{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T08:23:59Z","timestamp":1788337439240,"version":"build-2803163510"},"reference-count":49,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T00:00:00Z","timestamp":1788307200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Animals"],"abstract":"<jats:p>More than 80% of global brucellosis cases occur in semi-arid regions; however, the climatic factors associated with these outbreaks remain poorly understood. This study investigated environmental correlates of brucellosis in a semi-arid region of Xinjiang, China. A maximum entropy (MaxEnt) model incorporating 19 bioclimatic variables, wind speed, solar radiation, and ruminant livestock inventory was applied to 1132 surveillance-confirmed human brucellosis cases from January 2015 to December 2025. Precipitation in the driest month (31.8%), wind speed (24.3%), and temperature seasonality (13.7%) were the leading contributors to the predicted risk. The model identified high-risk zones in low-precipitation moderate-wind steppe environments and showed strong predictive performance (AUC = 0.960 \u00b1 0.007). These findings indicate that water scarcity and thermal variability are key environmental constraints associated with brucellosis distribution in semi-arid ecosystems and may inform climate-resilient One Health-based prevention strategies in similar agro-ecological zones globally.<\/jats:p>","DOI":"10.3390\/ani16172735","type":"journal-article","created":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T07:53:11Z","timestamp":1788335591000},"page":"2735","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Climatic Correlates of Brucellosis Transmission in a Semi-Arid Region of Xinjiang, China, 2015\u20132025: A Maximum Entropy Modeling Study Within a One Health Framework"],"prefix":"10.3390","volume":"16","author":[{"given":"Yuerong","family":"Lv","sequence":"first","affiliation":[{"name":"Key Laboratory of the Provincial Education Department of Heilongjiang for Common Animal Disease Prevention and Treatment, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7698-8578","authenticated-orcid":false,"given":"Xiang","family":"Gao","sequence":"additional","affiliation":[{"name":"Key Laboratory of the Provincial Education Department of Heilongjiang for Common Animal Disease Prevention and Treatment, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1186\/s13643-025-03036-2","article-title":"Seroprevalence of brucellosis in humans and livestock in Sub-Saharan Africa: A systematic review and meta-analysis","volume":"15","author":"Wagaba","year":"2025","journal-title":"Syst. 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