Bayesian approach in modelling cholera outbreak in Ilala municipal council, Tanzania

Abstract

In this paper, we consider a deterministic susceptible-infected-removed-bacteria (SIR-B) cholera epidemic model with water treatment as a control strategy. The infected compartments are divided into two classes namely; symptomatic infected and asymptomatic infected individuals in order to observe the contribution of vibrio cholerae to the environment from each compartment. The main objective of this paper is to validate the model using Ilala municipal council data. We estimate the model parameters using least square and Bayesian approach via Markov chain Monte Carlo (MCMC) methods. The sample of 10,000 number of simulations was carried out in MCMC run to study the behaviour of each parameter in the proposed model. The results show that the parameters have good convergence, the dynamic behaviour of prediction fits the observed data.