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The Probability and Duration of Epidemics in Stochastic Multistage or Multigroup Models

Wednesday, June 6, 2018 - 10:00am - 10:50am
Lind 305
Linda Allen (Texas Tech University)
Public health prevention, intervention, and control strategies are designed to prevent the occurrence of an epidemic, to shorten the course of an epidemic, or to reduce the number of cases. To prevent an epidemic, the goal is often to decrease the basic reproduction number R0 to a value below the critical threshold of one. In emerging and re-emerging diseases, differences in host susceptibility and infectivity make it more difficult to assess how intervention and control strategies affect R0, and the probability and duration of an epidemic. In this investigation, we review some results on probability and duration in simple epidemic settings and extend some of these results to the case of stochastic multistage and multigroup models. Methods from Markov chain and multitype branching process theory are applied. Implications for public health control are discussed.