A Systematic Map of Non-Clinical Evidence Syntheses Published Globally on COVID-19

Abstract

Study Objective: Evidence syntheses perform rigorous investigations of the primary literature and they have played a vital role in generating evidence-based recommendations for governments worldwide during the COVID-19 pandemic. However, there has not yet been an attempt to organize them across topic and other characteristics. This study performed a systematic mapping exercise of non-clinical evidence syntheses pertaining to COVID-19. Methods: This study conducted a systematic search on December 5, 2020 across 10 databases and servers: CINAHL, Embase, Global Health, Healthstar, MEDLINE, PsychINFO, and Web of Science, Research Square, MEDRxiv, and PROSPERO. Only full evidence syntheses published in a peer-reviewed journal or preprint server were included. Results: This study classified all evidence synthesis in the following topics: health service delivery (n = 280), prevention and behavior (n = 201), mental health (n = 140), social epidemiology (n = 31), economy (n = 22), and environment (n = 19). This study provides a comprehensive resource of all evidence syntheses categorized according to topic. Conclusions: This study proposes the following research priorities: governance, the impact of COVID-19 on different populations, the effectiveness of prevention and control methods across contexts, mental health, and vaccine hesitancy.

Estimated Prevalence of and Factors Associated With Clinically Significant Anxiety and Depression Among US Adults During the First Year of the COVID-19 Pandemic

“…Concerns about adverse mental health effects of COVID-19 have been raised since the beginning of the pandemic 1 , 2 based on evidence for such outcomes in past infectious disease outbreaks 3 , 4 , 5 and natural disasters. 6 Many empirical papers subsequently investigated the association of the pandemic with mental health, 7 and most concluded that the pandemic caused dramatic increases in anxiety and depression. However, such studies mostly compared online pandemic-era surveys with low or unreported response rates against prepandemic government benchmark probability surveys.…”