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Estimation of the Outbreak Severity and Evaluation of Epidemic Prevention Ability of COVID-19 by Province in China
American Journal of Public Health ; 110(12):1837-1843, 2020.
Article in English | ProQuest Central | ID: covidwho-1017821
ABSTRACT
Objectives. To compare the epidemic prevention ability of COVID-19 of each province in China and to evaluate the existing prevention and control capacity of each province. Methods. We established a quasi-Poisson linear mixed-effects model using the case data in cities outside Wuhan in Hubei Province, China. We adapted this model to estimate the number of potential cases in Wuhan and obtained epidemiological parameters. We estimated the initial number of cases in each province by using passenger flowrate data and constructed the extended susceptible-exposed-infectious-recovered model to predict the future disease transmission trends. Results. The estimated potential cases in Wuhan were about 3 times the reported cases. The basic reproductive number was 3.30 during the initial outbreak. Provinces with more estimated imported cases than reported cases were those in the ing provinces Hubei, including Henan and Shaanxi. The regions where the number of reported cases was closer to the predicted value were most the developed areas, including Beijing and Shanghai. Conclusions. The number of confirmed cases in Wuhan was underestimated in the initial period of the outbreak. Provincial surveillance and emergency response capabilities vary across the country. (Am J Public Health. 2020;1101837-1843. https// doi.org/10.2105/AJPH.2020.305893)

Full text: Available Collection: Databases of international organizations Database: ProQuest Central Type of study: Experimental Studies / Prognostic study Language: English Journal: American Journal of Public Health Year: 2020 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: ProQuest Central Type of study: Experimental Studies / Prognostic study Language: English Journal: American Journal of Public Health Year: 2020 Document Type: Article