Global infectious disease surveillance through automated multi lingual georeferencing of Internet media reports

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1 Global infectious disease surveillance through automated multi lingual georeferencing of Internet media reports John S. Brownstein, PhD Harvard Medical School Children s Hospital Informatics Program Harvard MIT Division of Health Sciences and Technology

2 Healthcare Surveillance AEGIS AEGIS INFLUENZA

3 Structured Clinical Surveillance Unstructured Web Surveillance Lack of infrastructure Low level training Gaps in coverage Poor information flow Abundant cheap/free resource Detailed local information Near real time reporting Less susceptible to political pressure

4 Progression of outbreak Early reporting of SARS Cases of atypical pneumonia Foshan Nov 16th 305 Cases of acute resp Guangdong Province Feb 11th Infected Chinese Doctor Hong Kong hotel Feb 21st Nov 2002 Mar 2003 Electronic Surveillance Pharma report Guangdong Province November 27 Media reports Guangdong Province Feb 10 Astute physician on ProMED Feb 10 Official WHO Report March 10 Initial WHO Report Feb 25

5 Source of outbreak news verified by WHO Adapted from Heymann 2001

6 Limitations of internet based surveillance Abundance of disparate electronic resources but none comprehensive Information is unstructured free text Difficulty in georeferencing of information sources No synthesized view of the current state of global health Brownstein et al. Institute of Medicine

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8 Healthmap Objectives Enhance surveillance of infectious diseases through integration Multi stream real time web based surveillance system Alert aggregator news wire, web sites, RRS feeds, mailing lists Automated multi lingual searching, categorization, filtering, georeferencing Achieve unified and comprehensive view of global health Space and time mapping Easy information access Limit information overload filter and duplicate removal Free and open multi lingual mapping resource Open source technologies combined with Open API systems Linux, Apache, MySQL,, PHP, Google Maps Brownstein et al. Institute of Medicine

9 Public Health Resource

10 Tool for general population

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12 HealthMap Article Processing ACQUIRING CATEGORIZING CLUSTERING FILTERING >20,000 sites Every hour; 24/ disease patterns 5000 location patterns Text Matching Similarity Score >3 million keywords 94% accuracy

13 UK 12 united kingdom 12 united states 13 united arab emirates 14 Georeferencing UK united Each node is a hashtable. Each key maps an input token either to an ID or another node. 12 kingdom states arab emirates As we process the input token by token, we traverse the tree accordingly. 14

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21 Early Stats > 200 alerts per day 60,000 alerts so far Alerts in 201 countries 169 pathogens 4 four languages English (60%) Spanish (20%) French (11%) Russsian (9%)

22 201 Countries with alarms 1 USA: UK: Canada: China:737 Geographic Representation

23 Multi lingual Surveillance

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25 Coverage Comparison: Argentina English News Bovine Anthrax Citrus Canker

26 Coverage Comparison: Argentina Spanish News Trichinosis Bronchiolitis Rotavirus Influenza

27 Georeferencing errors can occur No known pattern given in input Location given, wrong match London, Georgia Non location pattern matched Antarctica the horse Correct location, but too general Russia vs. Stavropol Krai

28 Georeferencing accuracy 1774 alerts processed 134 location edited (7.6%) 24% 47% Updates Inserts Deletes 29%

29 The dictionary approach provides us with a labeled corpus: Dictionary Approach Expansion Health authorities in New Caledonia are closely monitoring an upsurge of dengue fever cases

30 The dictionary approach provides us with a labeled corpus: Dictionary Approach Expansion Health authorities in New Caledonia are closely monitoring an upsurge of dengue fever cases

31 The dictionary approach provides us with a labeled corpus: Dictionary Approach Expansion Health authorities in New Caledonia are closely monitoring an upsurge of dengue fever cases NNP NNS IN NNP VBP RB VBG DT NN IN NN NNS Expansion: Learn the syntactic/lexical context in which locations & diseases occur

32 The dictionary approach provides us with a labeled corpus: Dictionary Approach Expansion Health authorities in New Caledonia are closely monitoring an upsurge of dengue fever cases NNP NNS IN NNP VBP RB VBG DT NN IN NN NNS Expansion: Learn the syntactic/lexical context in which locations & diseases occur Predict new locations & diseases: Health authorities in California are closely monitoring an upsurge of salmonella cases

33 Collaborative Georeferencing Networks ProMED of the International Society for Infectious Diseases (specialty moderators; full 40,000 members) Emerging Infections Network (EIN) of the Infectious Disease Society of America (982 ID consultants) US Naval Medical Research Center Detachment of DOD GEIS in Peru (Spanish and Portuguese moderation)

34 Conclusions Internet based disease mapping offers a promising multi use tool Value in visualization of distributed electronic resources Georeferencing still presents formidable challenges Higher resolution mapping Limiting misclassifications Multi lingual location identification

35 Children s Hospital Informatics Harvard MIT HST Clark Freifeld Mikaela Keller, PhD Ken Mandl, MD MPH Ben Reis, PhD Isaac Kohane, MD PhD Larry Madoff (ProMED) David Blazes (Peru NMRCD) Aranka Anema (UBC) Acknowledgments Funding Google Foundation National Library of Medicine (NLM) Centers for Disease Control and Prevention Canadian Institutes of Health Research (CIHR)

36 Contact