中国人兽共患病学报2023，Vol.39Issue(12)：1233-1238,6.DOI:10.3969/j.issn.1002-2694.2023.00.141
基于贝叶斯LASSO矩阵指数空间模型辨识布鲁氏菌病发病的关键风险因素
Identification of key risk factors in the incidence of brucellosis through Bayesian LASSO matrix exponential spatial specification
摘要
Abstract
The purpose of this study was to explore the relationships between the incidence of brucellosis and the climate,natural environment and animal husbandry in mainland China in 2020,and to identify key influencing variables.The objective was to provide a scientific basis for brucellosis prevention and control.For spatial autocorrelation,a BL-MESS model was es-tablished by combining the matrix exponential spatial specification(MESS)and Bayesian LASSO.Confidence intervals were used to identify important variables,and spatial effect decomposition was applied to reveal the potential relationships of various factors with the incidence of brucellosis.The incidence of brucellosis in China showed significantly positive spatial dependence.The average temperature,average elevation,proportion of pastureland area,and number of goats and sheep in stock at the end of the year had significant effects on brucellosis incidence.In addition,the number of goats in stock at the end of the year had a significantly positive spatial spillover effect,and the average elevation showed the opposite result,thus implying that areas with low altitude and provinces with large scale goat breeding are at risk of brucellosis spillover.The method greatly decreases the standard deviation of parameter estimation,improves precision and effectively identifies important risk factors.Brucellosis is substantially affected by climate and animal husbandry,thus suggesting that close attention to climate change and animal epi-demic prevention should be important aspects of brucellosis prevention in the future.关键词
布鲁氏菌病/矩阵指数空间规范/贝叶斯LASSOKey words
brucellosis/matrix exponential spatial specification/Bayesian LASSO分类
医药卫生引用本文复制引用
张辉国,梁韵婷,胡锡健..基于贝叶斯LASSO矩阵指数空间模型辨识布鲁氏菌病发病的关键风险因素[J].中国人兽共患病学报,2023,39(12):1233-1238,6.基金项目
Supported by the Natural Science Foundation of Xinjiang(No.2023D01C01),the Humanities and Social Science Research Pro-gram Foundation of the Ministry of Education(No.19YJA910007)and the National Natural Science Founda-tion of China(No.11961065)新疆自然科学基金(No.2023D01C01) （No.2023D01C01）
教育部人文社会科学研究规划基金(No.19YJA910007) （No.19YJA910007）
国家自然科学基金(No.11961065) （No.11961065）
