ABSTRACT
Introduction: To compare the performance between the compartment model and the autoregressive integrated moving average (ARIMA) model that were applied to the prediction of new infections during the coronavirus disease 2019 (COVID-19) epidemic. Methods: The compartment model and the ARIMA model were established based on the daily cases of new infection reported in China from December 2, 2019 to April 8, 2020. The goodness of fit of the two models was compared using the coefficient of determination (R2). Results: The compartment model predicts that the number of new cases without a cordon sanitaire, i.e., a restriction of mobility to prevent spread of disease, will increase exponentially over 10 days starting from January 23, 2020, while the ARIMA model shows a linear increase. The calculated R2 values of the two models without cordon sanitaire were 0.990 and 0.981. The prediction results of the ARIMA model after February 2, 2020 have a large deviation. The R2 values of complete transmission process fit of the epidemic for the 2 models were 0.964 and 0.933, respectively. Discussion: The two models fit well at different stages of the epidemic. The predictions of compartment model were more in line with highly contagious transmission characteristics of COVID-19. The accuracy of recent historical data had a large impact on the predictions of the ARIMA model as compared to those of the compartment model.
ABSTRACT
Introduction: The aim of this study was to construct an assessment method for cross-regional transmission of coronavirus disease 2019 (COVID-19) and to provide recommendations for optimizing measures such as interregional population movements. Methods: Taking Xi'an City as the example subject of this study's analysis, a Cross-Regional-Gravitational-Dynamic model was constructed to simulate the epidemic in each district of Xi'an under three scenarios of controlled population movement (Scenario 1: no intensive intervention; Scenario 2: blocking Yanta District on December 18 and blocking the whole region on December 23; and Scenario 3: blocking the whole region on December 23). This study then evaluated the effects of such simulated population control measures. Results: The cumulative number of cases for the three scenarios was 8,901,425, 178, and 474, respectively, and the duration of the epidemic was 175, 18, and 22 days, respectively. The real world prevention and control measures in Xi'an reduced the cumulative number of cases for its outbreak by 99.98% in comparison to the simulated response in Scenario 1; in contrast, the simulated prevention and control strategies set in Scenarios 2 (91.26%) and 3 (76.73%) reduced cases even further than the real world measures used in Xi'an. Discussion: The constructed model can effectively simulate an outbreak across regions. Timely implementation of two-way containment and control measures in areas where spillover is likely to occur is key to stopping cross-regional transmission.