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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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In this study, a non-autonomous patch dynamical model was developed for Zhejiang Province, incorporating the \u201clive sheep - mutton - human\u201d transmission chain. The effective reproduction number was defined to calculate infection metrics for pathogen transmission in three pathways: sheep-to-sheep, sheep-to-human, and mutton-to-human. Multi-source data, including demographics, livestock farming, and meat transportation data from 2018 to 2024, were integrated. Key drivers of brucellosis transmission were explored through parameter estimation, sensitivity analysis, and multi-scenario numerical simulations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The findings indicated a significant positive correlation between the number of live sheep imported from Region I and human brucellosis incidence rates, suggesting that imported infections have become the primary challenge for brucellosis control in Zhejiang Province. The baseline projected incidence in Zhejiang Province is expected to remain 0.3 per 100,000 by 2026 under current interventions. A 71.4% increase in human incidence (peaking at 0.6 per 100,000) in 2025 would occur if live sheep imports from other provinces were doubled, underscoring the risk of external introduction. Conversely, enhancing transport detection by 15% could reduce incidence below 0.2 per 100,000, while an integrated strategy combining improved culling, transport detection, and consumption monitoring could lower incidence to 0.1 per 100,000, representing a 66.7% reduction. Similarly, reducing both live sheep and mutton imports by 50% would decrease incidence by 40%, preventing an estimated 91 infections. Furthermore, improving comprehensive protection awareness by 50% is projected to reduce incidence to below 0.15 per 100,000, corresponding to a 53.3% decrease by 2026. Under non-immunization intervention scenarios, surveillance gaps in the farming-transportation-consumption chains could lead to a significant expansion of the epidemic. Implementing an integrated strategy combining source quarantine (testing imported live sheep), process control (regular monitoring of farming environments), and end-point protection (personal protective measures) was found to substantially reduce incidence rates within two years.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The results of this study suggest that strengthening the monitoring of the inter-provincial live animal transportation surveillance network is crucial, as it can facilitate early warning of brucellosis transmission risks. This highlights the importance of targeted measures to address imported infections and enhance surveillance across the entire transmission chain for effective brucellosis control in Type II regions like Zhejiang Province.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12879-026-12787-9","type":"journal-article","created":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T17:35:03Z","timestamp":1771608903000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A multi-source data-based modelling study on brucellosis transmission risk analysis and control strategies in Zhejiang Province, China"],"prefix":"10.1186","volume":"26","author":[{"given":"Juan","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junhui","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingyan","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shubo","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lu","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siqi","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongli","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,2,20]]},"reference":[{"issue":"6","key":"12787_CR1","doi-asserted-by":"publisher","first-page":"1270","DOI":"10.1111\/j.1365-2672.2005.02622.x","volume":"98","author":"SJ Cutler","year":"2005","unstructured":"Cutler SJ, Whatmore AM, Commander N J. 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