Bayesian estimation of Lassa virus epidemiological parameters: Implications for spillover prevention using wildlife vaccination.

ABSTRACT: Lassa virus is a significant burden on human health throughout its endemic region in West Africa, with most human infections the result of spillover from the primary rodent reservoir of the virus, the natal multimammate mouse, M. natalensis. Here we develop a Bayesian methodology for estimating epidemiological parameters of Lassa virus within its rodent reservoir and for generating probabilistic predictions for the efficacy of rodent vaccination programs. Our approach uses Approximate Bayesian Computation (ABC) to integrate mechanistic mathematical models, remotely-sensed precipitation data, and Lassa virus surveillance data from rodent populations. Using simulated data, we show that our method accurately estimates key model parameters, even when surveillance data are available from only a

SUBMITTER: Nuismer SL 

PROVIDER: S-EPMC7529244 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature