Fewer people caught the flu this season compared with past years. And many more apps tracking the flu have been developed. Any relationship between these two trends?
Of course, less flu could be just the result of fewer mutations in bugs, warmer weather and more vaccinations. Yet the power of good software - such as google flu trends, twitter-based trackers and numerous apps can not be underestimated. Thanks to these tools, we are now more aware (and more afraid).
The flu is inherently social. "Nip the flu in the bud by spreading information, not germs, through the social network", says Flu Alert app. and lets you sort your friends by their flu exposures. Virtual flu in Fluville is promoting healthy habits by showing how flu can spread. Fluspotter let's you exchange warnings with your facebook friends, Flutracking reads your e-mails, while Influ takes your voice messages and shares it with users around the world. Biodisapora is tracking disease outbreaks by monitoring air travel. Sickweather scans Twitter and Facebook posts, and Germtrax lets you also sync with Foursquare and Google+ to geo-locate your wereabouts while being sick - with one of 6067 sicknesses available in their database.
According to multiple research studies, flu-related Internet searches, use of certain phrases on Twitter and Facebook posts peak 1-2 weeks earlier than the epidemic curve and align reasonably well with CDC data.
Social media is a noisy but powerful adjunct to surveillance systems based on official sources. It gives us an opportunity of contributing to the community's common good. It raises our awareness, but is not sufficient on its own. Many other factors increase our individual risks. Air travel. Or stress (haven't you noticed flu season in Greece was the worst in the world this year?) Age and food, too.
Aurametrix is a personal health analysis system that tackles this problem with an integrative approach. It aligns your medical history and historical CDC information with your food, mood and amount of sleep. It looks at all environmental predictions for today telling you if pollen, mold spores or air quality are more likely to be the reason for your symptoms, or if it is the rise in infectious diseases in your area. Aurametrix relies on a range of official sources and social media predictions. The data are constantly updated and refined, and causes linked with effects.
Of course, less flu could be just the result of fewer mutations in bugs, warmer weather and more vaccinations. Yet the power of good software - such as google flu trends, twitter-based trackers and numerous apps can not be underestimated. Thanks to these tools, we are now more aware (and more afraid).
The flu is inherently social. "Nip the flu in the bud by spreading information, not germs, through the social network", says Flu Alert app. and lets you sort your friends by their flu exposures. Virtual flu in Fluville is promoting healthy habits by showing how flu can spread. Fluspotter let's you exchange warnings with your facebook friends, Flutracking reads your e-mails, while Influ takes your voice messages and shares it with users around the world. Biodisapora is tracking disease outbreaks by monitoring air travel. Sickweather scans Twitter and Facebook posts, and Germtrax lets you also sync with Foursquare and Google+ to geo-locate your wereabouts while being sick - with one of 6067 sicknesses available in their database.
According to multiple research studies, flu-related Internet searches, use of certain phrases on Twitter and Facebook posts peak 1-2 weeks earlier than the epidemic curve and align reasonably well with CDC data.
Social media is a noisy but powerful adjunct to surveillance systems based on official sources. It gives us an opportunity of contributing to the community's common good. It raises our awareness, but is not sufficient on its own. Many other factors increase our individual risks. Air travel. Or stress (haven't you noticed flu season in Greece was the worst in the world this year?) Age and food, too.
Aurametrix is a personal health analysis system that tackles this problem with an integrative approach. It aligns your medical history and historical CDC information with your food, mood and amount of sleep. It looks at all environmental predictions for today telling you if pollen, mold spores or air quality are more likely to be the reason for your symptoms, or if it is the rise in infectious diseases in your area. Aurametrix relies on a range of official sources and social media predictions. The data are constantly updated and refined, and causes linked with effects.
