Seminar Details

Seminar Details


Thursday

Sep 6

2:30 pm

Analyzing Time Series Data for Endemic Cholera in Bangladesh with Mechanistic Models of Infectious Disease Dynamics

Amanda Allen

General Exam

University of Washington - Statistics

Despite seasonal cholera outbreaks in Bangladesh, little is known
about the relationship between environmental conditions and cholera
cases. We seek to develop a predictive model for cholera outbreaks
in Bangladesh based on environmental predictors. To do this, we must
estimate the environmental parameters in the context of a disease
transmission model. We develop a method to simultaneously estimate
the transmission parameters and the environmental parameters in a
Susceptible-Infectious-Recovered-Susceptible (SIRS) model. The
entire system is treated as a continuous-time hidden Markov model,
where the unobserved Markov states are the numbers of people who are
susceptible, infected, and recovered at each time point, and the
observed states are the number of cholera cases reported. We use a
Bayesian framework to fit this hidden SIRS model, implementing
particle Markov chain Monte Carlo (MCMC) methods to sample from the
posterior distribution of the environmental and transmission
parameters given the observed data. We test this method using both
simulated data and data from Bakerganj, Bangladesh.