Estimation of the relationship between meteorological factors and measles using spatiotemporal Bayesian model in Shandong Province, China.

ABSTRACT:

Background

Measles-containing vaccine (MCV) has been effective in controlling the spread of measles. Some countries have declared measles elimination. But recently years, the number of cases worldwide has increased, posing a challenge to the global goal of measles eradication. This study estimated the relationship between meteorological factors and measles using spatiotemporal Bayesian model, aiming to provide scientific evidence for public health policy to eliminate measles.

Methods

Descriptive statistical analysis was performed on monthly data of measles and meteorological variables in 136 counties of Shandong Province from 2009 to 2017. Spatiotemporal Bayesian model was used to estimate the effects of meteorological factors on measles, and to evaluate measles risk areas a

SUBMITTER: Jia Y 

PROVIDER: S-EPMC10369697 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature