Early in the Epidemic: Impact of Preprints on Global Discourse of 2019-nCoV Transmissibility

Early in the Epidemic: Impact of Preprints on Global Discourse about COVID-19 Transmissibility. Lancet Glob Health. 2020 Mar 24. pii: S2214-109X(20)30113-3. doi: 10.1016/S2214-109X(20)30113-3.

12 Pages Posted: 12 Feb 2020 Last revised: 9 Apr 2020

See all articles by Maimuna S. Majumder

Maimuna S. Majumder

Boston Children's Hospital - Computational Health Informatics Program; Harvard University - Harvard Medical School

Kenneth D. Mandl

Boston Children's Hospital - Computational Health Informatics Program

Date Written: February 11, 2020

Abstract

As of February 11, 2020, more than 43,000 cases of a novel coronavirus (2019–nCoV) have been reported worldwide. Using publicly available data regarding the transmissibility potential (i.e. basic reproduction number) of 2019–nCoV, we demonstrate that relevant preprint studies generated considerable search and news media interest prior to the publication of peer-reviewed studies in the same topic area. We then show that preprint estimate ranges for the basic reproduction number associated with 2019–nCoV overlap with those presented by peer-reviewed studies that were published at a later date. Taken together, we argue that preprints are capable of driving global discourse during public health crises; however, we recommend that a consensus-based approach – as we have employed here – be considered as a means of assessing the robustness of preprint findings prior to peer review.

Keywords: novel coronavirus, preprints, transmissibility

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Suggested Citation

Majumder, Maimuna and Mandl, Kenneth D., Early in the Epidemic: Impact of Preprints on Global Discourse of 2019-nCoV Transmissibility (February 11, 2020). Early in the Epidemic: Impact of Preprints on Global Discourse about COVID-19 Transmissibility. Lancet Glob Health. 2020 Mar 24. pii: S2214-109X(20)30113-3. doi: 10.1016/S2214-109X(20)30113-3., Available at SSRN: https://ssrn.com/abstract=3536663 or http://dx.doi.org/10.2139/ssrn.3536663

Maimuna Majumder (Contact Author)

Boston Children's Hospital - Computational Health Informatics Program ( email )

United States

Harvard University - Harvard Medical School ( email )

25 Shattuck St
Boston, MA 02115
United States

Kenneth D. Mandl

Boston Children's Hospital - Computational Health Informatics Program ( email )

300 Longwood Avenue
LANDMARK 5506, MAIL STOP BCH3187
Boston, MA n/a 02215
United States
6173554145 (Phone)
02115 (Fax)

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