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Identifying vulnerable populations at a university during the COVID-19 pandemic.
Tanabe, Kawai O; Hayden, Meredith E; Zunder, Barbara; Holstege, Christopher P.
  • Tanabe KO; Department of Student Health & Wellness, Division of Student Affairs, University of Virginia, Charlottesville, Virginia, USA.
  • Hayden ME; Department of Student Health & Wellness, Division of Student Affairs, University of Virginia, Charlottesville, Virginia, USA.
  • Zunder B; Department of Student Health & Wellness, Division of Student Affairs, University of Virginia, Charlottesville, Virginia, USA.
  • Holstege CP; Department of Student Health & Wellness, Division of Student Affairs, University of Virginia, Charlottesville, Virginia, USA.
J Am Coll Health ; : 1-4, 2021 Feb 12.
Artigo em Inglês | MEDLINE | ID: covidwho-2236121
ABSTRACT

OBJECTIVE:

Persons with high-risk for severe COVID-19 illness require special attention when considering university operations during the novel coronavirus pandemic. The objective of this study was to determine the number of students who fall within a high-risk category according to Centers for Disease Control and Prevention (CDC) guidelines using linked databases.

Participants:

Students enrolled at a large public University and who accessed the student health center between 2016 and 2020.

Methods:

Clinical data were linked with both university student enrollment and disability services databases to provide a comprehensive, de-identified dataset of students at higher medical risk of severe COVID-19 illness.

Results:

1902 unique students (14% of the student health center population) were identified as having one or more high-risk condition.

Conclusions:

Utilizing a large and longitudinally linked student database provides universities with valuable information to make critical administrative decisions about how best to accommodate high-risk students to reduce their medical risk when returning to in-person instruction.
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Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Tipo de estudo: Estudo prognóstico Idioma: Inglês Revista: J Am Coll Health Ano de publicação: 2021 Tipo de documento: Artigo País de afiliação: 07448481.2021.1877142

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Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Tipo de estudo: Estudo prognóstico Idioma: Inglês Revista: J Am Coll Health Ano de publicação: 2021 Tipo de documento: Artigo País de afiliação: 07448481.2021.1877142