Tracking A(H1N1) using Riff

Last week, InSTEDD's CEO; Dr. Eric Rasmussen, blogged about the Riff workspace we stood up earlier to further aid experts and responders collaborating around emerging reports related to the 2009 A(H1N1) pandemic influenza. To-date, there's been massive news coverage around the event, but in order to make sense of it all, a group of experts (with a backgrounds in public health, international relations, diplomacy, social work, and emergency response) volunteered their time to collaborate around the various streams of information (listed below).



One by-product of this ongoing effort is that the information is appropriately tagged and geo-located. The A(H1N1) workspace allows you to subscribe to all the information or to a filter of your own. The tags include information beyond just a disease category, symptom, or syndrome, but we also tried to capture other important information; such as policy issues (e.g., vaccination, school closure, travel advisory, etc.). However, our primary goal is not to become another information source, rather to be able to provide a good situational awareness of the event in order to respond effectively. We are trying to address the following problems that are inherent in the current early detection systems:

• Classic problem: too much data, not enough information. Why aren’t the key indicators noticed earlier?
• Noisy data—low reliability—
• Need to keep the human in the loop (a lot of this is still an art).
• Sources not always obvious - we saw emerging sources of information, like the citizen reporting over a Google map (in the past much attention was paid to sources like Internet search queries (e.g., Eysenbach, Ginsberg, Polgreen, Hulth, and Cooper), over the counter medications sales (e.g., Wagner/RODS Lab), absenteeism (e.g., Wagner/RODS Lab), as opposed to ER chief complaints or routine disease surveillance hierarchical systems).
• Threat profile keeps changing- is not known for something like a SARS/SARI (e.g., Swine Flu or other things like it).
• Political and Organizational Boundaries (Note that we weren't able to perfectly communicate the first indications of SARS, or the outbreaks of H5N1 in China, and we saw that happen again with the H1N1 Swine outbreak).
  
• Need to set up the need for shared collaboration spaces and geographic distribution. Not only do we need human experts in the loop, but they need to share the hunches and concerns. Discussion needs to identify communities of interest. Different specialists are involved based on the nature of the threat.

I particularly applaud the effort by HealthMappers (Dr. Brownstein, et al) for quickly putting together an A(H1N1) mashup (or the New England Journal of Medicine HealthMap) which tracks the cases (confirmed, suspect, dead, or ruled out) alongside with the informal sources that HealthMap continuously monitors and moderates. HealthMap and BioCaster also setup moderated tweets on Twitter that are timely, reliable and of high quality.

Information Sources:

1. EISS Weekly Electronic Bulletin
2. Canada - FluWatch
3. USA - Centers for Disease Control and Prevention - FluView
   
4. Health Information for International Travel The Yellow Book
5. Moreover Public Health News
6. BBC Outbreak News
7. WHO Outbreak News
8. CDC Flu Updates
9. WHO Latest news on the avian influenza situation in humans around the world
10. EID Podcasts
11. EID Journal
12. Recent Outbreaks and Incidents
13. CDC Emergency Preparedness & Response
14. Google Outbreak News
15. Flu Stop with CDC
16. ProMED Mail (including ProMED MBDS)
17. FDA Twitter Feed
18. CDC MMWR
19. Eurosurveillance
20. Clinician Outreach and Communication Activity
21. Y! Health Cold & Flu News
22. CNN Health News
23. VitalStats
24. HEDDS Surveillance News
25. CDC en Español
26. Public Health Matters
27. WDIN Disease Map Digest
28. CDC Travel Notices
29. Citizen reporting using Google Map
30. Various Twitter feeds (including HealthMap, BioCaster, EpiSpider, and Veratect)
31. Google Insights for Search
    

The Challenge Ahead:

While all this is important, I'd like to emphasize the fact that the best data is still coming from old-fashioned shoe leather epidemiology. We have to be true to ourselves and remember that, with all the information, new tools, open networks of collaborators, etc., we still missed the early indication(s) of the A(H1N1) outbreak. I remember when I was in the trenches of SARS back in 2003, we didn't have the breadth and depth of the information nor the tools we currently have. This calls for an action to rethink our strategies around early detection especially for emerging infectious diseases...

Related Links:

• Low volume Riff announcements on Twitter
• Extremely Affordable Health Innovations
  
• MBDS ICT and Technology Forum
  
• Best Poster Award for Improving Public Health Investigation and Response at the Seventh Annual International Society for Disease Surveillance Conference
• Collaborative Analytics and Environment for Linking Early Event Detection to an Effective Response