Risk effects of environmental factors on human brucellosis in Aksu Prefecture, Xinjiang, China, 2014–2023
Abstract The context of rapid global environmental change underscores the pressing necessity to investigate the environmental factors and high-risk areas that contribute to the occurrence of brucellosis. In this study, a maximum entropy (MaxEnt) model was employed to analyze the factors influencing...
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2025-01-01
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| author | Di Wu Xinxiu Shen Quan Zhou Jing Zhou Ruonan Fu Chang Wang Yuhua Ma Chenchen Wang |
| author_facet | Di Wu Xinxiu Shen Quan Zhou Jing Zhou Ruonan Fu Chang Wang Yuhua Ma Chenchen Wang |
| author_sort | Di Wu |
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| description | Abstract The context of rapid global environmental change underscores the pressing necessity to investigate the environmental factors and high-risk areas that contribute to the occurrence of brucellosis. In this study, a maximum entropy (MaxEnt) model was employed to analyze the factors influencing brucellosis in the Aksu Prefecture from 2014 to 2023. A distributed lag nonlinear model (DLNM) was employed to investigate the lagged effect of meteorological factors on the occurrence of brucellosis. A total of 17 environmental factors were identified as affecting the distribution of brucellosis to varying degrees. The largest contributing was the normalized difference vegetation index (NDVI), followed by gross domestic product (GDP), and then meteorological factors such as average temperature, average relative humidity, and average wind speed. The receiver operating characteristic (ROC) curve demonstrated that the MaxEnt model exhibited a high degree of predictive efficacy, with an area under the curve (AUC) value of 0.921. The impact of high temperature (25℃ with a 2-month lag, RR = 3.130, 95% CI 1.642 ~ 5.965), low relative humidity (28% with a 2.5-month lag, RR = 1.795, 95% CI 1.298 ~ 2.483), and low wind speed (1.9 m/s with a 0-month lag, RR = 2.408, 95% CI 1.360 ~ 4.264) are the most significant meteorological factors associated with the incidence of brucellosis. The trends in the impact of extreme meteorological conditions on the spread of brucellosis were found to be generally consistent. Stratified analyses indicated that males were more affected by meteorological factors than females. The prevalence of brucellosis is influenced by a range of socio-economic and meteorological factors, and a multifaceted approach is necessary to prevent and control brucellosis. |
| format | Article |
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| institution | Kabale University |
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| language | English |
| publishDate | 2025-01-01 |
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| spelling | doaj-art-940c561434214114837cb9b2c7dca8d32025-01-26T12:34:21ZengNature PortfolioScientific Reports2045-23222025-01-0115111410.1038/s41598-025-86889-wRisk effects of environmental factors on human brucellosis in Aksu Prefecture, Xinjiang, China, 2014–2023Di Wu0Xinxiu Shen1Quan Zhou2Jing Zhou3Ruonan Fu4Chang Wang5Yuhua Ma6Chenchen Wang7School of Public Health, Xinjiang Medical UniversityAksu Regional Center for Disease Control and PreventionAksu Regional Center for Disease Control and PreventionSchool of Public Health, Xinjiang Medical UniversitySchool of Public Health, Xinjiang Medical UniversitySchool of Public Health, Xinjiang Medical UniversityXinjiang Key Laboratory of Clinical Genetic Testing and Biomedical InformationSchool of Public Health, Xinjiang Medical UniversityAbstract The context of rapid global environmental change underscores the pressing necessity to investigate the environmental factors and high-risk areas that contribute to the occurrence of brucellosis. In this study, a maximum entropy (MaxEnt) model was employed to analyze the factors influencing brucellosis in the Aksu Prefecture from 2014 to 2023. A distributed lag nonlinear model (DLNM) was employed to investigate the lagged effect of meteorological factors on the occurrence of brucellosis. A total of 17 environmental factors were identified as affecting the distribution of brucellosis to varying degrees. The largest contributing was the normalized difference vegetation index (NDVI), followed by gross domestic product (GDP), and then meteorological factors such as average temperature, average relative humidity, and average wind speed. The receiver operating characteristic (ROC) curve demonstrated that the MaxEnt model exhibited a high degree of predictive efficacy, with an area under the curve (AUC) value of 0.921. The impact of high temperature (25℃ with a 2-month lag, RR = 3.130, 95% CI 1.642 ~ 5.965), low relative humidity (28% with a 2.5-month lag, RR = 1.795, 95% CI 1.298 ~ 2.483), and low wind speed (1.9 m/s with a 0-month lag, RR = 2.408, 95% CI 1.360 ~ 4.264) are the most significant meteorological factors associated with the incidence of brucellosis. The trends in the impact of extreme meteorological conditions on the spread of brucellosis were found to be generally consistent. Stratified analyses indicated that males were more affected by meteorological factors than females. The prevalence of brucellosis is influenced by a range of socio-economic and meteorological factors, and a multifaceted approach is necessary to prevent and control brucellosis.https://doi.org/10.1038/s41598-025-86889-wBrucellosisInfluencing factorsMaximum entropy modelDistributional lag nonlinear modelMeteorological factor |
| spellingShingle | Di Wu Xinxiu Shen Quan Zhou Jing Zhou Ruonan Fu Chang Wang Yuhua Ma Chenchen Wang Risk effects of environmental factors on human brucellosis in Aksu Prefecture, Xinjiang, China, 2014–2023 Scientific Reports Brucellosis Influencing factors Maximum entropy model Distributional lag nonlinear model Meteorological factor |
| title | Risk effects of environmental factors on human brucellosis in Aksu Prefecture, Xinjiang, China, 2014–2023 |
| title_full | Risk effects of environmental factors on human brucellosis in Aksu Prefecture, Xinjiang, China, 2014–2023 |
| title_fullStr | Risk effects of environmental factors on human brucellosis in Aksu Prefecture, Xinjiang, China, 2014–2023 |
| title_full_unstemmed | Risk effects of environmental factors on human brucellosis in Aksu Prefecture, Xinjiang, China, 2014–2023 |
| title_short | Risk effects of environmental factors on human brucellosis in Aksu Prefecture, Xinjiang, China, 2014–2023 |
| title_sort | risk effects of environmental factors on human brucellosis in aksu prefecture xinjiang china 2014 2023 |
| topic | Brucellosis Influencing factors Maximum entropy model Distributional lag nonlinear model Meteorological factor |
| url | https://doi.org/10.1038/s41598-025-86889-w |
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