Dataset Information

Risk and Protective Factors in the COVID-19 Pandemic: A Rapid Evidence Map.

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.

SUBMITTER: Elmore R

PROVIDER: S-EPMC7732416 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Risk and Protective Factors in the COVID-19 Pandemic: A Rapid Evidence Map.

Elmore Rebecca R Schmidt Lena L Lam Juleen J Howard Brian E BE Tandon Arpit A Norman Christopher C Phillips Jason J Shah Mihir M Patel Shyam S Albert Tyler T Taxman Debra J DJ Shah Ruchir R RR

Frontiers in public health 20201124

<b>Background:</b> 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 ...[more]

PMID: 33330323

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Project description:BackgroundCoronavirus Disease 2019 (COVID-19) is a global pandemic and an anxiety-provoking event. There are few studies to identify potential risk and protective factors related to anxiety during COVID-19 pandemic.MethodsWe collected information on demographic data and lifestyles by a web-based survey of 19,802 participants from 34 provinces in China during COVID-19 pandemic. Level of anxiety was evaluated using the Self-Rating Anxiety Scale. We used ordinal multivariable logistic regression to estimate the associations of anxiety level with potential risk and protective factors. We further developed a new score to simplify the assessment of anxiety during COVID-19 crisis.ResultsAmong 19,802 participants, we found that those who were front-line medical personnel, suffered from chronic disease, with present symptoms of SARS-CoV-2 infection or contact history had 112, 93, 40 and 15% increased risk of higher anxiety level; while those with knowledge about personal protective measures or wore masks had 75 and 29% lower risk of higher anxiety level respectively. We developed a risk score by calculating the sum of single score of 17 factors. Each one increase of the risk score was associated with a 297% increase in anxiety index score. In categorical analysis, low risk (the risk score between 1 to 2), the moderate risk group (the risk score of 3) and high risk group (the risk score ≥ 4) had - 0.40 (95% CI: - 1.55, 0.76), 1.44 (95% CI: 0.27, 2.61) and 9.18 (95% CI: 8.04, 10.33) increase in anxiety index score, and 26% (95% CI: - 7, 72%), 172% (95% CI: 100, 270%), and 733% (95% CI: 516, 1026%) higher risk of anxiety respectively, when compared with the very low risk group (the risk score of 0). The AUC was 0.73 (95% CI, 0.72, 0.74) for the model fitted the developed risk score, with the cut-off point of 3.5.ConclusionsThese findings revealed protective and risk factors associated with anxiety, and developed a simple method of identifying people who are at an increased risk of anxiety during COVID-19 pandemic.

Project description:ObjectivesTo comprehensively map the existing evidence assessing the impact of travel-related control measures for containment of the SARS-CoV-2/COVID-19 pandemic.DesignRapid evidence map.Data sourcesMEDLINE, Embase and Web of Science, and COVID-19 specific databases offered by the US Centers for Disease Control and Prevention and the WHO.Eligibility criteriaWe included studies in human populations susceptible to SARS-CoV-2/COVID-19, SARS-CoV-1/severe acute respiratory syndrome, Middle East respiratory syndrome coronavirus/Middle East respiratory syndrome or influenza. Interventions of interest were travel-related control measures affecting travel across national or subnational borders. Outcomes of interest included infectious disease, screening, other health, economic and social outcomes. We considered all empirical studies that quantitatively evaluate impact available in Armenian, English, French, German, Italian and Russian based on the team's language capacities.Data extraction and synthesisWe extracted data from included studies in a standardised manner and mapped them to a priori and (one) post hoc defined categories.ResultsWe included 122 studies assessing travel-related control measures. These studies were undertaken across the globe, most in the Western Pacific region (n=71). A large proportion of studies focused on COVID-19 (n=59), but a number of studies also examined SARS, MERS and influenza. We identified studies on border closures (n=3), entry/exit screening (n=31), travel-related quarantine (n=6), travel bans (n=8) and travel restrictions (n=25). Many addressed a bundle of travel-related control measures (n=49). Most studies assessed infectious disease (n=98) and/or screening-related (n=25) outcomes; we found only limited evidence on economic and social outcomes. Studies applied numerous methods, both inferential and descriptive in nature, ranging from simple observational methods to complex modelling techniques.ConclusionsWe identified a heterogeneous and complex evidence base on travel-related control measures. While this map is not sufficient to assess the effectiveness of different measures, it outlines aspects regarding interventions and outcomes, as well as study methodology and reporting that could inform future research and evidence synthesis.

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Risk and Protective Factors in the COVID-19 Pandemic: A Rapid Evidence Map.

Publications

Risk and Protective Factors in the COVID-19 Pandemic: A Rapid Evidence Map.

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