Cited by 122COVID-19 Clinical Research StudiesSARS-CoV-2 and COVID-19 ResearchCOVID-19 epidemiological studies

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Coronavirus disease (COVID-19): a scoping review

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Abstract

Background: In December 2019, a pneumonia caused by a novel coronavirus (SARS-CoV-2) emerged in Wuhan, China and has rapidly spread around the world since then. Aim: This study aims to understand the research gaps related to COVID-19 and propose recommendations for future research. Methods: We undertook a scoping review of COVID-19, comprehensively searching databases and other sources to identify literature on COVID-19 between 1 December 2019 and 6 February 2020. We analysed the sources, publication date, type and topic of the retrieved articles/studies. Results: We included 249 articles in this scoping review. More than half (59.0%) were conducted in China. Guidance/guidelines and consensuses statements (n = 56; 22.5%) were the most common. Most (n = 192; 77.1%) articles were published in peer-reviewed journals, 35 (14.1%) on preprint servers and 22 (8.8%) posted online. Ten genetic studies (4.0%) focused on the origin of SARS-CoV-2 while the topics of molecular studies varied. Nine of 22 epidemiological studies focused on estimating the basic reproduction number of COVID-19 infection (R 0). Of all identified guidance/guidelines (n = 35), only ten fulfilled the strict principles of evidence-based practice. The number of articles published per day increased rapidly until the end of January. Conclusion: The number of articles on COVID-19 steadily increased before 6 February 2020. However, they lack diversity and are almost non-existent in some study fields, such as clinical research. The findings suggest that evidence for the development of clinical practice guidelines and public health policies will be improved when more results from clinical research becomes available.

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  • Scoping reviews are increasingly used to respond to complex questions where comparing interventions may be neither relevant nor possible.

    “Scoping reviews are increasingly used to respond to complex questions where comparing interventions may be neither relevant nor possible [27].”

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References 101 · Cited by 122

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Metadata

Authors
Lv, M., Luo, X., Estill, J., Liu, Y., Ren, M., Wang, J., Wang, Q., Zhao, S., Wang, X., Yang, S., Feng, X., Li, W., Liu, E., Zhang, X., Wang, L., Zhou, Q., Meng, W., Qi, X., Xun, Y., Yu, X., Chen, Y., & on behalf of the COVID-19 evidence and recommendations working group
Affiliations
  • Lanzhou University (CN)
  • University of Geneva (CH)
  • McMaster University (CA)
  • Chengdu University of Traditional Chinese Medicine (CN)
  • Chengdu Medical College (CN)
  • Children's Hospital of Chongqing Medical University (CN)
  • First Hospital of Lanzhou University (CN)
  • World Health Organization (CH)
Venue
Eurosurveillance
Published
2020-04-16
Volume
25
Issue
15
ISSN
  • 1025-496X (ISSN-L)
  • 1560-7917
OpenAlex
W3017130589
Cited by
122
References
101
Citations by year
2026: 2 · 2025: 2 · 2024: 7 · 2023: 12 · 2022: 31 · 2021: 34 · 2020: 33
FWCI
1.30
Type
journal article
Language
en
Open access
Locations
  • Eurosurveillance (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Archive ouverte UNIGE (University of Geneva) (acceptedVersion, other-oa)
  • Lanzhou University Institutional Repository (submittedVersion)
  • Archive ouverte UNIGE (University of Geneva) (submittedVersion, cc-by)
Funders
  • McMaster University
  • Lanzhou University
  • Chengdu Medical College
  • Chongqing Medical University
  • Shanxi Medical University
Topics
  • Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
Keywords
COVID-19 pandemic, SARS-CoV-2, research gaps, evidence-based practice, basic reproduction number, COVID-19 epidemiology, clinical research, public health policy, preprint servers, publication trends
MeSH terms
COVID-19, Humans, Pneumonia, Viral, Randomized Controlled Trials as Topic, Coronavirus Infections, Pandemics

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