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

doi:10.16462/j.cnki.zhjbkz.2020.05.010

Volume 24 Issue 5

Jul. 2020

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Article Navigation > CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION > 2020 > 24(5): 543-548

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

Citation:

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

Citation:

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

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Application of autoregressive integrated moving average (ARIMA) model in global prediction of COVID-19 incidence

doi: 10.16462/j.cnki.zhjbkz.2020.05.010

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

BAO Ya-wei and SHAO Ming contributed equally to this article

More Information

Corresponding author: PAN Fa-ming, E-mail:famingpan@ahmu.edu.cn; LI Xiao-jing, E-mail:ay_lxj@yahoo.com
Received Date: 2020-03-22
Rev Recd Date: 2020-03-25
Publish Date: 2020-05-10

Abstract

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.
- ARIMA model,
- COVID-19,
- Cumulative number of confirmed cases,
- Prediction

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References(13)

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