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Meta-Analysis of Several Epidemic Characteristics of COVID-19
Volume 18, Issue 3 (2020): Special issue: Data Science in Action in Response to the Outbreak of COVID-19, pp. 536–549
Panpan Zhang   Tiandong Wang   Sharon X. Xie  

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https://doi.org/10.6339/JDS.202007_18(3).0019
Pub. online: 4 August 2022      Type: Research Article      Open accessOpen Access

Published
4 August 2022

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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Keywords
basic reproduction number epidemic doubling time incubation period sensitivity analysis serial interval

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Journal of data science

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