Cargando…
SARS-CoV-2 and Wisconsin Nursing Homes: Temporal Dynamics During the COVID-19 Pandemic
OBJECTIVES: Evidence suggests that quality, location, and staffing levels may be associated with COVID-19 incidence in nursing homes. However, it is unknown if these relationships remain constant over time. We describe incidence rates of COVID-19 across Wisconsin nursing homes while examining factor...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AMDA - The Society for Post-Acute and Long-Term Care Medicine.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8390373/ https://www.ncbi.nlm.nih.gov/pubmed/34529958 http://dx.doi.org/10.1016/j.jamda.2021.08.021 |
_version_ | 1783743074991603712 |
---|---|
author | Gmehlin, Cameron G. Rivera, Frida Ramos-Castaneda, Jorge A. Pezzin, Liliana E. Ehn, Diane Duthie, Edmund H. Muñoz-Price, L. Silvia |
author_facet | Gmehlin, Cameron G. Rivera, Frida Ramos-Castaneda, Jorge A. Pezzin, Liliana E. Ehn, Diane Duthie, Edmund H. Muñoz-Price, L. Silvia |
author_sort | Gmehlin, Cameron G. |
collection | PubMed |
description | OBJECTIVES: Evidence suggests that quality, location, and staffing levels may be associated with COVID-19 incidence in nursing homes. However, it is unknown if these relationships remain constant over time. We describe incidence rates of COVID-19 across Wisconsin nursing homes while examining factors associated with their trajectory during 5 months of the pandemic. DESIGN: Retrospective cohort study. SETTING/PARTICIPANTS: Wisconsin nursing homes. METHODS: Publicly available data from June 1, 2020, to October 31, 2020, were obtained. These included facility size, staffing, 5-star Medicare rating score, and components. Nursing home characteristics were compared using Pearson chi-square and Kruskal-Wallis tests. Multiple linear regressions were used to evaluate the effect of rurality on COVID-19. RESULTS: There were a total of 2459 COVID-19 cases across 246 Wisconsin nursing homes. Number of beds (P < .001), average count of residents per day (P < .001), and governmental ownership (P = .014) were associated with a higher number of COVID-19 cases. Temporal analysis showed that the highest incidence rates of COVID-19 were observed in October 2020 (30.33 cases per 10,000 nursing home occupied-bed days, respectively). Urban nursing homes experienced higher incidence rates until September 2020; then incidence rates among rural nursing homes surged. In the first half of the study period, nursing homes with lower-quality scores (1-3 stars) had higher COVID-19 incidence rates. However, since August 2020, incidence was highest among nursing homes with higher-quality scores (4 or 5 stars). Multivariate analysis indicated that over time rural location was associated with increased incidence of COVID-19 (β = 0.05, P = .03). CONCLUSIONS AND IMPLICATIONS: Higher COVID-19 incidence rates were first observed in large, urban nursing homes with low-quality rating. By October 2020, the disease had spread to rural and smaller nursing homes and those with higher-quality ratings, suggesting that community transmission of SARS-CoV-2 may have propelled its spread. |
format | Online Article Text |
id | pubmed-8390373 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | AMDA - The Society for Post-Acute and Long-Term Care Medicine. |
record_format | MEDLINE/PubMed |
