内科

目的应用季节性（差分整合）自回归移动平均（SARIMA）模型预测广西乙类传染病发病情况。方法将2011年1月至2022年5月广西乙类传染病月报告发病数据作为训练集构建时间序列，拟合和构建SARIMA预测模型；以2022年6月至11月的广西乙类传染病月报告发病数据作为测试集对模型进行测试。结果广西乙类传染病的发病情况呈季节性规律，最优预测模型为SARIMA(3, 1, 3)(2, 0, 0)12，其预测效果平均相对误差为7.99%，预测发病例数95% CI均包含了实际发病例数。结论SARIMA(3, 1, 3)(2, 0, 0)12模型能较好地拟合广西乙类传染病的发病情况，可用于疫情的短期监测。

ObjectiveTo predict the incidence of category B infectious diseases in Guangxi with the seasonal autoregressive integrated moving average (SARIMA) model. MethodThe monthly reported incidence data of category B infectious diseases in Guangxi from January 2011 to May 2022 were used as the training set to construct a time series, and the SARIMA prediction model was fitted and constructed. The monthly reported incidence data of category B infectious diseases in Guangxi from June to November 2022 was used as the test set to test the model. ResultsThe incidence of category B infectious diseases in Guangxi was seasonal, and the optimal prediction model was SARIMA(3, 1, 3)(2, 0, 0)12, with a mean relative error of the predictive validity of 7.99%, and the 95% CI of the predictive incidence included the actual incidence. ConclusionThe SARIMA(3, 1, 3)(2, 0, 0)12 model can well fit the incidence of category B infectious diseases in Guangxi and can be used for short-term surveillance of the epidemic.

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