Systems to provide static spatially continuous maps of infectious disease risk and continually updated reports of infectious disease occurrence exist but to-date the two have never been combined.
Novel online data sources, such as social media, combined with epidemiologically relevant environmental information are valuable new data sources that can assist the “real-time” updating of spatial maps.
Advances in machine learning and the use of crowd sourcing open up the possibility of developing a continually updated atlas of infectious diseases.
Freely available dynamic infectious disease risk maps would be valuable to a wide range of health professionals from policy makers prioritizing limited resources to individual clinicians.
Hay SI, George DB, Moyes CL, Brownstein JS (2013) Big Data Opportunities for Global Infectious Disease Surveillance. PLoS Med 10(4): e1001413. http://dx.doi.org/10.1371/journal.pmed.1001413