A multi-source data-based modelling study on brucellosis transmission risk analysis and control strategies in Zhejiang Province, China
Juan Li, Wei Jiang, Junhui Zhang, Lingyan Zhao, Shubo Li, Lu Gao, Siqi Sun, Hongli Zhang

TL;DR
This study models brucellosis transmission in Zhejiang Province, China, showing that imported live sheep are a major risk and suggesting improved monitoring and control strategies to reduce infections.
Contribution
The study introduces a non-autonomous patch dynamical model for Type II regions, integrating multi-source data to analyze transmission risks and evaluate control strategies.
Findings
Imported live sheep from Region I strongly correlate with human brucellosis incidence in Zhejiang.
Enhanced transport detection and integrated control strategies could reduce incidence by up to 66.7%.
A 50% reduction in live sheep and mutton imports could prevent an estimated 91 infections.
Abstract
Brucellosis presents a severe challenge to public health due to its complex transmission mechanism. In China, regions are categorized into three types based on the number of new human brucellosis cases or provinces affected by animal outbreaks, with tailored control strategies adopted accordingly. Currently, most research on brucellosis transmission modeling focuses on Type I regions. However, due to regional variations in farming practices, influencing factors, and control measures, existing studies are highly region-specific, restricting their direct application to Type II regions such as Zhejiang Province. Notably, annual brucellosis outbreaks in Zhejiang Province are worsening, highlighting the need for targeted research. In this study, a non-autonomous patch dynamical model was developed for Zhejiang Province, incorporating the “live sheep - mutton - human” transmission chain. The…
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Taxonomy
TopicsBrucella: diagnosis, epidemiology, treatment · Zoonotic diseases and public health · Parasitic Diseases Research and Treatment
