Meta-analysis of several epidemic characteristics of COVID-19

Published in Journal of Data Science, 2020

Recommended citation: Zhang, P., Wang T. and Xie, S. X. (2020). "Meta-analysis of several epidemic characteristics of COVID-19." Journal of Data Science, 18(3), 536--549.

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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