An Open-Publishing Response to the COVID-19 Infodemic

TL;DR

This paper demonstrates how open online publishing using Manubot enabled a large, multidisciplinary team to collaboratively review and synthesize over 1,500 COVID-19 sources rapidly and transparently during the pandemic.

Contribution

It introduces a scalable, automated open publishing workflow for real-time scientific collaboration and dissemination during a global health crisis.

Findings

Organized over 50 scientists across disciplines.

Evaluated more than 1,500 sources.

Produced seven comprehensive literature reviews.

Abstract

The COVID-19 pandemic catalyzed the rapid dissemination of papers and preprints investigating the disease and its associated virus, SARS-CoV-2. The multifaceted nature of COVID-19 demands a multidisciplinary approach, but the urgency of the crisis combined with the need for social distancing measures present unique challenges to collaborative science. We applied a massive online open publishing approach to this problem using Manubot. Through GitHub, collaborators summarized and critiqued COVID-19 literature, creating a review manuscript. Manubot automatically compiled citation information for referenced preprints, journal publications, websites, and clinical trials. Continuous integration workflows retrieved up-to-date data from online sources nightly, regenerating some of the manuscript's figures and statistics. Manubot rendered the manuscript into PDF, HTML, LaTeX, and DOCX outputs, immediately updating the version available online upon the integration of new content. Through this effort, we organized over 50 scientists from a range of backgrounds who evaluated over 1,500 sources and developed seven literature reviews. While many efforts from the computational community have focused on mining COVID-19 literature, our project illustrates the power of open publishing to organize both technical and non-technical scientists to aggregate and disseminate information in response to an evolving crisis.