REFERENCES
Dugas, A., Hsieh, Y., Levin, S., Pines, J., Mareiniss, D., Mohareb, A., Gaydos, C., Perl, T., & Rothman, R. (2012). Google Flu Trends: Correlation With Emergency Department Influenza Rates and Crowding Metrics Clinical Infectious Diseases, 54 (4), 463-469 DOI: 10.1093/cid/cir883
Manago, Adriana M., Taylor, T., Greenfield, P.M. Me and my 400 friends: The anatomy of college students' Facebook networks, their communication patterns, and well-being. (2012) Developmental Psychology, Jan 30. doi: 10.1037/a0026338
Signorini A, Segre AM, Polgreen PM. The use of Twitter to track levels of disease activity and public concern in the U.S. during the influenza A H1N1 pandemic. PLoS One. 2011 May 4;6(5):e19467. PMID: 21573238
Ginsberg J, et al. Detecting influenza epidemics using search engine query data. (2009) Nature 457, 1012–1014.
Ortiz JR, et al. Monitoring influenza activity in the United States: A comparison of traditional surveillance systems with Google Flu Trends. PLoS ONE 6(4):e18687. 2011.
Christakis NA, et al. Social network sensors for early detection of contagious outbreaks. PLoS ONE 5(9):e12948. 2010.
Malik MT, Gumel A, Thompson LH, Strome T, Mahmud SM. "Google flu trends" and emergency department triage data predicted the 2009 pandemic H1N1 waves in Manitoba. Can J Public Health. 2011 Jul-Aug;102(4):294-7. PMID: 21913587
Collier N, Son NT, Nguyen NM. OMG U got flu? Analysis of shared health messages for bio-surveillance. J Biomed Semantics. 2011 Oct 6;2 Suppl 5:S9. PMID: 22166368
Basak P. Development of an online tool for public health: the European Public Health Law Network.
Public Health. 2011 Sep;125(9):600-3. Epub 2011 Aug 23. PMID: 21864871
Chew C, Eysenbach G. Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak. PLoS One. 2010 Nov 29;5(11):e14118. PMID: 21124761
Scanfeld D, Scanfeld V, Larson EL. Dissemination of health information through social networks: twitter and antibiotics. Am J Infect Control. 2010 Apr;38(3):182-8. PMID: 20347636
Eysenbach G. Infodemiology and infoveillance: framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the Internet. J Med Internet Res. 2009 Mar 27;11(1):e11. PMID: 19329408
Signorini A, Segre AM, Polgreen PM. The use of Twitter to track levels of disease activity and public concern in the U.S. during the influenza A H1N1 pandemic. PLoS One. 2011 May 4;6(5):e19467. PMID: 21573238
Ginsberg J, et al. Detecting influenza epidemics using search engine query data. (2009) Nature 457, 1012–1014.
Ortiz JR, et al. Monitoring influenza activity in the United States: A comparison of traditional surveillance systems with Google Flu Trends. PLoS ONE 6(4):e18687. 2011.
Christakis NA, et al. Social network sensors for early detection of contagious outbreaks. PLoS ONE 5(9):e12948. 2010.
Malik MT, Gumel A, Thompson LH, Strome T, Mahmud SM. "Google flu trends" and emergency department triage data predicted the 2009 pandemic H1N1 waves in Manitoba. Can J Public Health. 2011 Jul-Aug;102(4):294-7. PMID: 21913587
Collier N, Son NT, Nguyen NM. OMG U got flu? Analysis of shared health messages for bio-surveillance. J Biomed Semantics. 2011 Oct 6;2 Suppl 5:S9. PMID: 22166368
Basak P. Development of an online tool for public health: the European Public Health Law Network.
Public Health. 2011 Sep;125(9):600-3. Epub 2011 Aug 23. PMID: 21864871
Chew C, Eysenbach G. Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak. PLoS One. 2010 Nov 29;5(11):e14118. PMID: 21124761
Scanfeld D, Scanfeld V, Larson EL. Dissemination of health information through social networks: twitter and antibiotics. Am J Infect Control. 2010 Apr;38(3):182-8. PMID: 20347636
Eysenbach G. Infodemiology and infoveillance: framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the Internet. J Med Internet Res. 2009 Mar 27;11(1):e11. PMID: 19329408
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