|Date:||Thursday, October 25, 2018|
Epidemics of infectious pathogens of humans go through several stages. First comes an initial "stochastic" phase, during which case counts remain low and vary apparently at random. This initial phase is followed by a period of exponential growth of the number of new cases per unit time (the incidence). As more and more individuals become infected, the number of susceptible individuals in the population decreases; incidence consequently goes through a plateau then starts to decrease, a characteristic of the final stage of the epidemic, which typically concludes with the extinction or near extinction of the outbreak.
In this work, we focus on the initial stochastic phase of the epidemic, which, contrary to later stages, is badly captured by deterministic models. We consider a very simple random walk on the number of infectious individuals in the population, allowing us to obtain estimates of the duration of the stochastic phase. We then extend the model to two connected spatial locations.
This is joint work with Jason Rose (University of Manitoba) and Evan Milliken (Arizona State University).
December 10 – December 21: Fall Term Exam Period
December 22 – January 2: Winter Holiday (University Closed)
Statistics seminar: Erfan Houqe: “Random effects covariance matrix modeling for longitudinal data with covariates measurement error” — Thursday, January 17 at 2:45 p.m., P230 Duff Roblin.