ABSTRACT
:To predict the epidemiological trend of coronavirus disease 2019 (COVID-19) by mathematical modeling based on the population mobility and the epidemic prevention and control measures. : As of February 8ï¼2020ï¼the information of 151 confirmed cases in Yueqingï¼Zhejiang province were obtainedï¼including patients' infection processï¼population mobility between Yueqing and Wuhanï¼etc. To simulate and predict the development trend of COVID-19 in Yueqing, the study established two-stage mathematical modelsï¼integrating the population mobility data with the date of symptom appearance of confirmed cases and the transmission dynamics of imported and local cases. : It was found that in the early stage of the pandemicï¼the number of daily imported cases from Wuhan (using the date of symptom appearance) was positively associated with the number of population travelling from Wuhan to Yueqing on the same day and 6 and 9 days before that. The study predicted that the final outbreak size in Yueqing would be 170 according to the number of imported cases estimated by consulting the population number travelling from Wuhan to Yueqing and the susceptible-exposed-infectious-recovered (SEIR) model; while the number would be 165 if using the reported daily number of imported cases. These estimates were close to the 170ï¼the actual monitoring number of cases in Yueqing as of April 27ï¼2020. : The two-stage modeling approach used in this study can accurately predict COVID-19 epidemiological trend.
Subject(s)
COVID-19 , China/epidemiology , Disease Outbreaks , Humans , Models, Theoretical , Pandemics , SARS-CoV-2ABSTRACT
This study aimed to quantitatively assess the effectiveness of the Wuhan lockdown measure on controlling the spread of coronavirus diesase 2019 (COVID-19). : Firstlyï¼estimate the daily new infection rate in Wuhan before January 23ï¼2020 when the city went into lockdown by consulting the data of Wuhan population mobility and the number of cases imported from Wuhan in 217 cities of Mainland China. Then estimate what the daily new infection rate would have been in Wuhan from January 24 to January 30th if the lockdown measure had been delayed for 7 daysï¼assuming that the daily new infection in Wuhan after January 23 increased in a highï¼moderate and low trend respectively (using exponential, linear and logarithm growth models). Based on thatï¼calculate the number of infection cases imported from Wuhan during this period. Finallyï¼predict the possible impact of 7-day delayed lockdown in Wuhan on the epidemic situation in China using the susceptible-exposed-infectious-removed (SEIR) model. : The daily new infection rate in Wuhan was estimated to be 0.021%ï¼0.026%ï¼0.029%ï¼0.033% and 0.070% respectively from January 19 to January 23. And there were at least 20 066 infection cases in Wuhan by January 23ï¼2020. If Wuhan lockdown measure had been delayed for 7 daysï¼the daily new infection rate on January 30 would have been 0.335% in the exponential growth modelï¼0.129% in the linear growth modelï¼and 0.070% in the logarithm growth model. Correspondinglyï¼there would have been 32 075ï¼24 819 and 20 334 infection cases travelling from Wuhan to other areas of Mainland Chinaï¼and the number of cumulative confirmed cases as of March 19 in Mainland China would have been 3.3-3.9 times of the officially reported number. Conclusions: Timely taking city-level lockdown measure in Wuhan in the early stage of COVID-19 outbreak is essential in containing the spread of the disease in China.