Publishing of COVID-19 Preprints in Peer-reviewed Journals, Preprinting Trends, Public Discussion and Quality Issues (preprint)

IntroductionCOVID-19-related (vs. non-related) articles appear to be more expeditiously processed and published in peer-reviewed journals. We aimed to evaluate: (i) whether COVID-19-related preprints were favoured for publication, (ii) preprinting trends and public discussion of the preprints and (iii) relationship between the publication topic (COVID-19-related or not) and quality issues. MethodsManuscripts deposited at bioRxiv and medRxiv between January 1 and October 21 were assessed for the probability of publishing in peer-reviewed journals, and those published were evaluated for submission-to-acceptance time. The extent of public discussion was assessed based on Altmetric and Disqus data. The Retraction Watch database and PubMed were used to explore the retraction of COVID-19 and non-COVID-19 articles and preprints. ResultsWith adjustment for the preprinting server and number of deposited versions, COVID-19-related preprints were more likely to be published within 120 days since the deposition of the first version (OR=1.99, 95%CI 1.76-2.25) as well as over the entire observed period (OR=1.49, 95%CI 1.36-1.62). Submission-to-acceptance was by 41.69 days (95%CI 46.56-36.80) shorter for COVID-19 articles. Public discussion of preprints was modest and COVID-19 articles were overrepresented in the pool of retracted articles in 2020. ConclusionCurrent data suggest a preference for publication of COVID-19-related preprints over the observed period.

World Health Organization (WHO) COVID-19 Database: Who Needs It? (preprint)

Introduction: A large number of COVID-19 publications has created a need to collect all research-related material in practical and reliable centralized databases. The aim of this study was to evaluate the functionality and quality of the compiled World Health Organisation COVID-19 database and compare it to Pubmed and Scopus. Methods: Article metadata for COVID-19 articles and articles on 8 specific topics related to COVID-19 was exported from the WHO global research database, Scopus and Pubmed. The analysis was conducted in R to investigate the number and overlapping of the articles between the databases and the missingness of values in the metadata. Results: The WHO database contains the largest number of COVID-19 related articles overall but retrieved the same number of articles on 8 specific topics as Scopus and Pubmed. Despite having the smallest number of exclusive articles overall, the highest number of exclusive articles on specific COVID-19 related topics was retrieved from the Scopus database. Further investigation revealed that PubMed and Scopus have more comprehensive structure than the WHO database, and less missing values in the categories searched by the information retrieval systems. Discussion: This study suggests that the WHO COVID-19 database, even though it is compiled from multiple databases, has a very simple and limited structure, and significant problems with data quality. As a consequence, relying on this database as a source of articles for systematic reviews or bibliometric analyses is undesirable.

Preliminary Analysis of COVID-19 Academic Information Patterns: A Call for Open Science in the Times of Closed Borders (preprint)

Introduction: The Pandemic of COVID-19, an infectious disease caused by SARS-CoV-2 motivated the scientific community to work together in order to gather, organize, process and distribute data on the novel biomedical hazard. Here, we analyzed how the scientific community responded to this challenge by quantifying distribution and availability patterns of the academic information related to COVID-19. The aim of our study was to assess the quality of the information flow and scientific collaboration, two factors we believe to be critical for finding new solutions for the ongoing pandemic. Materials and methods: The RISmed R package, and a custom Python script were used to fetch metadata on articles indexed in PubMed and published on Rxiv preprint server. Scopus was manually searched and the metadata was exported in BibTex file. Publication rate and publication status, affiliation and author count per article, and submission-to-publication time were analysed in R. Biblioshiny application was used to create a world collaboration map. Results: Our preliminary data suggest that COVID-19 pandemic resulted in generation of a large amount of scientific data, and demonstrates potential problems regarding the information velocity, availability, and scientific collaboration in the early stages of the pandemic. More specifically, our results indicate precarious overload of the standard publication systems, significant problems with data availability and apparent deficient collaboration. Conclusion: In conclusion, we believe the scientific community could have used the data more efficiently in order to create proper foundations for finding new solutions for the COVID-19 pandemic. Moreover, we believe we can learn from this on the go and adopt open science principles and a more mindful approach to COVID-19-related data to accelerate the discovery of more efficient solutions. We take this opportunity to invite our colleagues to contribute to this global scientific collaboration by publishing their findings with maximal transparency.