How Have Global Scientists Responded to Tackling COVID-19?

Abstract

Since the outbreak of COVID-19, the global scientific communities across almost all countries have made urgent, intensive, and continuous effort on understanding, fighting and modeling the COVID-19 pandemic. COVID-19 research turns out to be the first overwhelming global scientific reaction to significant global crises and threats. This literature analysis report collects and summarizes the profiles, trends, quality and impact of this global scientific response. It collects and analyzes 346,267 scientific references in English, involving researchers from 189 countries and regions in 27 subject areas. The report generates a picture of how global scientists have responded to COVID-19 between Jan 2020 and Mar 2022 in terms of their publication quantity, impact, focused major problems, and research areas and methods over country/region, discipline and time and collaboratively. The report also captures broad-reaching distributions and trends of modeling COVID-19 by AI, data science, analytics, shallow and deep machine learning, epidemic modeling, applied mathematics, and social science methods, etc. We further show the correlations between publication quality and quantity and economic status and COVID-19 infections globally and in major countries and regions. The literature analysis results of this global scientific response to COVID-19 present a comprehensive global, regional and subject-specific picture of the significant cross-disciplinary, cross-country, cross-problem, and cross-technique profiles and differences of the COVID-19 publication quantity and quality. The report also discloses significant imbalances in the COVID-19 research across countries/regions, subject areas, problems, topics, methods, research collaborations, and economic statuses. We share the source and analytical data of this global literature analysis for further research on this unprecedented and future crises.

AI in Combating the COVID-19 Pandemic

“…Out of the 36,830 AI-related studies in the literature, 4 17,499 are on AI for medical science, 5089 are from computer science, and 3283 are from social science (SSRN-based). An analysis of these manuscripts using natural language processing reveals the following results.…”

“…17 However, the commitment from each country is very biased and imbalanced in the researched problems and techniques. 4 Figure 6 shows the number of first-authored publications of the top-10 countries on top-10 business problems using top-10 focused methods. Their primary technical interests are in regression, SIR models, and classic and deep machine learning.…”

“…In this article, I would like to share my shallow observations on these issues, building on my systematic review of AI against COVID-19, in particular, data-driven COVID-19 modeling 3 and global scientist efforts. 4 The main motivation of this article is to encourage deeper and wider AI attention, thinking, and developments in containing COVID-19, future pandemics, natural and social disasters, and other significant challenges, including those highly improbable or even unimaginable events (so-called "gray rhino" and "black swan" events), and being prepared to intervene in their consequences and impact.…”

“…We have conducted a comprehensive literature review of how global scientists responded to tackling COVID-19. 3,4 We collected and analyzed 281,718 formal publications and 24,271 preprints made by global scientists on COVID-19 from Web of Science, Scopus, SSRN, and medical repositories from January 2020 to December 13, 2021. b Firstauthored researchers from 172 countries and regions have committed to constituting this body of knowledge on COVID-19, as shown in Figure 1. Of these 305,989 manuscripts, 38,730 are related to AI, with 5095 AI-related publications from computer science, 17,499 from medical science, and 3283 from social science.…”

“…The major issues are COVID-19 mental health, mortality prediction, lockdown, anxiety, vaccine, public health, X-ray, depression, spread prediction, and risk factors. The intensive interest in case and transmission prediction in the middle stage has been substantially reduced, replaced by an increasing studies on vaccines and mental health.However, the commitment from each country is very biased and imbalanced in the researched problems and techniques 4. Figure6shows the number of first-authored publications of the top-10 countries on top-10 business problems using top-10 focused methods.…”