spelling | pubmed-83903732021-08-27 SARS-CoV-2 and Wisconsin Nursing Homes: Temporal Dynamics During the COVID-19 Pandemic Gmehlin, Cameron G. Rivera, Frida Ramos-Castaneda, Jorge A. Pezzin, Liliana E. Ehn, Diane Duthie, Edmund H. Muñoz-Price, L. Silvia J Am Med Dir Assoc Original Study OBJECTIVES: Evidence suggests that quality, location, and staffing levels may be associated with COVID-19 incidence in nursing homes. However, it is unknown if these relationships remain constant over time. We describe incidence rates of COVID-19 across Wisconsin nursing homes while examining factors associated with their trajectory during 5 months of the pandemic. DESIGN: Retrospective cohort study. SETTING/PARTICIPANTS: Wisconsin nursing homes. METHODS: Publicly available data from June 1, 2020, to October 31, 2020, were obtained. These included facility size, staffing, 5-star Medicare rating score, and components. Nursing home characteristics were compared using Pearson chi-square and Kruskal-Wallis tests. Multiple linear regressions were used to evaluate the effect of rurality on COVID-19. RESULTS: There were a total of 2459 COVID-19 cases across 246 Wisconsin nursing homes. Number of beds (P < .001), average count of residents per day (P < .001), and governmental ownership (P = .014) were associated with a higher number of COVID-19 cases. Temporal analysis showed that the highest incidence rates of COVID-19 were observed in October 2020 (30.33 cases per 10,000 nursing home occupied-bed days, respectively). Urban nursing homes experienced higher incidence rates until September 2020; then incidence rates among rural nursing homes surged. In the first half of the study period, nursing homes with lower-quality scores (1-3 stars) had higher COVID-19 incidence rates. However, since August 2020, incidence was highest among nursing homes with higher-quality scores (4 or 5 stars). Multivariate analysis indicated that over time rural location was associated with increased incidence of COVID-19 (β = 0.05, P = .03). CONCLUSIONS AND IMPLICATIONS: Higher COVID-19 incidence rates were first observed in large, urban nursing homes with low-quality rating. By October 2020, the disease had spread to rural and smaller nursing homes and those with higher-quality ratings, suggesting that community transmission of SARS-CoV-2 may have propelled its spread. AMDA - The Society for Post-Acute and Long-Term Care Medicine. 2021-11 2021-08-27 /pmc/articles/PMC8390373/ /pubmed/34529958 http://dx.doi.org/10.1016/j.jamda.2021.08.021 Text en © 2021 AMDA - The Society for Post-Acute and Long-Term Care Medicine. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Original Study Gmehlin, Cameron G. Rivera, Frida Ramos-Castaneda, Jorge A. Pezzin, Liliana E. Ehn, Diane Duthie, Edmund H. Muñoz-Price, L. Silvia SARS-CoV-2 and Wisconsin Nursing Homes: Temporal Dynamics During the COVID-19 Pandemic |
title | SARS-CoV-2 and Wisconsin Nursing Homes: Temporal Dynamics During the COVID-19 Pandemic |
title_full | SARS-CoV-2 and Wisconsin Nursing Homes: Temporal Dynamics During the COVID-19 Pandemic |
title_fullStr | SARS-CoV-2 and Wisconsin Nursing Homes: Temporal Dynamics During the COVID-19 Pandemic |
title_full_unstemmed | SARS-CoV-2 and Wisconsin Nursing Homes: Temporal Dynamics During the COVID-19 Pandemic |
title_short | SARS-CoV-2 and Wisconsin Nursing Homes: Temporal Dynamics During the COVID-19 Pandemic |
title_sort | sars-cov-2 and wisconsin nursing homes: temporal dynamics during the covid-19 pandemic |
topic | Original Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8390373/ https://www.ncbi.nlm.nih.gov/pubmed/34529958 http://dx.doi.org/10.1016/j.jamda.2021.08.021 |
work_keys_str_mv | AT gmehlincamerong sarscov2andwisconsinnursinghomestemporaldynamicsduringthecovid19pandemic AT riverafrida sarscov2andwisconsinnursinghomestemporaldynamicsduringthecovid19pandemic AT ramoscastanedajorgea sarscov2andwisconsinnursinghomestemporaldynamicsduringthecovid19pandemic AT pezzinlilianae sarscov2andwisconsinnursinghomestemporaldynamicsduringthecovid19pandemic AT ehndiane sarscov2andwisconsinnursinghomestemporaldynamicsduringthecovid19pandemic AT duthieedmundh sarscov2andwisconsinnursinghomestemporaldynamicsduringthecovid19pandemic AT munozpricelsilvia sarscov2andwisconsinnursinghomestemporaldynamicsduringthecovid19pandemic |