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Survival analysis of factors affecting the timing of COVID-19 non-pharmaceutical interventions by U.S. universities

BACKGROUND: During March of 2020 the Centers for Disease Control and Prevention (CDC) announced non-pharmaceutical intervention (NPI) guidance as the primary mitigation strategy against growing COVID-19 community spread due to the absence of a vaccine or effective treatment at that time. CDC guidanc...

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Autores principales: Cevasco, Kevin E., Roess, Amira A., North, Hayley M., Zeitoun, Sheryne A., Wofford, Rachel N., Matulis, Graham A., Gregory, Abigail F., Hassan, Maha H., Abdo, Aya D., von Fricken, Michael E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8562371/
https://www.ncbi.nlm.nih.gov/pubmed/34727895
http://dx.doi.org/10.1186/s12889-021-12035-6
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author Cevasco, Kevin E.
Roess, Amira A.
North, Hayley M.
Zeitoun, Sheryne A.
Wofford, Rachel N.
Matulis, Graham A.
Gregory, Abigail F.
Hassan, Maha H.
Abdo, Aya D.
von Fricken, Michael E.
author_facet Cevasco, Kevin E.
Roess, Amira A.
North, Hayley M.
Zeitoun, Sheryne A.
Wofford, Rachel N.
Matulis, Graham A.
Gregory, Abigail F.
Hassan, Maha H.
Abdo, Aya D.
von Fricken, Michael E.
author_sort Cevasco, Kevin E.
collection PubMed
description BACKGROUND: During March of 2020 the Centers for Disease Control and Prevention (CDC) announced non-pharmaceutical intervention (NPI) guidance as the primary mitigation strategy against growing COVID-19 community spread due to the absence of a vaccine or effective treatment at that time. CDC guidance states that NPIs are most effective when instituted in an early, targeted, and layered fashion. NPIs are effective in slowing spread, and measures should be custom-tailored to each population. This study examines factors associated with implementation and timing of NPI interventions across large public and private U.S. universities at the onset of the COVID-19 pandemic. METHODS: NPI decisions of interest include when U.S. universities canceled international travel, shifted to online learning, moved faculty/staff to remote work, limited campus housing, and closed campus for all non-essential personnel. Cox proportional hazard analyses of retrospective data were conducted to assess the time to NPI events. Hazard ratios were calculated for university governance, campus setting, religious affiliation, health infrastructure, faculty diversity, and student demographics. The methods control for variance inflation factors, COVID case prevalence, and time varying covariates of spring break and states’ state of emergency (SOE) orders. This study captures NPI decisions at 575 U.S. universities during spring of 2020 which affected the movement of seven million students and two million employees. RESULTS: Universities located in districts represented by Democratic party congressional members reported earlier NPI implementation than Republican (Cox proportional hazard ratio (HR) range 0.61–0.80). University religious affiliation was not associated with the timing any of the NPI decisions. Universities with more diverse faculty showed an association with earlier NPI implementation (HR range 0.65–0.76). The existence of university-affiliated health infrastructure was not associated with NPI timing. CONCLUSION: University NPI implementation was largely driven by local COVID-19 epidemiology, culture and political concerns. The timing of university NPI decisions varied by regional politics, faculty demographics, university governance, campus setting, and foreign student prevalence adjusting for COVID-19 state case prevalence and spring break timing. Religious affiliation and presence of university health infrastructure were not associated with timing. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-12035-6.
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spelling pubmed-85623712021-11-03 Survival analysis of factors affecting the timing of COVID-19 non-pharmaceutical interventions by U.S. universities Cevasco, Kevin E. Roess, Amira A. North, Hayley M. Zeitoun, Sheryne A. Wofford, Rachel N. Matulis, Graham A. Gregory, Abigail F. Hassan, Maha H. Abdo, Aya D. von Fricken, Michael E. BMC Public Health Research BACKGROUND: During March of 2020 the Centers for Disease Control and Prevention (CDC) announced non-pharmaceutical intervention (NPI) guidance as the primary mitigation strategy against growing COVID-19 community spread due to the absence of a vaccine or effective treatment at that time. CDC guidance states that NPIs are most effective when instituted in an early, targeted, and layered fashion. NPIs are effective in slowing spread, and measures should be custom-tailored to each population. This study examines factors associated with implementation and timing of NPI interventions across large public and private U.S. universities at the onset of the COVID-19 pandemic. METHODS: NPI decisions of interest include when U.S. universities canceled international travel, shifted to online learning, moved faculty/staff to remote work, limited campus housing, and closed campus for all non-essential personnel. Cox proportional hazard analyses of retrospective data were conducted to assess the time to NPI events. Hazard ratios were calculated for university governance, campus setting, religious affiliation, health infrastructure, faculty diversity, and student demographics. The methods control for variance inflation factors, COVID case prevalence, and time varying covariates of spring break and states’ state of emergency (SOE) orders. This study captures NPI decisions at 575 U.S. universities during spring of 2020 which affected the movement of seven million students and two million employees. RESULTS: Universities located in districts represented by Democratic party congressional members reported earlier NPI implementation than Republican (Cox proportional hazard ratio (HR) range 0.61–0.80). University religious affiliation was not associated with the timing any of the NPI decisions. Universities with more diverse faculty showed an association with earlier NPI implementation (HR range 0.65–0.76). The existence of university-affiliated health infrastructure was not associated with NPI timing. CONCLUSION: University NPI implementation was largely driven by local COVID-19 epidemiology, culture and political concerns. The timing of university NPI decisions varied by regional politics, faculty demographics, university governance, campus setting, and foreign student prevalence adjusting for COVID-19 state case prevalence and spring break timing. Religious affiliation and presence of university health infrastructure were not associated with timing. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-12035-6. BioMed Central 2021-11-02 /pmc/articles/PMC8562371/ /pubmed/34727895 http://dx.doi.org/10.1186/s12889-021-12035-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Cevasco, Kevin E.
Roess, Amira A.
North, Hayley M.
Zeitoun, Sheryne A.
Wofford, Rachel N.
Matulis, Graham A.
Gregory, Abigail F.
Hassan, Maha H.
Abdo, Aya D.
von Fricken, Michael E.
Survival analysis of factors affecting the timing of COVID-19 non-pharmaceutical interventions by U.S. universities
title Survival analysis of factors affecting the timing of COVID-19 non-pharmaceutical interventions by U.S. universities
title_full Survival analysis of factors affecting the timing of COVID-19 non-pharmaceutical interventions by U.S. universities
title_fullStr Survival analysis of factors affecting the timing of COVID-19 non-pharmaceutical interventions by U.S. universities
title_full_unstemmed Survival analysis of factors affecting the timing of COVID-19 non-pharmaceutical interventions by U.S. universities
title_short Survival analysis of factors affecting the timing of COVID-19 non-pharmaceutical interventions by U.S. universities
title_sort survival analysis of factors affecting the timing of covid-19 non-pharmaceutical interventions by u.s. universities
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8562371/
https://www.ncbi.nlm.nih.gov/pubmed/34727895
http://dx.doi.org/10.1186/s12889-021-12035-6
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