A Bayesian spatiotemporal autoregressive model with constant and temporally varying coefficients: an application to hotspot detection of childhood tuberculosis in Bandung City, Indonesia

Abstract

The health reported data shows that the risk of tuberculosis among children aged 0-14 years is still a significant health problem in developing countries such as Indonesia in terms of case detection, control, and effective treatment. However, some information is available about the burden of tuberculosis and its risk factors (e.g., malnutrition, population density, healthy behaviours, and AFB smear-positive tuberculosis) which can be very useful. This study aimed to identify the hotspot of tuberculosis among children aged 0-14 years in Bandung city, Indonesia. Using Bandung health profile database of tuberculosis notification for 2016 – 2018, we estimated the burden of tuberculosis among children aged 0-14 years by districts. We estimate that incidence rates vary over space and time, with the hotspots centred in the western and central regions of Bandung city. Population density has a significant effect on burden tuberculosis among aged 0-14 years over districts.