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Meta-analysis of several epidemic characteristics of COVID-19.
Zhang, Panpan; Wang, Tiandong; Xie, Sharon X.
  • Zhang P; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA 19104, U.S.A.
  • Wang T; Department of Statistics, Texas A&M University, College Station, TX 77843, U.S.A.
  • Xie SX; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA 19104, U.S.A.
J Data Sci ; 18(3): 536-549, 2020 07.
Article in English | MEDLINE | ID: covidwho-890632
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ABSTRACT
As the COVID-19 pandemic has strongly disrupted people's daily work and life, a great amount of scientific research has been conducted to understand the key characteristics of this new epidemic. In this manuscript, we focus on four crucial epidemic metrics with regard to the COVID-19, namely the basic reproduction number, the incubation period, the serial interval and the epidemic doubling time. We collect relevant studies based on the COVID-19 data in China and conduct a meta-analysis to obtain pooled estimates on the four metrics. From the summary results, we conclude that the COVID-19 has stronger transmissibility than SARS, implying that stringent public health strategies are necessary.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Reviews Language: English Journal: J Data Sci Year: 2020 Document Type: Article Affiliation country: JDS.202007_18(3).0019

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Reviews Language: English Journal: J Data Sci Year: 2020 Document Type: Article Affiliation country: JDS.202007_18(3).0019