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bioRxiv · 10.1101/348169

Detecting spatiotemporal pattern of tuberculosis and the relationship between ecological environment and tuberculosis, a spatial panel data analysis in Guangxi, China

CUI, Z.·Lin, D.·Chongsuvivatwong, V.·Zhao, J.·Lin, M.·Ou, J.
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Abstract

Guangxi is one of the provinces having the highest reported incidence of tuberculosis (TB) in China. However, spatial and temporal pattern and causation of the situation are still unclear. In order to detect the spatiotemporal pattern of TB and the association with ecological environment factors in Guangxi Zhuang autonomous region, China, We performed a spatiotemporal analysis with prediction using time series analysis, Morans I global and local spatial autocorrelation statistics, and space-time scan statistics, to detect temporal and spatial clusters. Spatial panel models were employed to identify the influence factors. The time series analysis shows that the number of reported cases peaked in spring and summer and decreased in autumn and winter with the annual reported incidence of 113.1/100,000 population. Morans I global statistics were greater than 0 (0.363 - 0.536) during the study period. The most significant hot spots were mainly located in the central part. The east part exhibited a low-low relation. By spacetime scanning, the clusters identified were similar to that of the local autocorrelation statistics, and were clustered toward the early of 2016. Duration of sunshine, per capita gross domestic product (PGDP), the recovery rate of TB and participation rate of new cooperative medical care insurance in rural areas had a significant negative association with TB. In conclusion, the reported incidence of TB in Guangxi remains high. The main cluster was located in the central part of Guangxi, a region where promoting the productivity, improving TB treatment pathway and strengthening environmental protective measures (increasing sunshine exposure) are urgently needed.

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CUI, Z., Lin, D., Chongsuvivatwong, V., Zhao, J., Lin, M., Ou, J.. 2018-06-15. Detecting spatiotemporal pattern of tuberculosis and the relationship between ecological environment and tuberculosis, a spatial panel data analysis in Guangxi, China. https://doi.org/10.1101/348169

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