| 自回归求和滑动平均(ARIMA)模型在全球新型冠状病毒肺炎发病人数预测中的应用 |
| |
| 引用本文： | 包娅薇, 邵明, 陈雨婷, 刘旭祥, 丁晓芹, 潘贵霞, 潘发明, 李小静. 自回归求和滑动平均(ARIMA)模型在全球新型冠状病毒肺炎发病人数预测中的应用[J]. 中华疾病控制杂志, 2020, 24(5): 543-548. doi: 10.16462/j.cnki.zhjbkz.2020.05.010 |
| |
| 作者姓名： | 包娅薇 邵明 陈雨婷 刘旭祥 丁晓芹 潘贵霞 潘发明 李小静 |
| |
| 作者单位： | 1.230022 合肥, 安徽医科大学第一附属医院整形外科;2.230032 合肥, 安徽医科大学公共卫生学院流行病与卫生统计学系;3.230000 合肥, 合肥市疾病预防控制中心230000 |
| |
| 摘 要： | 目的 应用自回归求和滑动平均(autoregressive integrated moving average, ARIMA)模型对全球新型冠状病毒肺炎(coronavirus disease 2019, COVID-19)发病人数进行预测, 为各国提出的防控策略与措施提供参考和评价依据。 方法 收集2020年2月22日-3月19日各国(意大利、西班牙、德国、法国等)COVID-19每日累计确诊人数, 用SPSS 17.0和R 3.6.1软件拟合ARIMA模型, 对5日前数据进行回带评价拟合效果, 同时利用该模型预测各国后10日数据。 结果 ARIMA模型预测值和实际值动态趋势基本一致, 实际值在预测值的95%CI内。 结论 ARIMA模型能够较好的对全球COVID-19发病人数进行预测, 在指导疫情防控方面有实际意义。
|
| 关 键 词： | ARIMA模型 COVID-19 累计确诊人数 预测 |
| 收稿时间： | 2020-03-22 |
| 修稿时间： | 2020-03-25 |
Application of autoregressive integrated moving average (ARIMA) model in global prediction of COVID-19 incidence |
| |
| BAO Ya-wei, SHAO Ming, CHEN Yu-ting, LIU Xu-xiang, DING Xiao-qin, PAN Gui-xia, PAN Fa-ming, LI Xiao-jing. Application of autoregressive integrated moving average (ARIMA) model in global prediction of COVID-19 incidence[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2020, 24(5): 543-548. doi: 10.16462/j.cnki.zhjbkz.2020.05.010 |
| |
| Authors: | BAO Ya-wei SHAO Ming CHEN Yu-ting LIU Xu-xiang DING Xiao-qin PAN Gui-xia PAN Fa-ming LI Xiao-jing |
| |
| Affiliation: | 1. Department of Plastic Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China;2. Department of Epidemiology and Biostatisticst School of Public Health, Anhui Medical University, Hefei 230032, China;3. Hefei Center for Disease Control and Prevention, Hefei 230032, China |
| |
| Abstract: | Objective Autoregressive integrated moving average(ARIMA) model was used to predict the incidence of coronavirus disease 2019(COVID-19) in the world, providing reference and evaluation basis for prevention and control strategies and measures proposed by various countries. Methods The cumulative daily number of confirmed COVID-19 patients in various countries(Italy, Spain, Germany, France, and et al) on February 22, 2020(solstice, March 19) was collected. The ARIMA model was fitted with SPSS17.0 and R3.6.1 software. Results The dynamic trend of the predicted and actual values of ARIMA model is basically consistent, and the actual values are within the 95% confidence interval(CI) of the predicted values. Conclusion ARIMA model can better predict the incidence of COVID-19 globally, which has practical significance in guiding epidemic prevention and control. |
| |
| Keywords: | ARIMA model COVID-19 Cumulative number of confirmed cases Prediction |
| 本文献已被 维普 万方数据 等数据库收录！ |
| 点击此处可从《中华疾病控制杂志》浏览原始摘要信息 |
|
点击此处可从《中华疾病控制杂志》下载免费的PDF全文 |
|
