FluTE, a Publicly Available Stochastic Influenza Epidemic Simulation Model

• Published in: PLoS computational biology Vol. 6; no. 1; p. e1000656
• Main Authors: Chao, Dennis L., Halloran, M. Elizabeth, Obenchain, Valerie J., Longini, Ira M.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.01.2010; Public Library of Science (PLoS)
• Subjects: Censuses; Community; Computational Biology; Computer Simulation; Computer-generated environments; Control; Disease Outbreaks; Epidemics; Households; Humans; Infectious Diseases/Epidemiology and Control of Infectious Diseases; Influenza; Influenza, Human - transmission; Intervention; Methods; Models, Biological; Pandemics; Personal computers; Population; Prevalence; Public Health and Epidemiology/Epidemiology; Public Health and Epidemiology/Infectious Diseases; Public policy; Software; Stochastic models; Stochastic Processes; Studies; United States; United States; Prevalence; Stochastic Processes; Disease Outbreaks; Models, Biological; United States; Computer Simulation; Humans; Influenza, Human; Software
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1000656

Mathematical and computer models of epidemics have contributed to our understanding of the spread of infectious disease and the measures needed to contain or mitigate them. To help prepare for future influenza seasonal epidemics or pandemics, we developed a new stochastic model of the spread of influenza across a large population. Individuals in this model have realistic social contact networks, and transmission and infections are based on the current state of knowledge of the natural history of influenza. The model has been calibrated so that outcomes are consistent with the 1957/1958 Asian A(H2N2) and 2009 pandemic A(H1N1) influenza viruses. We present examples of how this model can be used to study the dynamics of influenza epidemics in the United States and simulate how to mitigate or delay them using pharmaceutical interventions and social distancing measures. Computer simulation models play an essential role in informing public policy and evaluating pandemic preparedness plans. We have made the source code of this model publicly available to encourage its use and further development.