Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Int J Environ Res Public Health. 2019 Nov 5;16(21):4289. doi: 10.3390/ijerph16214289.
Brucellosis occurs periodically and causes great economic and health burdens. Brucellosis prediction plays an important role in its prevention and treatment. This paper establishes relationships between human brucellosis (HB) and land surface temperature (LST), and the normalized difference vegetation index (NDVI). A seasonal autoregressive integrated moving average with exogenous variables (SARIMAX) model is constructed to predict trends in brucellosis rates. The fitted results (Akaike Information Criterion (AIC) = 807.58, Schwarz Bayes Criterion (SBC) = 819.28) showed obvious periodicity and a rate of increase of 138.68% from January 2011 to May 2016. We found a significant effect between HB and NDVI. At the same time, the prediction part showed that the highest monthly incidence per year has a decreasing trend after 2015. This may be because of the brucellosis prevention and control measures taken by the Chinese Government. The proposed model allows the early detection of brucellosis outbreaks, allowing more effective prevention and control.
布鲁氏菌病周期性发生，给经济和健康带来了巨大负担。布鲁氏菌病预测对其预防和治疗起着重要作用。本文建立了人类布鲁氏菌病（HB）与地表温度（LST）和归一化差异植被指数（NDVI）之间的关系。构建了一个具有外生变量的季节性自回归综合移动平均（SARIMAX）模型来预测布鲁氏菌病发病率的趋势。拟合结果（赤池信息量准则（AIC）=807.58，施瓦茨贝叶斯准则（SBC）=819.28）显示出明显的周期性，2011 年 1 月至 2016 年 5 月的增长率为 138.68%。我们发现 HB 与 NDVI 之间存在显著影响。同时，预测部分显示，2015 年后每年的最高月发病率呈下降趋势。这可能是因为中国政府采取了布鲁氏菌病防控措施。所提出的模型允许早期发现布鲁氏菌病疫情，从而更有效地进行预防和控制。
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