赵玉芹,史景红,徐菲,郭世成.应用自回归移动平均模型预测分析江西省流行性腮腺炎的发病趋势[J].Chinese journal of Epidemiology,2023,44(12):1911-1915 |
应用自回归移动平均模型预测分析江西省流行性腮腺炎的发病趋势 |
Application of autoregressive integrated moving average model to predict and analyze the incidence trend of mumps in Jiangxi Province |
Received:May 29, 2023 |
DOI:10.3760/cma.j.cn112338-20230529-00338 |
KeyWord: 流行性腮腺炎 自回归移动平均模型 非药物干预 预测 |
English Key Word: Mumps Autoregressive integrated moving average model Non-drug interventions Prediction |
FundProject:江西省卫生健康委员会科技计划(202211306);中华预防医学会预防接种信息化与服务能力提升项目(CPMA-JY2021-016) |
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Abstract: |
目的 应用自回归移动平均模型(ARIMA)预测分析江西省流行性腮腺炎的发病趋势。方法 利用ARIMA对江西省2015-2019年每月流行性腮腺炎报告发病数进行建模,预测12个月的发病数,并与2020、2021、2022年报告发病数进行比较分析。结果 最优模型为ARIMA(0,2,1)(1,2,0)12。预测发病数显著高于2020、2021、2022年报告发病数。2020、2021、2022年流行性腮腺炎报告发病数较预测发病数分别减少54.02%、63.40%、66.09%。结论 2020-2022年江西省流行性腮腺炎报告发病数明显低于预测发病数,考虑与非药物干预措施、免疫策略的改变等有关,建议进一步加强流行性腮腺炎监测,以更好应对流行性腮腺炎疫情。 |
English Abstract: |
Objective To predict and analyze the incidence trend of mumps using the Autoregressive integrated moving average model (ARIMA) in Jiangxi Province. Methods The ARIMA was used to model the number of mumps cases per month from 2015 to 2019 in Jiangxi Province. The number of mumps cases in 12 months was predicted and was compared with the actual reported cases in 2020, 2021, and 2022, respectively. Results The optimal model was ARIMA (0,2,1)(1,2,0)12. The predicted number of cases was significantly higher than that reported in 2020, 2021 and 2022. The number of reported cases of mumps in 2020, 2021, and 2022 decreased by 54.02%, 63.40%, and 66.09% compared with the forecast. Conclusions From 2020 to 2022, the reported incidence of mumps in Jiangxi Province was significantly lower than the predicted incidence. Considering that it was related to non-drug intervention measures and changes in immunization strategies, it was suggested to strengthen mumps surveillance further to better cope with the epidemic situation of mumps. |
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