Feasibility and effectiveness of daily temperature screening to detect COVID-19 in a prospective cohort at a large public university.

COVID-19 Detection Fever SARS-CoV-2 Screening Temperature monitoring Thermometer

Journal

BMC public health
ISSN: 1471-2458
Titre abrégé: BMC Public Health
Pays: England
ID NLM: 100968562

Informations de publication

Date de publication:
16 09 2021
Historique:
received: 28 04 2021
accepted: 29 08 2021
entrez: 17 9 2021
pubmed: 18 9 2021
medline: 23 9 2021
Statut: epublish

Résumé

Many persons with active SARS-CoV-2 infection experience mild or no symptoms, presenting barriers to COVID-19 prevention. Regular temperature screening is nonetheless used in some settings, including university campuses, to reduce transmission potential. We evaluated the potential impact of this strategy using a prospective university-affiliated cohort. Between June and August 2020, 2912 participants were enrolled and tested for SARS-CoV-2 by PCR at least once (median: 3, range: 1-9). Participants reported temperature and symptoms daily via electronic survey using a previously owned or study-provided thermometer. We assessed feasibility and acceptability of daily temperature monitoring, calculated sensitivity and specificity of various fever-based strategies for restricting campus access to reduce transmission, and estimated the association between measured temperature and SARS-CoV-2 test positivity using a longitudinal binomial mixed model. Most participants (70.2%) did not initially have a thermometer for taking their temperature daily. Across 5481 total person months, the average daily completion rate of temperature values was 61.6% (median: 67.6%, IQR: 41.8-86.2%). Sensitivity for SARS-CoV-2 ranged from 0% (95% CI 0-9.7%) to 40.5% (95% CI 25.6-56.7%) across all strategies for self-report of possible COVID-19 symptoms on day of specimen collection, with corresponding specificity of 99.9% (95% CI 99.8-100%) to 95.3% (95% CI 94.7-95.9%). An increase of 0.1 °F in individual mean body temperature on the same day as specimen collection was associated with 1.11 increased odds of SARS-CoV-2 positivity (95% CI 1.06-1.17). Our study is the first, to our knowledge, that examines the feasibility, acceptability, and effectiveness of daily temperature screening in a prospective cohort during an infectious disease outbreak, and the only study to assess these strategies in a university population. Daily temperature monitoring was feasible and acceptable; however, the majority of potentially infectious individuals were not detected by temperature monitoring, suggesting that temperature screening is insufficient as a primary means of detection to reduce transmission of SARS-CoV-2.

Sections du résumé

BACKGROUND
Many persons with active SARS-CoV-2 infection experience mild or no symptoms, presenting barriers to COVID-19 prevention. Regular temperature screening is nonetheless used in some settings, including university campuses, to reduce transmission potential. We evaluated the potential impact of this strategy using a prospective university-affiliated cohort.
METHODS
Between June and August 2020, 2912 participants were enrolled and tested for SARS-CoV-2 by PCR at least once (median: 3, range: 1-9). Participants reported temperature and symptoms daily via electronic survey using a previously owned or study-provided thermometer. We assessed feasibility and acceptability of daily temperature monitoring, calculated sensitivity and specificity of various fever-based strategies for restricting campus access to reduce transmission, and estimated the association between measured temperature and SARS-CoV-2 test positivity using a longitudinal binomial mixed model.
RESULTS
Most participants (70.2%) did not initially have a thermometer for taking their temperature daily. Across 5481 total person months, the average daily completion rate of temperature values was 61.6% (median: 67.6%, IQR: 41.8-86.2%). Sensitivity for SARS-CoV-2 ranged from 0% (95% CI 0-9.7%) to 40.5% (95% CI 25.6-56.7%) across all strategies for self-report of possible COVID-19 symptoms on day of specimen collection, with corresponding specificity of 99.9% (95% CI 99.8-100%) to 95.3% (95% CI 94.7-95.9%). An increase of 0.1 °F in individual mean body temperature on the same day as specimen collection was associated with 1.11 increased odds of SARS-CoV-2 positivity (95% CI 1.06-1.17).
CONCLUSIONS
Our study is the first, to our knowledge, that examines the feasibility, acceptability, and effectiveness of daily temperature screening in a prospective cohort during an infectious disease outbreak, and the only study to assess these strategies in a university population. Daily temperature monitoring was feasible and acceptable; however, the majority of potentially infectious individuals were not detected by temperature monitoring, suggesting that temperature screening is insufficient as a primary means of detection to reduce transmission of SARS-CoV-2.

Identifiants

pubmed: 34530802
doi: 10.1186/s12889-021-11697-6
pii: 10.1186/s12889-021-11697-6
pmc: PMC8445011
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1693

Informations de copyright

© 2021. The Author(s).

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Auteurs

Shelley N Facente (SN)

School of Public Health, Division of Epidemiology and Biostatistics, University of California, Berkeley, 2121 Berkeley Way # 5302, Berkeley, CA, 94720, USA. sfacente@berkeley.edu.
Facente Consulting, Richmond, CA, USA. sfacente@berkeley.edu.

Lauren A Hunter (LA)

School of Public Health, Division of Epidemiology and Biostatistics, University of California, Berkeley, 2121 Berkeley Way # 5302, Berkeley, CA, 94720, USA.

Laura J Packel (LJ)

School of Public Health, Division of Epidemiology and Biostatistics, University of California, Berkeley, 2121 Berkeley Way # 5302, Berkeley, CA, 94720, USA.

Yi Li (Y)

School of Public Health, Division of Epidemiology and Biostatistics, University of California, Berkeley, 2121 Berkeley Way # 5302, Berkeley, CA, 94720, USA.

Anna Harte (A)

University Health Services, University of California Berkeley, Berkeley, CA, USA.

Guy Nicolette (G)

University Health Services, University of California Berkeley, Berkeley, CA, USA.

Shana McDevitt (S)

Innovative Genomics Institute, University of California Berkeley, Berkeley, CA, USA.

Maya Petersen (M)

School of Public Health, Division of Epidemiology and Biostatistics, University of California, Berkeley, 2121 Berkeley Way # 5302, Berkeley, CA, 94720, USA.

Arthur L Reingold (AL)

School of Public Health, Division of Epidemiology and Biostatistics, University of California, Berkeley, 2121 Berkeley Way # 5302, Berkeley, CA, 94720, USA.

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Classifications MeSH