Bayesian spatio-temporal modelling of tuberculosis in Vietnam: Insights from a local-area analysis.

ABSTRACT: Spatial analysis and disease mapping have the potential to enhance understanding of tuberculosis (TB) dynamics, whose spatial dynamics may be complicated by the mix of short and long-range transmission and long latency periods. TB notifications in Nam Dinh Province for individuals aged 15 and older from 2013 to 2022 were analyzed with a variety of spatio-temporal methods. The study commenced with an analysis of spatial autocorrelation to identify clustering patterns, followed by the evaluation of several candidate Bayesian spatio-temporal models. These models varied from simple assessments of spatial heterogeneity to more complex configurations incorporating covariates and interactions. The findings highlighted a peak in the TB notification rate in 2017, with 98 cases per 100,000 populatio

SUBMITTER: Bui LV 

PROVIDER: S-EPMC11869078 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature