The HealthMap team recently published Information Technology and Global Surveillance of Cases of 2009 H1N1 Influenza in the New England Journal of Medicine (NEJM). The online paper includes three interactive figures* and demonstrates how informal data can be used to understand epidemiological trends of infectious diseases. (*Figure 1shows the worldwide spread of the H1N1 virus,Figure 2shows a timeline of informal reporting of cases worldwide, and Figure 3 shows the relationship between GDP and time lag between suspected and confirmed case reports)
During the 2009 H1N1 influenza pandemic, nontraditional surveillance sources such as Internet news sources provided new public health data. Collectively, these sources overcame certain limitations of traditional surveillance systems, including reporting delays, inconsistent population coverage, and a poor sensitivity to detect emerging diseases. In May 2009, in collaboration with NEJM and as part of the NEJM’s H1N1 Influenza Center (http://h1n1.nejm.org), HealthMap created an H1N1 interactive map (available at www.healthmap.org/nejm) displaying these reports to enhance the situational awareness of public health professionals, clinicians, and the general public regarding the global spread of 2009 H1N1 influenza infection. Visitors to the site could filter reports according to suspected or confirmed cases or deaths and view a chosen time interval to show the spread of disease. During the two major waves of the H1N1 pandemic, HealthMap collected more than 87,000 reports from both informal and official sources (43,738 reports during the first wave of infection, from April 1 to August 29, 2009, and 43,366 reports during the second wave of infection, from August 30 to December 31, 2009). These reports formed the dataset used in the analyses of this latest paper.
Overall, the 2009 H1N1 influenza pandemic presented an important test of new disease-surveillance systems. The use of data that were collected, coded, and analyzed through the NEJM’s HealthMap system shows how such systems, which were built largely around readily available informal sources, can provide both early warnings and an ongoing operating picture of the patterns of disease spread.
Citation for the publication can be found here.
