Center for Disease Control and Prevention of Chinese People's Liberation Army, 20 Dong-Da-Jie Street, Fengtai District, Beijing, 100071, China.
Academy of Military Medical Sciences, Academy of Military Science of Chinese People's Liberation Army, 27 Taiping Road, Haidian District, Beijing, 100036, China.
Infect Dis Poverty. 2023 Apr 12;12(1):36. doi: 10.1186/s40249-023-01087-y.
Brucellosis is a common zoonotic infectious disease in China. This study aimed to investigate the incidence trends of brucellosis in China, construct an optimal prediction model, and analyze the driving role of climatic factors for human brucellosis.
Using brucellosis incidence, and the socioeconomic and climatic data for 2014-2020 in China, we performed spatiotemporal analyses and calculated correlations with brucellosis incidence in China, developed and compared a series of regression and Seasonal Autoregressive Integrated Moving Average X (SARIMAX) models for brucellosis prediction based on socioeconomic and climatic data, and analyzed the relationship between extreme weather conditions and brucellosis incidence using copula models.
In total, 327,456 brucellosis cases were reported in China in 2014-2020 (monthly average of 3898 cases). The incidence of brucellosis was distinctly seasonal, with a high incidence in spring and summer and an average annual peak in May. The incidence rate was highest in the northern regions' arid and continental climatic zones (1.88 and 0.47 per million people, respectively) and lowest in the tropics (0.003 per million people). The incidence of brucellosis showed opposite trends of decrease and increase in northern and southern China, respectively, with an overall severe epidemic in northern China. Most regression models using socioeconomic and climatic data cannot predict brucellosis incidence. The SARIMAX model was suitable for brucellosis prediction. There were significant negative correlations between the proportion of extreme weather values for both high sunshine and high humidity and the incidence of brucellosis as follows: high sunshine, [Formula: see text] = -0.59 and -0.69 in arid and temperate zones; high humidity, [Formula: see text] = -0.62, -0.64, and -0.65 in arid, temperate, and tropical zones.
Significant seasonal and climatic zone differences were observed for brucellosis incidence in China. Sunlight, humidity, and wind speed significantly influenced brucellosis. The SARIMAX model performed better for brucellosis prediction than did the regression model. Notably, high sunshine and humidity values in extreme weather conditions negatively affect brucellosis. Brucellosis should be managed according to the "One Health" concept.
布鲁氏菌病是中国常见的人畜共患传染病。本研究旨在探讨中国布鲁氏菌病的发病趋势,构建最佳预测模型,并分析气候因素对人间布鲁氏菌病的驱动作用。
利用 2014-2020 年中国布鲁氏菌病发病率及社会经济和气候数据,进行时空分析,并计算与中国布鲁氏菌病发病率的相关性,基于社会经济和气候数据,开发并比较一系列回归和季节性自回归综合移动平均 X(SARIMAX)模型进行布鲁氏菌病预测,并使用 copula 模型分析极端天气条件与布鲁氏菌病发病率的关系。
2014-2020 年中国共报告布鲁氏菌病 327456 例(月平均 3898 例)。布鲁氏菌病发病具有明显季节性,春夏季高发,年均高峰在 5 月。发病率在北方干旱和大陆性气候带最高(分别为 1.88 和 0.47/百万人),在热带最低(0.003/百万人)。中国北方布鲁氏菌病发病率呈下降趋势,南方呈上升趋势,北方总体疫情严重。大多数使用社会经济和气候数据的回归模型不能预测布鲁氏菌病的发病率。SARIMAX 模型适用于布鲁氏菌病的预测。高阳光和高湿度极值比例与布鲁氏菌病发病率呈显著负相关,如下所示:干旱和温带地区高阳光,[公式:见正文] = -0.59 和 -0.69;干旱、温带和热带地区高湿度,[公式:见正文] = -0.62、-0.64 和-0.65。
中国布鲁氏菌病发病率存在明显的季节性和气候带差异。阳光、湿度和风速对布鲁氏菌病有显著影响。SARIMAX 模型比回归模型更适合布鲁氏菌病的预测。值得注意的是,极端天气条件下高阳光和高湿度值对布鲁氏菌病有负面影响。应根据“同一健康”理念管理布鲁氏菌病。