Ke Li, Jidan Zhang, Binbin Yu, Michael P. Ward, Mengxin Liu, Yuanhua Liu, Zengliang Wang, Zhuohang Chen, Wenjin Li, Na Wang, Yu Zhao, Xiangdong Yang, Fuping Yang, Peng Wang, Zhijie Zhang
{"title":"2006-2021年影响云南省人类布鲁氏菌病发病的气象、社会经济和环境因素：贝叶斯时空模型研究","authors":"Ke Li, Jidan Zhang, Binbin Yu, Michael P. Ward, Mengxin Liu, Yuanhua Liu, Zengliang Wang, Zhuohang Chen, Wenjin Li, Na Wang, Yu Zhao, Xiangdong Yang, Fuping Yang, Peng Wang, Zhijie Zhang","doi":"10.1155/tbed/8872434","DOIUrl":null,"url":null,"abstract":"<div>\n <p><b>Background:</b> Brucellosis epidemics in Yunnan Province in southern China have increased and caused more impact in recent years. However, the epidemiological characteristics and driving factors for brucellosis have not been clearly described. The aim of this study was to analyze the spatiotemporal distribution and potential factors for human brucellosis (HB) in Yunnan Province, 2006–2021.</p>\n <p><b>Methods:</b> HB data were obtained from the China National Notifiable Infectious Diseases Reporting Information System. Global spatial autocorrelation and spatial scanning statistics were used to analyze the spatial patterns of brucellosis. Zero-inflated negative binomial (ZINB) Bayesian spatiotemporal models were applied to the analysis of potential risk factors, including environmental, meteorological, and socioeconomic factors.</p>\n <p><b>Findings:</b> Between 2006 and 2021, a total of 2794 brucellosis cases were reported. The central and western regions were the most severely affected. GDP showed a positive correlation with brucellosis risk when in the range 0–30.9 billion RMB, peaking with a relative risk (RR) of 13.64 (95% Bayesian credible interval [BCI]: 4.10, 49.10) at around 2.3 billion RMB. Conversely, a negative correlation was observed for GDP between 101 and 135 billion RMB, with the RR dropping to 0.14 (95% BCI: 0.01, 0.89) at 135 billion RMB. Brucellosis cases increased by 4.90% (95% BCI: 1.82%, 7.95%) per 1°C increase in temperature, while a 1° increase in slope reduced cases by 17.06% (95% BCI: 4.01%, 28.81%).</p>\n <p><b>Interpretation:</b> Our findings suggest that socioeconomic factors play the greatest role in the occurrence of brucellosis in both northern and southern China; however, the effects of the environmental factors may be different between these areas. Differences in factors affecting each region need to be fully considered, and brucellosis prevention and control need to be adapted to these differences.</p>\n </div>","PeriodicalId":234,"journal":{"name":"Transboundary and Emerging Diseases","volume":"2025 1","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/tbed/8872434","citationCount":"0","resultStr":"{\"title\":\"Meteorological, Socioeconomic, and Environmental Factors Influencing Human Brucellosis Occurrence in Yunnan, China, 2006–2021: A Bayesian Spatiotemporal Modeling Study\",\"authors\":\"Ke Li, Jidan Zhang, Binbin Yu, Michael P. Ward, Mengxin Liu, Yuanhua Liu, Zengliang Wang, Zhuohang Chen, Wenjin Li, Na Wang, Yu Zhao, Xiangdong Yang, Fuping Yang, Peng Wang, Zhijie Zhang\",\"doi\":\"10.1155/tbed/8872434\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n <p><b>Background:</b> Brucellosis epidemics in Yunnan Province in southern China have increased and caused more impact in recent years. However, the epidemiological characteristics and driving factors for brucellosis have not been clearly described. The aim of this study was to analyze the spatiotemporal distribution and potential factors for human brucellosis (HB) in Yunnan Province, 2006–2021.</p>\\n <p><b>Methods:</b> HB data were obtained from the China National Notifiable Infectious Diseases Reporting Information System. Global spatial autocorrelation and spatial scanning statistics were used to analyze the spatial patterns of brucellosis. Zero-inflated negative binomial (ZINB) Bayesian spatiotemporal models were applied to the analysis of potential risk factors, including environmental, meteorological, and socioeconomic factors.</p>\\n <p><b>Findings:</b> Between 2006 and 2021, a total of 2794 brucellosis cases were reported. The central and western regions were the most severely affected. GDP showed a positive correlation with brucellosis risk when in the range 0–30.9 billion RMB, peaking with a relative risk (RR) of 13.64 (95% Bayesian credible interval [BCI]: 4.10, 49.10) at around 2.3 billion RMB. Conversely, a negative correlation was observed for GDP between 101 and 135 billion RMB, with the RR dropping to 0.14 (95% BCI: 0.01, 0.89) at 135 billion RMB. Brucellosis cases increased by 4.90% (95% BCI: 1.82%, 7.95%) per 1°C increase in temperature, while a 1° increase in slope reduced cases by 17.06% (95% BCI: 4.01%, 28.81%).</p>\\n <p><b>Interpretation:</b> Our findings suggest that socioeconomic factors play the greatest role in the occurrence of brucellosis in both northern and southern China; however, the effects of the environmental factors may be different between these areas. Differences in factors affecting each region need to be fully considered, and brucellosis prevention and control need to be adapted to these differences.