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
:To evaluate the impact of socioeconomic statusï¼population mobilityï¼prevention and control measures on the early-stage coronavirus disease 2019 (COVID-19) development in major cities of China. : The rate of daily new confirmed COVID-19 cases in the 51 cities with the largest number of cumulative confirmed cases as of February 19ï¼2020 (except those in Hubei province) were collected and analyzed using the time series cluster analysis. It was then assessed according to three aspectsï¼that is, socioeconomic statusï¼population mobilityï¼and control measures for the pandemic. : According to the analysis on the 51 citiesï¼4 development patterns of COVID-19 were obtainedï¼including a high-incidence pattern (in Xinyu)ï¼a late high-incidence pattern (in Ganzi)ï¼a moderate incidence pattern (in Wenzhou and other 12 cities)ï¼and a low and stable incidence pattern (in Hangzhou and other 35 cities). Cities with different types and within the same type both had different scores on the three aspects. : There were relatively large difference on the COVID-19 development among different cities in Chinaï¼possibly affected by socioeconomic statusï¼population mobility and prevention and control measures that were taken. Thereforeï¼a timely public health emergency response and travel restriction measures inside the city can interfere the development of the pandemic. Population flow from high risk area can largely affect the number of cumulative confirmed cases.