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Epidemiological analysis of asymptomatic SARS-CoV-2 transmission in the community: an individual-based model.
Guo, Zuiyuan; Xiao, Dan.
  • Guo Z; Department of Disease Control, Center for Disease Control and Prevention in Northern Theater Command, Shenyang, China.
  • Xiao D; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, No. 119, South 4th Ring Road West, Fengtai District, Beijing, China. danxiaoepi@163.com.
Sci Rep ; 11(1): 6251, 2021 03 18.
Article in English | MEDLINE | ID: covidwho-1142452
ABSTRACT
We established an individual-based computer model to simulate the occurrence, infection, discovery, quarantine, and quarantine release (recovery) of asymptomatic SARS-CoV-2 infected individuals or patients within the community. The model was used to explore the effects of control measures, such as active tracing, laboratory testing, active treatment, and home quarantine on the epidemic. Considering the condition that R0 = 1.2, when a case of an imported asymptomatic infected individual (AII) was reported in the community, the implementation of control measures reduced the number of AIIs and patients by 62.2% and 62.4%, respectively. The number of undetected AIIs and patients peaked at 302 days of the epidemic, reaching 53 and 20 individuals, respectively. The implementation of sustained active tracing, laboratory testing, active treatment, and home quarantine can significantly reduce the probability of disease outbreaks and block the spread of the COVID-19 epidemic caused by AIIs in the community.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Disease Outbreaks / COVID-19 / Models, Biological Type of study: Observational study Limits: Humans Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-84893-4

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Disease Outbreaks / COVID-19 / Models, Biological Type of study: Observational study Limits: Humans Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-84893-4