</p>\\n </div>\",\"PeriodicalId\":234,\"journal\":{\"name\":\"Transboundary and Emerging Diseases\",\"volume\":\"2025 1\",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2025-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1155/tbed/8872434\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transboundary and Emerging Diseases\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1155/tbed/8872434\",\"RegionNum\":2,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transboundary and Emerging Diseases","FirstCategoryId":"97","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/tbed/8872434","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
Meteorological, Socioeconomic, and Environmental Factors Influencing Human Brucellosis Occurrence in Yunnan, China, 2006–2021: A Bayesian Spatiotemporal Modeling Study
Background: Brucellosis epidemics in Yunnan Province in southern China have increased and caused more impact in recent years. However, the epidemiological characteristics and driving factors for brucellosis have not been clearly described. The aim of this study was to analyze the spatiotemporal distribution and potential factors for human brucellosis (HB) in Yunnan Province, 2006–2021.
Methods: HB data were obtained from the China National Notifiable Infectious Diseases Reporting Information System. Global spatial autocorrelation and spatial scanning statistics were used to analyze the spatial patterns of brucellosis. Zero-inflated negative binomial (ZINB) Bayesian spatiotemporal models were applied to the analysis of potential risk factors, including environmental, meteorological, and socioeconomic factors.
Findings: Between 2006 and 2021, a total of 2794 brucellosis cases were reported. The central and western regions were the most severely affected. GDP showed a positive correlation with brucellosis risk when in the range 0–30.9 billion RMB, peaking with a relative risk (RR) of 13.64 (95% Bayesian credible interval [BCI]: 4.10, 49.10) at around 2.3 billion RMB. Conversely, a negative correlation was observed for GDP between 101 and 135 billion RMB, with the RR dropping to 0.14 (95% BCI: 0.01, 0.89) at 135 billion RMB. Brucellosis cases increased by 4.90% (95% BCI: 1.82%, 7.95%) per 1°C increase in temperature, while a 1° increase in slope reduced cases by 17.06% (95% BCI: 4.01%, 28.81%).
Interpretation: Our findings suggest that socioeconomic factors play the greatest role in the occurrence of brucellosis in both northern and southern China; however, the effects of the environmental factors may be different between these areas. Differences in factors affecting each region need to be fully considered, and brucellosis prevention and control need to be adapted to these differences.
期刊介绍：
Transboundary and Emerging Diseases brings together in one place the latest research on infectious diseases considered to hold the greatest economic threat to animals and humans worldwide. The journal provides a venue for global research on their diagnosis, prevention and management, and for papers on public health, pathogenesis, epidemiology, statistical modeling, diagnostics, biosecurity issues, genomics, vaccine development and rapid communication of new outbreaks. Papers should include timely research approaches using state-of-the-art technologies. The editors encourage papers adopting a science-based approach on socio-economic and environmental factors influencing the management of the bio-security threat posed by these diseases, including risk analysis and disease spread modeling. Preference will be given to communications focusing on novel science-based approaches to controlling transboundary and emerging diseases. The following topics are generally considered out-of-scope, but decisions are made on a case-by-case basis (for example, studies on cryptic wildlife populations, and those on potential species extinctions):
Pathogen discovery: a common pathogen newly recognised in a specific country, or a new pathogen or genetic sequence for which there is little context about — or insights regarding — its emergence or spread.
Prevalence estimation surveys and risk factor studies based on survey (rather than longitudinal) methodology, except when such studies are unique. Surveys of knowledge, attitudes and practices are within scope.
Diagnostic test development if not accompanied by robust sensitivity and specificity estimation from field studies.
Studies focused only on laboratory methods in which relevance to disease emergence and spread is not obvious or can not be inferred (“pure research” type studies).
Narrative literature reviews which do not generate new knowledge. Systematic and scoping reviews, and meta-analyses are within scope.
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