Cargando…
Real-time analysis of hospital length of stay in a mixed SARS-CoV-2 Omicron and Delta epidemic in New South Wales, Australia
BACKGROUND: The distribution of the duration that clinical cases of COVID-19 occupy hospital beds (the ‘length of stay’) is a key factor in determining how incident caseloads translate into health system burden. Robust estimation of length of stay in real-time requires the use of survival methods th...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9844941/ https://www.ncbi.nlm.nih.gov/pubmed/36650474 http://dx.doi.org/10.1186/s12879-022-07971-6 |
_version_ | 1784870773796634624 |
---|---|
author | Tobin, Ruarai J. Wood, James G. Jayasundara, Duleepa Sara, Grant Walker, Camelia R. Martin, Genevieve E. McCaw, James M. Shearer, Freya M. Price, David J. |
author_facet | Tobin, Ruarai J. Wood, James G. Jayasundara, Duleepa Sara, Grant Walker, Camelia R. Martin, Genevieve E. McCaw, James M. Shearer, Freya M. Price, David J. |
author_sort | Tobin, Ruarai J. |
collection | PubMed |
description | BACKGROUND: The distribution of the duration that clinical cases of COVID-19 occupy hospital beds (the ‘length of stay’) is a key factor in determining how incident caseloads translate into health system burden. Robust estimation of length of stay in real-time requires the use of survival methods that can account for right-censoring induced by yet unobserved events in patient progression (e.g. discharge, death). In this study, we estimate in real-time the length of stay distributions of hospitalised COVID-19 cases in New South Wales, Australia, comparing estimates between a period where Delta was the dominant variant and a subsequent period where Omicron was dominant. METHODS: Using data on the hospital stays of 19,574 individuals who tested positive to COVID-19 prior to admission, we performed a competing-risk survival analysis of COVID-19 clinical progression. RESULTS: During the mixed Omicron-Delta epidemic, we found that the mean length of stay for individuals who were discharged directly from ward without an ICU stay was, for age groups 0–39, 40–69 and 70 +, respectively, 2.16 (95% CI: 2.12–2.21), 3.93 (95% CI: 3.78–4.07) and 7.61 days (95% CI: 7.31–8.01), compared to 3.60 (95% CI: 3.48–3.81), 5.78 (95% CI: 5.59–5.99) and 12.31 days (95% CI: 11.75–12.95) across the preceding Delta epidemic (1 July 2021–15 December 2021). We also considered data on the stays of individuals within the Hunter New England Local Health District, where it was reported that Omicron was the only circulating variant, and found mean ward-to-discharge length of stays of 2.05 (95% CI: 1.80–2.30), 2.92 (95% CI: 2.50–3.67) and 6.02 days (95% CI: 4.91–7.01) for the same age groups. CONCLUSIONS: Hospital length of stay was substantially reduced across all clinical pathways during a mixed Omicron-Delta epidemic compared to a prior Delta epidemic, contributing to a lessened health system burden despite a greatly increased infection burden. Our results demonstrate the utility of survival analysis in producing real-time estimates of hospital length of stay for assisting in situational assessment and planning of the COVID-19 response. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07971-6. |
format | Online Article Text |
id | pubmed-9844941 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-98449412023-01-18 Real-time analysis of hospital length of stay in a mixed SARS-CoV-2 Omicron and Delta epidemic in New South Wales, Australia Tobin, Ruarai J. Wood, James G. Jayasundara, Duleepa Sara, Grant Walker, Camelia R. Martin, Genevieve E. McCaw, James M. Shearer, Freya M. Price, David J. BMC Infect Dis Research BACKGROUND: The distribution of the duration that clinical cases of COVID-19 occupy hospital beds (the ‘length of stay’) is a key factor in determining how incident caseloads translate into health system burden. Robust estimation of length of stay in real-time requires the use of survival methods that can account for right-censoring induced by yet unobserved events in patient progression (e.g. discharge, death). In this study, we estimate in real-time the length of stay distributions of hospitalised COVID-19 cases in New South Wales, Australia, comparing