The early scientific literature response to the novel Coronavirus outbreak: who published what?

  1. Davide Gori
  2. Erik Boetto
  3. Maria Pia Fantini

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Introduction

Recent events highlight how emerging and re-emerging pathogens are becoming global challenges for public health. In December 2019, a novel coronavirus has emerged. This has suddenly turned out into global health concern.

Objectives

Aim of this research is to focus on the bibliometric aspects in order to measure what is published in the first 30-days of a global epidemic outbreak

Methods

We searched PubMed database in order to find all relevant studies in the first 30-days from the first publication.

Results

From the initial 442 identified articles, 234 were read in-extenso. The majority of papers come from China, UK and USA. 63.7% of the papers were commentaries, editorials and reported data and only 17.5% of the sources used data directly collected on the field. Topics mainly addressed were “epidemiology”, “preparedness” and “generic discussion”. NNR showed a reduction for both the objectives assessed from January to February.

Conclusions

“Diagnosis” and effective preventive and therapeutic measures were the fields in which more research is still needed. The vast majority of scientific literature in the first 30-days of an epidemic outbreak is based on reported data rather than primary data. Nevertheless, the scientific statements and public health decisions rely on these data.

Strengths of our study

This is the first bibliometric research in Pubmed Database on the first 30 days of publications regarding the novel Coronavirus (SARS-nCoV-2) outbreak of 2019.

The vast majority of publication in the first 30-days of an epidemic outbreak are reported data or comments, and only a small fraction of the papers have directly collected data.

Limitations of our study

Our research is only PubMed based. It ill be auspicable to consult more than one relevant database in future papers.

In addition, we excluded non-English publications leading to a potential bias due to the fact that the outbreak started in China.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.03.25.20043315: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: The virus name was updated from “2019-nCoV” to “SARS-CoV-2” by the International Committee on Taxonomy of Viruses on 11 February 2020, [16] yet we performed the search using the term “nCoV” since we presumed that no paper published between 11 February 2020 and 13 February 2020 would have used the term “SARS-COV-2”.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Electronic searches: We searched MEDLINE (PubMed) electronic database in order to find all relevant studies.
    MEDLINE
    suggested: (MEDLINE, RRID:SCR_002185)
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Chi2 test was used in order to test for significant differences in the comparison of percentages, using the statistical software STATA 15 (StataCorp. 2017. Stata Statistical Software: Release 15.
    STATA
    suggested: (Stata, RRID:SCR_012763)
    StataCorp
    suggested: (Stata, RRID:SCR_012763)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    There are several limitations in our study. First, we based our research only on PubMed, that does not index all of the scientific impacted journals. It is strongly recommended to consult more than one relevant database when performing systematic reviews of the literature, [25] even though it has been reported that most of the high-quality articles, like those included in Cochrane Reviews, are indexed in PubMed. [26] In addition, we excluded all the publications not in English. We acknowledge that, given the outbreak started in China, this may have led to a partial selection bias. Nevertheless, papers excluded which were written in Chinese and had an English abstract, were for the greatest part reports of the Chinese Government (data not shown). We considered only the articles published until 13 February 2020, and taking into account that literature is now changing day-by-day for this topic, extending the bibliometric research for the next months would be of paramount importance. In conclusion, as far as we know, our very early review is the first bibliometric study analyzing the early scientific research output about COVID-19 from a quantitative and descriptive standpoint. Due to the huge amount of interest and concern related to this outbreak, our analysis shows that the scientific publication has been very reactive but still preliminar, with an expected deficit of original data and an excess of editorials and commentaries. Further research is needed to review and synthesiz...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.03.25.20043315v1 on medRxiv