Cargando…
Estimating surge in COVID-19 cases, hospital resources and PPE demand with the interactive and locally-informed COVID-19 Health System Capacity Planning Tool
INTRODUCTION: The COVID-19 pandemic revealed an urgent need for analytic tools to help health system leaders plan for surges in hospital capacity. Our objective was to develop a practical and locally informed Tool to help explore the effects of public health interventions on SARS-CoV-2 transmission...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Swansea University
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9052960/ https://www.ncbi.nlm.nih.gov/pubmed/35516164 http://dx.doi.org/10.23889/ijpds.v5i4.1710 |
_version_ | 1784696894267588608 |
---|---|
author | Krylova, Olga Kazmi, Omar Wang, Hui Lam, Kelvin Logar-Henderson, Chloe Gapanenko, Katerina |
author_facet | Krylova, Olga Kazmi, Omar Wang, Hui Lam, Kelvin Logar-Henderson, Chloe Gapanenko, Katerina |
author_sort | Krylova, Olga |
collection | PubMed |
description | INTRODUCTION: The COVID-19 pandemic revealed an urgent need for analytic tools to help health system leaders plan for surges in hospital capacity. Our objective was to develop a practical and locally informed Tool to help explore the effects of public health interventions on SARS-CoV-2 transmission and create scenarios to project potential surges in hospital admissions and resource demand. METHODS: Our Excel-based Tool uses a modified S(usceptible)-E(xposed)-I(nfected)-R(emoved) model with vaccination to simulate the potential spread of COVID-19 cases in the community and subsequent demand for hospitalizations, intensive care unit beds, ventilators, health care workers, and personal protective equipment. With over 40+ customizable parameters, planners can adapt the Tool to their jurisdiction and changes in the pandemic. RESULTS: We showcase the Tool using data for Ontario, Canada. Using healthcare utilization data to fit hospitalizations and ICU cases, we illustrate how public health interventions influenced the COVID-19 reproduction number and case counts. We also demonstrate the Tool’s ability to project a potential epidemic trajectory and subsequent demand for hospital resources. Using local data, we built three planning scenarios for Ontario for a 3-month period. Our worst-case scenario accurately projected the surge in critical care demand that overwhelmed hospital capacity in Ontario during Spring 2021. CONCLUSIONS: Our Tool can help different levels of health authorities plan their response to the pandemic. The main differentiators between this Tool and other existing tools include its ease of use, ability to build scenarios, and that it provides immediate outcomes that are ready to share with executive decision makers. The Tool is used by provincial health ministries, public health departments, and hospitals to make operational decisions and communicate possible scenarios to the public. The Tool provides educational value for the healthcare community and can be adapted for existing and emerging diseases. |
format | Online Article Text |
id | pubmed-9052960 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Swansea University |
record_format | MEDLINE/PubMed |
spelling | pubmed-90529602022-05-04 Estimating surge in COVID-19 cases, hospital resources and PPE demand with the interactive and locally-informed COVID-19 Health System Capacity Planning Tool Krylova, Olga Kazmi, Omar Wang, Hui Lam, Kelvin Logar-Henderson, Chloe Gapanenko, Katerina Int J Popul Data Sci Population Data Science INTRODUCTION: The COVID-19 pandemic revealed an urgent need for analytic tools to help health system leaders plan for surges in hospital capacity. Our objective was to develop a practical and locally informed Tool to help explore the effects of public health interventions on SARS-CoV-2 transmission and create scenarios to project potential surges in hospital admissions and resource demand. METHODS: Our Excel-based Tool uses a modified S(usceptible)-E(xposed)-I(nfected)-R(emoved) model with vaccination to simulate the potential spread of COVID-19 cases in the community and subsequent demand for hospitalizations, intensive care unit beds, ventilators, health care workers, and personal protective equipment. With over 40+ customizable parameters, planners can adapt the Tool to their jurisdiction and changes in the pandemic. RESULTS: We showcase the Tool using data for Ontario, Canada. Using healthcare utilization data to fit hospitalizations and ICU cases, we illustrate how public health interventions influenced the COVID-19 reproduction number and case counts. We also demonstrate the Tool’s ability to project a potential epidemic trajectory and subsequent demand for hospital resources. Using local data, we built three planning scenarios for Ontario for a 3-month period. Our worst-case scenario accurately projected the surge in critical care demand that overwhelmed hospital capacity in Ontario during Spring 2021. CONCLUSIONS: Our Tool can help different levels of health authorities plan their response to the pandemic. The main differentiators between this Tool and other existing tools include its ease of use, ability to build scenarios, and that it provides immediate outcomes that are ready to share with executive decision makers. The Tool is used by provincial health ministries, public health departments, and hospitals to make operational decisions and communicate possible scenarios to the public. The Tool provides educational value for the healthcare community and can be adapted for existing and emerging diseases. Swansea University 2022-04-06 /pmc/articles/PMC9052960/ /pubmed/35516164 http://dx.doi.org/10.23889/ijpds.v5i4.1710 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. |
spellingShingle | Population Data Science Krylova, Olga Kazmi, Omar Wang, Hui Lam, Kelvin Logar-Henderson, Chloe Gapanenko, Katerina Estimating surge in COVID-19 cases, hospital resources and PPE demand with the interactive and locally-informed COVID-19 Health System Capacity Planning Tool |
title | Estimating surge in COVID-19 cases, hospital resources and PPE demand with the interactive and locally-informed COVID-19 Health System Capacity Planning Tool |
title_full | Estimating surge in COVID-19 cases, hospital resources and PPE demand with the interactive and locally-informed COVID-19 Health System Capacity Planning Tool |
title_fullStr | Estimating surge in COVID-19 cases, hospital resources and PPE demand with the interactive and locally-informed COVID-19 Health System Capacity Planning Tool |
title_full_unstemmed | Estimating surge in COVID-19 cases, hospital resources and PPE demand with the interactive and locally-informed COVID-19 Health System Capacity Planning Tool |
title_short | Estimating surge in COVID-19 cases, hospital resources and PPE demand with the interactive and locally-informed COVID-19 Health System Capacity Planning Tool |
title_sort | estimating surge in covid-19 cases, hospital resources and ppe demand with the interactive and locally-informed covid-19 health system capacity planning tool |
topic | Population Data Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9052960/ https://www.ncbi.nlm.nih.gov/pubmed/35516164 http://dx.doi.org/10.23889/ijpds.v5i4.1710 |
work_keys_str_mv | AT krylovaolga estimatingsurgeincovid19caseshospitalresourcesandppedemandwiththeinteractiveandlocallyinformedcovid19healthsystemcapacityplanningtool AT kazmiomar estimatingsurgeincovid19caseshospitalresourcesandppedemandwiththeinteractiveandlocallyinformedcovid19healthsystemcapacityplanningtool AT wanghui estimatingsurgeincovid19caseshospitalresourcesandppedemandwiththeinteractiveandlocallyinformedcovid19healthsystemcapacityplanningtool AT lamkelvin estimatingsurgeincovid19caseshospitalresourcesandppedemandwiththeinteractiveandlocallyinformedcovid19healthsystemcapacityplanningtool AT logarhendersonchloe estimatingsurgeincovid19caseshospitalresourcesandppedemandwiththeinteractiveandlocallyinformedcovid19healthsystemcapacityplanningtool AT gapanenkokaterina estimatingsurgeincovid19caseshospitalresourcesandppedemandwiththeinteractiveandlocallyinformedcovid19healthsystemcapacityplanningtool |