase 1: Informal sources 1.54‐6.89 compared to official sources 1.27‐3.72Phase 2: Informal sources 1.04‐1.51 compared to official sources 1.06‐1.73

Case counts Hospitalizations HealthMap Twitter

Chunara et al. 2012. American Journal of TropicalMedicine and Hygiene.

New Directions in Participatory Systems

Mechanical Turk

www.mturk.com

India Malaria HIT

flunearyou.org

Registration

Facebook integration

Form after illness indication

IndividualTop Awards

GroupTop Awards

Awarded to top three individuals withhighest total number person‐forms

Minimum Threshold eligibility:10,000 person‐forms

(one form allowed per person per week)

Awarded to top three groups withhighest total number person‐forms 

divided by number of persons in group

Minimum Threshold eligibility:100,000 person‐forms

(one form allowed per person per week)

APHA                                   Challenge

Age Distributions

Users Household members

Linking Surveillance with Prevention:HealthMap Flu Vaccine Finder

HealthMap Flu Vaccine Finder

Collaboration of over 50,000 pharmacies

Global Official Surveillance Platforms

Ministry of Health Mapping

Automated mining/mapping of over 500 MOH data feeds

Conclusions

• Value in the fusion and visualization of distributed electronic resources (online epidemic intelligence, social networks, mobile technology)

• Novel Internet‐based collaborative systems can play an important complementary role in gathering information quickly and improving coverage and accessibility.

• These early efforts at tapping the power of digital tools demonstrate important steps in improving health systems as well as engaging the public as participants in the public health process. 

HealthMap Team

• Clark Freifeld, MA• David Scales, MD PhD• Susan Aman• Leila Amerling, MBA• Emily Chan, MSc• Rumi Chunara, PhD• Annie Gatwood, PhD• Mikaela Keller, PhD• Sumiko Mekaru, DVM, MVM• Katelynn O'Brien• Amy Sonricker, MPH

77

Funding

Questions?

john_brownstein@harvard.eduwww.healthmap.org

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