Spatio-temporal dengue risk modelling in the south of Thailand: a Bayesian approach to dengue vulnerability.

ABSTRACT:

Background

More than half of the global population is predicted to be living in areas susceptible to dengue transmission with the vast majority in Asia. Dengue fever is of public health concern, particularly in the southern region of Thailand due to favourable environmental factors for its spread. The risk of dengue infection at the population level varies in time and space among sub-populations thus, it is important to study the risk of infection considering spatio-temporal variation.

Methods

This study presents a joint spatio-temporal epidemiological model in a Bayesian setting using Markov chain Monte Carlo (MCMC) simulation with the CARBayesST package of R software. For this purpose, monthly dengue records by district from 2002 to 2018 from the southern region of Thailan

SUBMITTER: Abdulsalam FI 

PROVIDER: S-EPMC10351518 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature