Predictive modeling to estimate the demand for intensive care hospital beds nationwide in the context of the COVID-19 pandemic
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Peña, Víctor Hugo
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Predictive modeling to estimate the demand for intensive care hospital beds nationwide in the context of the COVID-19 pandemic
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Abstract
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.
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Artículo de publicación SCOPUS
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Medwave Volumen: 20 Número: 9 Oct 2020
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