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. 2020 Aug 26;9:157–161. doi: 10.1016/j.cegh.2020.08.007

Table 1.

Characteristics of the included studies in the meta-analysis of serial interval (SI) of COVID-19.

Authors Study Area Time Period Methodology Sample Size SI 95% CI
Hiroshi Nishiura et al.19 World Up to 12th February 2020 Bayesian Approach with double interval censoring 28 4.7 3.7 6.0
Zhanwei Du et al.20 China 21st January – 8th February 2020 Fitting a normal distribution 468 3.96 3.53 4.39
Qun Li et al.21 Wuhan Up to 22nd January 2020 Fitting a gamma distribution for laboratory-confirmed cases 6 7.5 4.1 10.9
Moran Ki17 Korea Up to 20th January 2020 Calculating the mean of differences in time of symptoms 7 6.3 4.1 8.5
Juanjuan Zhang et al.22 China 19th January – 17th February 2020 Fitting a gamma distribution 35 5.1 1.3 11.6
Shi Zhao et al.23 Hong Kong 16th January – 15th February 2020 Fitting a gamma distribution 21 4.4 2.9 6.7
Ganyani Tapiwa et al.24 Singapore 21st January – 26th February 2020 Bayesian Framework 27 5.2 3.6 6.8
Ganyani Tapiwa et al.24 Tianjin (China) 14th January – 27th February 2020 Bayesian Framework 57 3.9 2.8 5.1
Shujuan Ma et al.25 Seven Countries 29th February – 2nd March 2020 Fitting a normal distribution 689 6.7 6.3 7.1
Qifang Bi et al.26 China 14th January – 12th February 2020 Fitting a gamma distribution 48 6.3 5.2 7.6
Choung You et al.27 China Up to 2nd February 2020 Calculating the mean of differences in time of symptoms 71 4.4 3.7 5.1
Menghui Li et al.28 China 21st January – 29th February 2020 Bayesian Approach with the doubly interval-censored likelihood 337 5.8 5.4 6.2