Predicting COVID-19 epidemiological trend by applying population mobility data in two-stage modeling.
Zhejiang Da Xue Xue Bao Yi Xue Ban
; 50(1): 68-73, 2021 02 25.
Article
in English
| MEDLINE | ID: covidwho-1266777
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.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
COVID-19
Type of study:
Observational study
/
Prognostic study
Limits:
Humans
Country/Region as subject:
Asia
Language:
English
Journal:
Zhejiang Da Xue Xue Bao Yi Xue Ban
Journal subject:
Medicine
Year:
2021
Document Type:
Article
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