estimates between a period where Delta was the dominant variant and a subsequent period where Omicron was dominant. METHODS: Using data on the hospital stays of 19,574 individuals who tested positive to COVID-19 prior to admission, we performed a competing-risk survival analysis of COVID-19 clinical progression. RESULTS: During the mixed Omicron-Delta epidemic, we found that the mean length of stay for individuals who were discharged directly from ward without an ICU stay was, for age groups 0–39, 40–69 and 70 +, respectively, 2.16 (95% CI: 2.12–2.21), 3.93 (95% CI: 3.78–4.07) and 7.61 days (95% CI: 7.31–8.01), compared to 3.60 (95% CI: 3.48–3.81), 5.78 (95% CI: 5.59–5.99) and 12.31 days (95% CI: 11.75–12.95) across the preceding Delta epidemic (1 July 2021–15 December 2021). We also considered data on the stays of individuals within the Hunter New England Local Health District, where it was reported that Omicron was the only circulating variant, and found mean ward-to-discharge length of stays of 2.05 (95% CI: 1.80–2.30), 2.92 (95% CI: 2.50–3.67) and 6.02 days (95% CI: 4.91–7.01) for the same age groups. CONCLUSIONS: Hospital length of stay was substantially reduced across all clinical pathways during a mixed Omicron-Delta epidemic compared to a prior Delta epidemic, contributing to a lessened health system burden despite a greatly increased infection burden. Our results demonstrate the utility of survival analysis in producing real-time estimates of hospital length of stay for assisting in situational assessment and planning of the COVID-19 response. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07971-6. BioMed Central 2023-01-17 /pmc/articles/PMC9844941/ /pubmed/36650474 http://dx.doi.org/10.1186/s12879-022-07971-6 Text en © The Author(s) 2023 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 Tobin, Ruarai J. Wood, James G. Jayasundara, Duleepa Sara, Grant Walker, Camelia R. Martin, Genevieve E. McCaw, James M. Shearer, Freya M. Price, David J. Real-time analysis of hospital length of stay in a mixed SARS-CoV-2 Omicron and Delta epidemic in New South Wales, Australia |
title | Real-time analysis of hospital length of stay in a mixed SARS-CoV-2 Omicron and Delta epidemic in New South Wales, Australia |
title_full | Real-time analysis of hospital length of stay in a mixed SARS-CoV-2 Omicron and Delta epidemic in New South Wales, Australia |
title_fullStr | Real-time analysis of hospital length of stay in a mixed SARS-CoV-2 Omicron and Delta epidemic in New South Wales, Australia |
title_full_unstemmed | Real-time analysis of hospital length of stay in a mixed SARS-CoV-2 Omicron and Delta epidemic in New South Wales, Australia |
title_short | Real-time analysis of hospital length of stay in a mixed SARS-CoV-2 Omicron and Delta epidemic in New South Wales, Australia |
title_sort | real-time analysis of hospital length of stay in a mixed sars-cov-2 omicron and delta epidemic in new south wales, australia |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9844941/ https://www.ncbi.nlm.nih.gov/pubmed/36650474 http://dx.doi.org/10.1186/s12879-022-07971-6 |
work_keys_str_mv | AT tobinruaraij realtimeanalysisofhospitallengthofstayinamixedsarscov2omicronanddeltaepidemicinnewsouthwalesaustralia AT woodjamesg realtimeanalysisofhospitallengthofstayinamixedsarscov2omicronanddeltaepidemicinnewsouthwalesaustralia AT jayasundaraduleepa realtimeanalysisofhospitallengthofstayinamixedsarscov2omicronanddeltaepidemicinnewsouthwalesaustralia AT saragrant realtimeanalysisofhospitallengthofstayinamixedsarscov2omicronanddeltaepidemicinnewsouthwalesaustralia AT walkercameliar realtimeanalysisofhospitallengthofstayinamixedsarscov2omicronanddeltaepidemicinnewsouthwalesaustralia AT martingenevievee realtimeanalysisofhospitallengthofstayinamixedsarscov2omicronanddeltaepidemicinnewsouthwalesaustralia AT mccawjamesm realtimeanalysisofhospitallengthofstayinamixedsarscov2omicronanddeltaepidemicinnewsouthwalesaustralia AT shearerfreyam realtimeanalysisofhospitallengthofstayinamixedsarscov2omicronanddeltaepidemicinnewsouthwalesaustralia AT pricedavidj realtimeanalysisofhospitallengthofstayinamixedsarscov2omicronanddeltaepidemicinnewsouthwalesaustralia |