The research, funded by NIH’s National Institute of Allergy and Infectious Diseases, aims to develop statistical techniques to integrate data from multiple surveillance systems to detect infectious diseases. The researchers will also develop algorithms to predict how surveillance systems perform.
Project leader Justin Remais, PhD — an environmental health sciences associate professor at UC Berkeley School of Public Health — will collaborate with statisticians and epidemiologists from Emory University in Atlanta, the University of Florida in Gainesville and the Beijing Institute for Microbiology and Epidemiology.
The researchers will focus on detecting outbreaks, tracking infections and supporting disease control efforts related to tuberculosis, malaria and schistosomiasis.
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