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Application of the exponential smoothing model and ARIMA model in prediction of the endemic situation of schistosomiasis in Hunan Province


Application of the exponential smoothing model and ARIMA model in prediction of the endemic situation of schistosomiasis in Hunan Province



Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 32(3): 236-241



PMID: 32468784

[摘要] 目的 应用指数平滑模型与ARIMA模型预测湖南省人畜血吸虫感染率变化趋势。方法 根据 1957–2015 年湖南省血吸虫病防治工作统计资料中的人畜感染率数据, 建立指数平滑模型及ARIMA模型, 并对 2016–2018 年湖南省人畜血吸虫感染率进行预测与效果评价。结果 1957–2015 年湖南省人畜血吸虫感染率指数平滑模型与ARIMA模型均具有较好拟合效果。1957–2015 年湖南省人畜血吸虫感染率具有线性趋势, 2016–2018 年人群感染率Brown’s线性趋势指数平滑模型与家畜感染率Holt’s线性趋势指数平滑模型预测值较 2016–2018 年人畜感染率ARIMA模型预测值更匹配于实际数据, 但ARIMA模型提示湖南省血吸虫病可能仍处于低流行状态。结论 在血吸虫病低流行情况下, 湖南省亟须研发高敏感度疾病监测技术, 以匹配当前流行态势, 并强化防控措施以巩固取得的防控成果。.

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