Forecasting the Trend of COVID-19 Considering the Impacts of Public Health Interventions: An Application of FGM and Buffer Level

Kai Lisa Lo; Minglei Zhang; Yanhui Chen; Jinhong Jackson Mi

doi:10.1007/s41666-021-00103-w

Forecasting the Trend of COVID-19 Considering the Impacts of Public Health Interventions: An Application of FGM and Buffer Level

J Healthc Inform Res. 2021;5(4):497-528. doi: 10.1007/s41666-021-00103-w. Epub 2021 Sep 7.

Authors

Kai Lisa Lo¹, Minglei Zhang¹, Yanhui Chen¹, Jinhong Jackson Mi¹

Affiliation

¹ School of Economics and Management, Shanghai Maritime University, No. 1550 Haigang Avenue, Pudong, Shanghai, People's Republic of China.

Abstract

Purpose: COVID-19 is still showing a tendency of spreading around the world. In order to improve the subsequent control of COVID-19, it is essential to conduct a study on measuring and predicting the scale of the outbreak in the future.

Methods: This paper uses rolling mechanism and grid search to find the best fractional order of Fractional Order Accumulation Grey Model (FGM). Buffer level is proposed based on the general form of weakening buffer operator to measure the effect of government control measurements on the epidemic. And the buffer level is associated with the Government Response Stringency index and the Mobility Index.

Results: Firstly, the model proposed in this paper dominates the ARIMA model which has been widely used in predicting the confirmed COVID-19 cases. Secondly, in the process of using the buffer level to modify the FGM, this paper finds that government measurements require the active cooperation of the public and often have a time lag when they are effective. Only when government increase its stringency and the public observe the order can the spread of COVID-19 be slowed down. If there is only the controlling measure and the public does not react actively, it will not slow down the epidemic. Thirdly, according to the Mobility Index and Government Response Stringency Index in December, this paper predicts the cumulative confirmed cases of the end of January in different scenarios according to different buffer levels. The study suggests that the world should continue to maintain high vigilance and take corresponding control measures for the outbreak of COVID-19.

Conclusions: Government's control measures and public's abidance are both important in this battle with COVID-19. Governments control measures have time-lag effect and the time lag is about 9 days. When the government increases its stringency and the public cooperates with the government, we must consider the weaken buffer operator with proper buffer level in the prediction process. These prediction methods can be considered in the prediction of COVID-19 confirmed cases in the future or the trend of other epidemics.

Keywords: Buffer level; COVID-19; Fractional order accumulation grey model (FGM); Grey system.