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In Silico Surveillance: Evaluating Outbreak Detection With Simulation Models, Bryan Lewis, Stephen Eubank, Allyson M. Abrams, Ken Kleinman
In Silico Surveillance: Evaluating Outbreak Detection With Simulation Models, Bryan Lewis, Stephen Eubank, Allyson M. Abrams, Ken Kleinman
Public Health Department Faculty Publication Series
Background
Detecting outbreaks is a crucial task for public health officials, yet gaps remain in the systematic evaluation of outbreak detection protocols. The authors’ objectives were to design, implement, and test a flexible methodology for generating detailed synthetic surveillance data that provides realistic geographical and temporal clustering of cases and use to evaluate outbreak detection protocols.
Methods
A detailed representation of the Boston area was constructed, based on data about individuals, locations, and activity patterns. Influenza-like illness (ILI) transmission was simulated, producing 100 years ofin silico ILI data. Six different surveillance systems were designed and developed using gathered cases …