Evaluation and prediction of the COVID-19 variations at different input population and quarantine strategies, a case study in Guangdong province, China

Abstract In this study, an epidemic model was developed to simulate and predict the disease variations of Guangdong province which was focused on the period from Jan 27 to Feb 20, 2020. To explore the impacts of the input population and quarantine strategies on the disease variations at different scenarios, four time points were assumed as Feb 6, Feb 16, Feb 24 and Mar 5 2020. The major results suggest that our model can well capture the disease variations with high accuracy. The simulated peak value of the confirmed cases is 1002 at Feb 10, 2020 which is mostly close to the reported number of 1007 at Feb 9, 2020. The disease will become extinction with peak value of 1397 at May 11, 2020. Moreover, the increased numbers of the input population can mainly shorten the disease extinction days and the increased percentages of the exposed individuals of the input population increase the number of cumulative confirmed cases at a small percentage. Increasing the input population and decreasing the quarantine strategy together around the time point of the peak value of the confirmed cases, may lead to the second outbreak.

[1]  Zengyun Hu,et al.  Evaluation of reanalysis, spatially interpolated and satellite remotely sensed precipitation data sets in central Asia , 2016 .

[2]  L. Yang,et al.  Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak , 2020, International Journal of Infectious Diseases.

[3]  Qiming Zhou,et al.  DISO: A rethink of Taylor diagram , 2019, International Journal of Climatology.

[4]  W. Jianhong,et al.  Analysis of COVID-19 epidemic traced data and stochastic discrete transmission dynamic model , 2020 .

[5]  Jianhong Wu,et al.  Estimation of the Transmission Risk of the 2019-nCoV and Its Implication for Public Health Interventions , 2020, Journal of clinical medicine.

[6]  K. Yuen,et al.  Clinical Characteristics of Coronavirus Disease 2019 in China , 2020, The New England journal of medicine.

[7]  Peng Zhihang,et al.  Studies of the strategies for controlling the COVID-19 epidemic in China: Estimation of control efficacy and suggestions for policy makers , 2020, SCIENTIA SINICA Mathematica.

[8]  Yongli Cai,et al.  A conceptual model for the coronavirus disease 2019 (COVID-19) outbreak in Wuhan, China with individual reaction and governmental action , 2020, International Journal of Infectious Diseases.

[9]  Daozhou Gao,et al.  Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak , 2020, Journal of clinical medicine.

[10]  Jessica T Davis,et al.  The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak , 2020, Science.

[11]  G. Leung,et al.  Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study , 2020, The Lancet.