Abstract
Background: Given the worldwide spread of the 2019 Novel Coronavirus (COVID-19), there is an urgent need to identify risk and protective factors and expose areas of insufficient understanding. Emerging tools, such as the Rapid Evidence Map (rEM), are being developed to systematically characterize large collections of scientific literature. We sought to generate an rEM of risk and protective factors to comprehensively inform areas that impact COVID-19 outcomes for different sub-populations in order to better protect the public.Methods: We developed a protocol that includes a study goal, study questions, a PECO statement, and a process for screening literature by combining semi-automated machine learning with the expertise of our review team. We applied this protocol to reports within the COVID-19 Open Research Dataset (CORD-19) that were published in early 2020. SWIFT-Active Screener was used to prioritize records according to pre-defined inclusion criteria. Relevant studies were categorized by risk and protective status; susceptibility category (Behavioral, Physiological, Demographic, and Environmental); and affected sub-populations. Using tagged studies, we created an rEM for COVID-19 susceptibility that reveals: (1) current lines of evidence; (2) knowledge gaps; and (3) areas that may benefit from systematic review.Results: We imported 4,330 titles and abstracts from CORD-19. After screening 3,521 of these to achieve 99% estimated recall, 217 relevant studies were identified. Most included studies concerned the impact of underlying comorbidities (Physiological); age and gender (Demographic); and social factors (Environmental) on COVID-19 outcomes. Among the relevant studies, older males with comorbidities were commonly reported to have the poorest outcomes. We noted a paucity of COVID-19 studies among children and susceptible sub-groups, including pregnant women, racial minorities, refugees/migrants, and healthcare workers, with few studies examining protective factors.Conclusion: Using rEM analysis, we synthesized the recent body of evidence related to COVID-19 risk and protective factors. The results provide a comprehensive tool for rapidly elucidating COVID-19 susceptibility patterns and identifying resource-rich/resource-poor areas of research that may benefit from future investigation as the pandemic evolves.
Highlights
Since the emergence of the novel coronavirus (COVID-19) in late 2019, there has been great interest in what can be learned about this virus and what can be done to slow its spread
We found a general lack of studies examining COVID-19 protective factors, we were able to identify some literature suggesting that younger age, Bacillus Calmette-Guerin (BCG) childhood vaccination, blood type O, and Estradiol and Anti- Müllerian Hormone may confer protective effects against contracting COVID-19
We identified research areas in which there exists a moderate body of literature where a follow-up review, such as a systematic review, may be informative and areas where evidence is lacking
Summary
Since the emergence of the novel coronavirus (COVID-19) in late 2019, there has been great interest in what can be learned about this virus and what can be done to slow its spread. In order to quickly synthesize published research on COVID-19 risk and protective factors in humans, we sought to conduct a rapid Evidence Map (rEM) [1] of literature published between January 1, 2020–April 3, 2020. Evidence maps result from a systematic search of a broad field and are undertaken to identify gaps in knowledge and guide future research needs. Given the worldwide spread of the 2019 Novel Coronavirus (COVID-19), there is an urgent need to identify risk and protective factors and expose areas of insufficient understanding. Emerging tools, such as the Rapid Evidence Map (rEM), are being developed to systematically characterize large collections of scientific literature. We sought to generate an rEM of risk and protective factors to comprehensively inform areas that impact COVID-19 outcomes for different sub-populations in order to better protect the public
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