Predictive modeling to estimate the demand for intensive care hospital beds nationwide in the context of the COVID-19 pandemic
Introduction SARS CoV-2 pandemic is pressing hard on the responsiveness of health systems worldwide, notably concerning the massive surge in demand for intensive care hospital beds. Aim This study proposes a methodology to estimate the saturation moment of hospital intensive care beds (critical...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Medwave Estudios Limitada
2020-10-01
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| Series: | Medwave |
| Subjects: | |
| Online Access: | https://www.medwave.cl/link.cgi/Medwave/Revisiones/Analisis/8039.act |
| _version_ | 1829512680027717632 |
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| author | Víctor Hugo Peña Alejandra Espinosa |
| author_facet | Víctor Hugo Peña Alejandra Espinosa |
| author_sort | Víctor Hugo Peña |
| collection | DOAJ |
| description | Introduction
SARS CoV-2 pandemic is pressing hard on the responsiveness of health systems worldwide, notably concerning the massive surge in demand for intensive care hospital beds.
Aim
This study proposes a methodology to estimate the saturation moment of hospital intensive care beds (critical care beds) and determine the number of units required to compensate for this saturation.
Methods
A total of 22,016 patients with diagnostic confirmation for COVID-19 caused by SARS-CoV-2 were analyzed between March 4 and May 5, 2020, nationwide. Based on information from the Chilean Ministry of Health and ministerial announcements in the media, the overall availability of critical care beds was estimated at 1,900 to 2,000. The Gompertz function was used to estimate the expected number of COVID-19 patients and to assess their exposure to the available supply of intensive care beds in various possible scenarios, taking into account the supply of total critical care beds, the average occupational index, and the demand for COVID-19 patients who would require an intensive care bed.
Results
A 100% occupancy of critical care beds could be reached between May 11 and May 27. This condition could be extended for around 48 days, depending on how the expected over-demand is managed.
Conclusion
A simple, easily interpretable, and applicable to all levels (nationwide, regionwide, municipalities, and hospitals) model is offered as a contribution to managing the expected demand for the coming weeks and helping reduce the adverse effects of the COVID-19 pandemic. |
| first_indexed | 2024-12-16T12:46:34Z |
| format | Article |
| id | doaj.art-7883bb7fc4c94db9a615be2847c76d7b |
| institution | Directory Open Access Journal |
| issn | 0717-6384 0717-6384 |
| language | English |
| last_indexed | 2024-12-16T12:46:34Z |
| publishDate | 2020-10-01 |
| publisher | Medwave Estudios Limitada |
| record_format | Article |
| series | Medwave |
| spelling | doaj.art-7883bb7fc4c94db9a615be2847c76d7b2022-12-21T22:31:17ZengMedwave Estudios LimitadaMedwave0717-63840717-63842020-10-012009e8039e803910.5867/medwave.2020.09.8039Predictive modeling to estimate the demand for intensive care hospital beds nationwide in the context of the COVID-19 pandemicVíctor Hugo Peña0https://orcid.org/0000-0003-2374-1074Alejandra Espinosa1https://orcid.org/0000-0003-4779-5341Departamento de Tecnología Médica, Facultad de Medicina, Universidad de Chile, Chile Departamento de Tecnología Médica, Facultad de Medicina, Universidad de Chile, ChileIntroduction SARS CoV-2 pandemic is pressing hard on the responsiveness of health systems worldwide, notably concerning the massive surge in demand for intensive care hospital beds. Aim This study proposes a methodology to estimate the saturation moment of hospital intensive care beds (critical care beds) and determine the number of units required to compensate for this saturation. Methods A total of 22,016 patients with diagnostic confirmation for COVID-19 caused by SARS-CoV-2 were analyzed between March 4 and May 5, 2020, nationwide. Based on information from the Chilean Ministry of Health and ministerial announcements in the media, the overall availability of critical care beds was estimated at 1,900 to 2,000. The Gompertz function was used to estimate the expected number of COVID-19 patients and to assess their exposure to the available supply of intensive care beds in various possible scenarios, taking into account the supply of total critical care beds, the average occupational index, and the demand for COVID-19 patients who would require an intensive care bed. Results A 100% occupancy of critical care beds could be reached between May 11 and May 27. This condition could be extended for around 48 days, depending on how the expected over-demand is managed. Conclusion A simple, easily interpretable, and applicable to all levels (nationwide, regionwide, municipalities, and hospitals) model is offered as a contribution to managing the expected demand for the coming weeks and helping reduce the adverse effects of the COVID-19 pandemic.https://www.medwave.cl/link.cgi/Medwave/Revisiones/Analisis/8039.act2019 novel coronavirus diseaseepidemiologypublic healthvirusesemergency medicinehospitalization |
| spellingShingle | Víctor Hugo Peña Alejandra Espinosa Predictive modeling to estimate the demand for intensive care hospital beds nationwide in the context of the COVID-19 pandemic Medwave 2019 novel coronavirus disease epidemiology public health viruses emergency medicine hospitalization |
| title | Predictive modeling to estimate the demand for intensive care hospital beds nationwide in the context of the COVID-19 pandemic |
| title_full | Predictive modeling to estimate the demand for intensive care hospital beds nationwide in the context of the COVID-19 pandemic |
| title_fullStr | Predictive modeling to estimate the demand for intensive care hospital beds nationwide in the context of the COVID-19 pandemic |
| title_full_unstemmed | Predictive modeling to estimate the demand for intensive care hospital beds nationwide in the context of the COVID-19 pandemic |
| title_short | Predictive modeling to estimate the demand for intensive care hospital beds nationwide in the context of the COVID-19 pandemic |
| title_sort | predictive modeling to estimate the demand for intensive care hospital beds nationwide in the context of the covid 19 pandemic |
| topic | 2019 novel coronavirus disease epidemiology public health viruses emergency medicine hospitalization |
| url | https://www.medwave.cl/link.cgi/Medwave/Revisiones/Analisis/8039.act |
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