Newsflash

April 2012 - The National Institute of General Medical Sciences awarded R01 funding to Drs. Wagner and Hogan to develop a standard computable language for the Apollo Web Services.

 
Reference Details
Jiang, X., Wallstrom, G., Cooper, G. F. and Wagner, M. M. (2009), "Bayesian prediction of an epidemic curve", J Biomed Inform, 42: 90--99.

Abstract:
An epidemic curve is a graph in which the number of new cases of an outbreak disease is plotted against time. Epidemic curves are ordinarily constructed after the disease outbreak is over. However, a good estimate of the epidemic curve early in an outbreak would be invaluable to health care officials. Currently, techniques for predicting the severity of an outbreak are very limited. As far as predicting the number of future cases, ordinarily epidemiologists simply make an educated guess as to how many people might become affected. We develop a model for estimating an epidemic curve early in an outbreak, and we show results of experiments testing its accuracy.
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