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Forecasting the incidence of mumps in Chongqing based on a SARIMA model

机译:基于Sarima模型的重庆腮腺炎发病率预测

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Mumps is classified as a class C infection disease in China, and the Chongqing area has one of the highest incidence rates in the country. We aimed to establish a prediction model for mumps in Chongqing and analyze its seasonality, which is important for risk analysis and allocation of resources in the health sector. Data on incidence of mumps from January 2004 to December 2018 were obtained from Chongqing Municipal Bureau of Disease Control and Prevention. The incidence of mumps from 2004 to 2017 was fitted using a seasonal autoregressive comprehensive moving average (SARIMA) model. The root mean square error (RMSE) and mean absolute percentage error (MAPE) were used to compare the goodness of fit of the models. The 2018 incidence data were used for validation. From 2004 to 2018, a total of 159,181 cases (93,655 males and 65,526 females) of mumps were reported in Chongqing, with significantly more men than women. The age group of 0–19 years old accounted for 92.41% of all reported cases, and students made up the largest proportion (62.83%), followed by scattered children and children in kindergarten. The SARIMA(2, 1, 1) × (0, 1, 1)12 was the best fit model, RMSE and MAPE were 0.9950 and 39.8396%, respectively. Based on the study findings, the incidence of mumps in Chongqing has an obvious seasonal trend, and SARIMA(2, 1, 1) × (0, 1, 1)12 model can also predict the incidence of mumps well. The SARIMA model of time series analysis is a feasible and simple method for predicting mumps in Chongqing.
机译:腮腺炎被归类为中国的C类感染病,重庆地区拥有该国最高的发病率之一。我们旨在建立重庆腮腺炎的预测模型,分析其季节性,对卫生部门的风险分析和资源分配是重要的。 2004年1月至2018年12月的腮腺炎发生率数据是从重庆市疾病控制和预防局获得的。 2004年至2017年腮腺炎的发病率使用季节性自回归综合综合综合寿命(Sarima)模型。均均方误差(RMSE)和平均绝对百分比误差(MAPE)用于比较模型适合的良好。 2018年发病率数据用于验证。从2004年到2018年,重庆报道了共有159,181例(93,655名男性和65,526名女性),比女性多于女性。年龄组0-19岁占所有报告案件的92.41%,学生占幼儿园的分散儿童和儿童的比例最大(62.83%)。 Sarima(2,1,1)×(0,1,1)12是最佳的拟合模型,RMSE和MAPE分别为0.9950和39.8396%。基于研究结果,重庆腮腺炎的发生率具有明显的季节性趋势,赛马艇(2,1,1)×(0,1,1)12模型也可以预测腮腺炎的发生率。 Sarima时间序列分析模型是预测重庆腮腺炎的可行性和简单方法。

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