The collective wisdom in the COVID-19 research: comparison and synthesis of epidemiological parameter estimates in preprints and peer-reviewed articles.

Wang, Yuejiao; Cao, Zhidong; Zeng, Daniel Dajun; Zhang, Qingpeng; Luo, Tianyi

OBJECTIVES We aimed to explore the collective wisdom of preprints related to COVID-19 by comparing and synthesizing with results of peer-reviewed publications. METHODS PubMed, Google Scholar, medRxiv, bioRxiv, arXiv, and SSRN were searched for papers about the estimation of four epidemiological parameters of the COVID-19: the basic reproduction number, incubation period, infectious period, and case-fatality-rate. Distributions of parameters and timeliness of preprints and peer-reviewed papers were both compared. Four parameters in two groups were synthesized by bootstrap and their validities were evaluated by simulated cumulative cases of susceptible-exposed-infectious-recovered-dead-cumulative (SEIRDC) model. RESULTS 106 papers were included for analysis. The distributions of four parameters in two literature groups were close, and the timeliness of preprints was better. Synthesized estimates of the basic reproduction number (3.18, 95% CI 2.85-3.53), incubation period (5.44 days, 95% CI 4.98-5.99), infectious period (6.25 days, 95% CI 5.09-7.51), and case-fatality-rate (4.51%, 95% CI 3.41%-6.29%) were obtained. Simulated cumulative cases of SEIRDC model matched well with the onset cases in China. CONCLUSIONS The validity of the COVID-19 parameter estimations of the preprints was on par with that of peer-reviewed publications, and synthesized results of literatures could reduce the uncertainty and be used for epidemic decision making.