Evidence-Based Medicine in a Pandemic: Open Science Resources for COVID-19

Evidence-based medicine (EBM) involves the “conscientious and judicious” review and appraisal of available evidence in the making of medical decisions. In the best situations, EBM is a necessary but time-consuming step in the diagnosis, treatment, and prognosis of patients. But in the face of a novel virus pandemic, a virus with no known treatment, with imperfect diagnostic tests, and public health interventions developed on the fly, and with little to no time to peer review, EBM becomes even more challenging and more important. The effects of the COVID-19 pandemic on information access and dissemination include the development of Rapid Reviews by several organizations, and highlight the need for open science initiatives and the importance of pre-print servers. This post provides some of these resources for use by clinicians, students, and researchers.


The response to a pandemic cannot wait for the standard peer review process to play out. Hence we have seen the rise in use of preprints. Preprints are versions of papers that are complete and made public prior to peer review and publication in a journal. Preprint servers, for decades the standard for disseminating Physics (aRxiv, now maintained at Cornell University) and other information, have taken longer to take full hold in Biology and Medicine, but COVID-19 will likely have a lasting impact on their use. By posting preprints to one of these servers, authors are able to make their findings immediately available and receive feedback on manuscripts from the scientific community. Readers need to use caution and critically appraise extra carefully as preprints have not been subjected to peer review.


With so much information being generated so quickly as science and medicine race to find answers, various organizations are making sense of all of this research in the form of rapid reviews. “Rapid reviews” are a form of knowledge synthesis in which components of the systematic review process are simplified or omitted to produce information in a timely manner.1  Note that these do not use the same level of rigor as a systematic review so there is potential bias introduced, so these are best reserved for when time is crucial. Here are some examples.


  • COVID-19 Open Research Dataset (CORD-19) https://pages.semanticscholar.org/coronavirus-research is a free resource of over 52,000 scholarly articles, including over 41,000 with full text, about COVID-19 and the coronavirus family of viruses for use by the global research community.
  • LitCovid https://www.ncbi.nlm.nih.gov/research/coronavirus/ NLM’s hub for tracking COVID-19 information. From the site: “LitCovid is a curated literature hub for tracking up-to-date scientific information about the 2019 novel Coronavirus. It is the most comprehensive resource on the subject, providing a central access to 5645 (and growing) relevant articles in PubMed. The articles are updated daily and are further categorized by different research topics and geographic locations for improved access. You can read more at Chen et al. Nature (2020) and download our data here.”   

Khangura S, Konnyu K, Cushman R, Grimshaw J, Moher D. Evidence summaries: the evolution of a rapid review approach. Syst Rev. 2012;1:10. doi:10.1186/2046-4053-1-10.


This site uses Akismet to reduce spam. Learn how your comment data is processed.