Spatiotemporal analysis of tuberculosis incidence and its associated factors in mainland China

Abstract

Spatiotemporal analysis is an important tool to monitor changes of tuberculosis (TB) epidemiology, identify high-risk regions and guide resource allocation. However, there are limited data on the contributing factors of TB incidence. This study aimed to investigate the spatiotemporal pattern of TB incidence and its associated factors in mainland China during 2005-2013. Global Moran's I test, Getis-Ord Gi index and heat maps were used to examine the spatial clustering and seasonal patterns. Generalized Linear Mixed Model was applied to identify factors associated with TB incidence. TB incidence presented high geographical variations with two main hot spots, while a generally consistent seasonal pattern was observed with a peak in late winter. Furthermore, we found province-level TB incidence increased with the proportion of the elderly but decreased with Gross Demographic Product per capita and the male:female ratio. Meteorological factors also influenced TB incidence. TB showed obvious spatial clustering in mainland China and both the demographic and socio-economic factors and meteorological measures were associated with TB incidence. These results provide the related information to identify the high-risk districts and the evidence for the government to develop corresponding control measures.