Melioidosis is a zoonotic disease that is caused by Burkholderia pseudomallei, which is a serious public health and safety risk. In order to explore the global animal melioidosis risk distribution and its dynamic response to future climate scenarios, we collected global data about reported animal incidence sites. Data regarding the density of Burkholderia pseudomallei in the environment were created by collecting and sorting information about the Burkholderia pseudomallei occurrence sites in contaminated air, soil, and water. Combined with bioclimatic variables, the maximum entropy (MaxEnt) niche was modeled for global animal melioidosis. The findings indicate that under current bioclimatic conditions, global animal melioidosis risk regions are concentrated between 30° S and 30° N, with high-risk areas being mainly in Central America, the northern part of South America, and eastern and southern India, among others. Most countries will expand their risk regions under future climatic scenarios. Melioidosis risk expanding towards higher northern latitudes has led to new epidemic areas. In addition, the melioidosis risk area will contract in some areas. Therefore, we have provided a basis for global melioidosis surveillance and propose feasible strategies for prevention and control in high-risk regions, which will help countries to carry out targeted surveillance and prevention to reduce risks and losses.

Not-yet-known not-yet-known not-yet-known unknown Tuberculosis is a zoonotic chronic respiratory infectious disease caused by the Mycobacterium tuberculosis complex. Domestic animals such as cattle, sheep, and goats are important but neglected hosts of tuberculosis. The outbreak and epidemic of tuberculosis can seriously threaten human and veterinary health. To investigate the effects of air pollutants and meteorological factors on cattle, sheep, and goat tuberculosis, we obtained the incidence rates of M. tuberculosis infection in cattle, buffaloes, sheep, and goats in China from the published literature. We identified key risk factors among 6 major air pollutants (particulate matter 2.5, particulate matter 10, carbon monoxide, nitrogen dioxide, sulfur dioxide, and ozone) and 19 bioclimatic variables; simulated the risk distribution of cattle, sheep, and goat tuberculosis in China using the maximum entropy niche model; and evaluated the effects of environmental factors. The area under the curve of the model was 0.873 (95% confidence interval, 0.0851–0.0895). The risk factors that most significantly influenced the incidence of tuberculosis included NO2 level, mean temperature of the coldest quarter, cattle distribution density, sheep distribution density, O3 level, and precipitation of the driest month. The predicted risk map indicated that the high-risk regions were Guangxi Province; the northern Taklimakan Desert in Xinjiang, Guangdong Province; Hainan Province; Eastern Qinghai Province; parts of Shandong Province; Gansu Province; Eastern Sichuan Province; Central Shaanxi Province; Central Inner Mongolia; Beijing–Tianjin–Hebei region; Ningxia Hui Autonomous Region; Northern Henan Province; the border area between Jiangsu, Zhejiang, and Shanghai; and Taiwan Island. Improved surveillance is needed in these high-risk areas, and early preventive measures must be implemented based on the risk factors identified to reduce future incidence of cattle, sheep, and goat tuberculosis.

Tuberculosis is a zoonotic chronic respiratory infectious disease caused by the Mycobacterium tuberculosis complex. The outbreak and epidemic of tuberculosis can seriously threaten human and veterinary health. To investigate the effects of environmental factors on tuberculosis in domestic ruminants, we collected data regarding the prevalence of tuberculosis in cattle, buffaloes, sheep, and goats in China (1956–2024) from publicly published literature and available databases. We identified the key risk factors among six major air pollutants and 19 bioclimatic variables; simulated the risk distribution of tuberculosis in cattle, buffaloes, sheep, and goats in China using the maximum entropy ecological niche model; and evaluated the effects of environmental factors. The area under the curve of the model was 0.873 (95% confidence interval, 0.851–0.895). The risk factors that most significantly influenced the prevalence of tuberculosis were the nitrogen dioxide (NO₂) level, mean temperature of the coldest quarter, cattle distribution density, sheep distribution density, ozone (O₃) level, and precipitation of the driest month. The predicted map of tuberculosis risk in cattle, buffaloes, sheep, and goats indicated that the high-risk regions were mainly distributed in South, North, East, and Northwest China. Improved surveillance is needed in these high-risk areas, and early preventive measures must be implemented based on the risk factors identified to reduce the future prevalence of tuberculosis in cattle, buffaloes, sheep, and goats.