Bayesian prediction of an epidemic curve

Xia Jiang, Garrick Wallstrom, Gregory F. Cooper, Michael M. Wagner

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)90-99
Number of pages10
JournalJournal of Biomedical Informatics
Volume42
Issue number1
DOIs
StatePublished - Feb 2009

Keywords

  • Bayesian network
  • Biosurveillance
  • Disease surveillance
  • Epidemic curve

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

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