Spatiotemporal Pattern Evolution and Driving Factors of Brucellosis in China, 2003-2019.

Int J Environ Res Public Health

Department of Statistics, School of Mathematics and Statistics, Guangdong University of Foreign Studies, Guangzhou 510006, China.

Published: August 2022

Brucellosis is a prevalent zoonotic disease worldwide. However, the spatiotemporal patterns evolution and its driving factors of Brucellosis have not been well explored. In this study, spatiotemporal scan statistics were applied to describe the spatiotemporal pattern of evolution in Brucellosis from 2003 to 2019 in mainland China, and GeoDetector analysis was further conducted to explore the driving effects of environmental, meteorological, and socioeconomic factors. We identified a distinct seasonal pattern for Brucellosis, with a peak in May and lowest incidence between September and December. High-risk clusters were first observed in the northwestern pastoral areas and later expanded to the southern urban areas. The spatiotemporal heterogeneity was mainly explained by total SO emissions, average annual temperature, sheep output, and consumption of meat per capita with explanatory powers of 45.38%, 44.60%, 40.76%, and 30.46% respectively. However, the explanatory power changed over time. Specifically, the explanatory power of average annual temperature tended to decrease over time, while consumption of meat per capita and total output of animal husbandry tended to increase. The most favorable conditions for the spread of Brucellosis include 0.66-0.70 million tons of SO emissions, 9.54-11.68 °C of average annual temperature, 63.28-72.40 million heads of sheep output, and 16.81-20.58 kg consumption of meat per capita. Brucellosis remains more prevalent in traditional pastoral areas in Northwest China, with the tendency of spreading from pastoral to non-pastoral, and rural to urban, areas. Total SO emission, average annual temperature, sheep output, and consumption of meat per capita dominated the spatial heterogeneity of Brucellosis with changes in explanatory power over time.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9408399PMC
http://dx.doi.org/10.3390/ijerph191610082DOI Listing

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