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Updated: Aug 6, 2026
Microscopy-based Assays for High-throughput Screening of Host Factors Involved in Brucella Infection of Hela Cells
Published on: August 5, 2016
Spatiotemporal Analysis of the Primary Factors and Risk Quantification of Human Brucellosis Prevention and Control in
Juan Li1,2, Wenjing Li1, Lingyan Zhao3
1School of Computer Science and Technology (School of Artificial Intelligence), Zhejiang Sci-Tech University, Hangzhou, People's Republic of China.
Introduction:
Brucellosis is a major zoonotic disease that poses significant public health and socio-economic threats. In China, human brucellosis incidence has continued to rise, including in highly developed regions such as Zhejiang Province, despite relatively low levels of livestock husbandry. This study investigates the recent surge in human brucellosis in Zhejiang, aiming to identify key risk factors and inform prevention strategies.
Methods:
We collected case data from 11 municipal divisions of Zhejiang Province (2018-2023). To overcome limitations of conventional clustering methods, we applied Bayesian spatiotemporal models, global autocorrelation analysis, variance inflation factor analysis and Spearman correlation analysis. Sheep and cattle production, socio-economic metrics and climatic variables were incorporated to examine disease distribution, quantify risk factors and identify high-risk areas.
Results:
Human brucellosis showed marked regional variation and spatiotemporal clustering. Elevated risks were observed in Huzhou, Jiaxing, Quzhou and Lishui, while Zhoushan, Ningbo, Taizhou, Wenzhou and Hangzhou displayed lower risks. Live sheep imports and slaughter volumes were the dominant factors, positively correlated with incidence (RR = 1.1816, 95% CI: 1.0096-1.3880; RR = 1.6175, 95% CI: 1.1883-2.3546). These findings underscore the importance of livestock trade and slaughter practices in shaping transmission dynamics.
Conclusions:
Targeted prevention strategies are urgently needed in developed regions such as Zhejiang. We recommend strengthening the brucellosis prevention framework, enhancing regulatory oversight of live sheep transport and slaughter in high-risk areas and leveraging modern information technologies (e.g., AI and big data) for surveillance and decision support. This study advances the theoretical and practical framework for brucellosis prevention and offers insights for both regional and national disease control, contributing to public health protection and sustainable livestock development.
