Global Research on Coronaviruses: A Metadata-Based Analysis for Public Health Policies.

Warin, Thierry

BACKGROUND Within the context of the COVID-19 pandemic, this article suggests a data science strategy for analyzing global research on coronaviruses. The application of reproducible research principles founded on text-as-data, open science, the dissemination of scientific data, and easy access to scientific production may aid public health in the fight against the virus. OBJECTIVE The primary goal of this article is to use global research on coronaviruses to identify critical elements that can help inform public health policy decisions. We present a data science framework to assist policymakers in implementing cutting-edge data science techniques for the purpose of developing evidence-based public health policies. METHODS We use the EpiBibR package to gain access to coronavirus research documents worldwide (n = 121,231) and their associated metadata. To analyze these data, we first employ a theoretical framework to group the findings into three categories: conceptual, intellectual, and social. Second, we map the results of our analysis in these three dimensions using machine learning techniques (natural language processing) and social network analysis. RESULTS Our findings are first methodological in nature. They demonstrate the potential for the proposed data science framework to be applied to public health policies. Additionally, our findings indicate that the United States and China are the primary contributors to global coronavirus research. They also demonstrate that India and Europe are significant contributors, albeit in a secondary position. University collaborations in this domain are strong between the United States, Canada, and the United Kingdom, confirming the country-level findings. CONCLUSIONS Our findings argue for a data-driven approach to public health policy, particularly when efficient and relevant research is required. Text mining techniques can assist policymakers in calculating evidence-based indices and informing their decision-making process regarding specific actions necessary for effective health responses. CLINICALTRIAL