Key Words: 2019 novel coronavirus disease, epidemiology, public health, viruses, emergency medicine, hospitalization
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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Introducción
La pandemia por SARS CoV-2 está presionando fuertemente la capacidad de respuesta de los sistemas de salud en todo el mundo, siendo uno de los aspectos más importantes el aumento masivo de pacientes que requerirán utilizar camas hospitalarias de cuidados intensivos.
Objetivo
Este estudio propone una metodología para estimar el momento de saturación de las camas de cuidados intensivos hospitalarios (camas críticas) y determinar el número de unidades requeridas para compensar dicha saturación.
Método
Se analizaron 22 016 pacientes con confirmación diagnóstica para COVID-19 provocada por SARS-CoV-2, entre el 4 de marzo y el 5 de mayo de 2020 a nivel nacional. Sobre la base de información del Ministerio de Salud de Chile y a anuncios ministeriales en medios de prensa, se estimó una disponibilidad total actual de 1900 a 2200 camas críticas totales. Se utilizó la función de Gompertz para estimar el número esperado de pacientes COVID-19 y evaluar su exposición a la oferta disponible de camas de cuidados intensivos en varios escenarios posibles. Para ello se tomó en cuenta la oferta de camas críticas totales, el índice ocupacional promedio, y la demanda de pacientes COVID-19 que requerirán cama de cuidados intensivos.
Resultados
Considerando diferentes escenarios, entre el 11 y el 27 de mayo podría ser alcanzado el 100% de ocupación de camas críticas totales. Esta condición podría extenderse por unos 48 días dependiendo como se maneje la sobredemanda esperada.
Conclusión
Se puede establecer una ventana de operaciones relativamente estrecha, de 4 a 8 semanas, para mitigar la inminente saturación de camas críticas hospitalarias, producto de la demanda de pacientes COVID-19.
Authors:
Víctor Hugo Peña[1], Alejandra Espinosa[1]
Affiliation:
[1] Departamento de Tecnología Médica, Facultad de Medicina, Universidad de Chile, Chile
E-mail: vicarcl@gmail.com
Author address:
[1] 6 ADB Ave., Mandaluyong Metro-Manila Philippines
Citation: Peña VH, Espinosa A. Predictive modeling to estimate the demand for intensive care hospital beds nationwide in the context of the COVID-19 pandemic. Medwave 2020;20(9):e8039 doi: 10.5867/medwave.2020.09.8039
Submission date: 24/4/2020
Acceptance date: 2/9/2020
Publication date: 5/10/2020
Origin: Not commissioned
Type of review: Externally peer-reviewed by three reviewers, double-blind
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Siordia JA Jr. Epidemiology and clinical features of COVID-19: A review of current literature. J Clin Virol. 2020 Jun;127:104357. | CrossRef | PubMed |Cuestas E. La pandemia por el nuevo coronavirus covid-19 [The novel coronavirus covid-19 pandemic]. Rev Fac Cien Med Univ Nac Cordoba. 2020 Mar 18;77(1):1-3. | CrossRef | PubMed |Sen-Crowe B, McKenney M, Elkbuli A. Social distancing during the COVID-19 pandemic: Staying home save lives. Am J Emerg Med. 2020 Jul;38(7):1519-1520. | CrossRef | PubMed |Güner R, Hasanoğlu I, Aktaş F. COVID-19: Prevention and control measures in community. Turk J Med Sci. 2020 Apr 21;50(SI-1):571-577. | CrossRef | PubMed |Córdova-Lepe F, Gutiérrez-Aguilar R, Gutiérrez-Jara JP. Número de casos COVID-19 en Chile a 120 días con datos al 21/03/2020 y umbral del esfuerzo diario para aplanar la epi-curva [Number of COVID-19 cases in Chile at 120 days with data at 21/03/2020 and threshold of daily effort to flatten the epi-curve]. Medwave. 2020 Mar 27;20(2):e7861. | CrossRef | PubMed |Grasselli G, Pesenti A, Cecconi M. Critical Care Utilization for the COVID-19 Outbreak in Lombardy, Italy: Early Experience and Forecast During an Emergency Response. JAMA. 2020 Apr 28;323(16):1545-1546. | CrossRef | PubMed |Ministerio de Salud de Chile. Unidad de Gestión Centralizada de Camas, UGCC. Santiago, Chile: MINSAL; 2018. [On line]. | Link |Litton E, Bucci T, Chavan S, Ho YY, Holley A, Howard G, et al. Surge capacity of intensive care units in case of acute increase in demand caused by COVID-19 in Australia. Med J Aust. 2020 Jun;212(10):463-467. | CrossRef | PubMed |Vaghi C, Rodallec A, Fanciullino R, Ciccolini J, Mochel JP, Mastri M, et al. Population modeling of tumor growth curves and the reduced Gompertz model improve prediction of the age of experimental tumors. PLoS Comput Biol. 2020 Feb 25;16(2):e1007178. | CrossRef | PubMed |Bürger R, Chowell G, Lara-Díıaz LY. Comparative analysis of phenomenological growth models applied to epidemic outbreaks. Math Biosci Eng. 2019 May 16;16(5):4250-4273. | CrossRef | PubMed |Latorre R, Sandoval G. El mapa actualizado de las camas de hospitales en Chile. La Tercera. 2020. [On line]. | Link |Departamento de Políticas de Salud y Estudios. 2do Informe COVID 19. Colegio Médico de Chile; 2020. [On line]. | Link |Gonzalez RI, Munoz F, Moya PS, Kiwi M. Is a COVID19 Quarantine Justified in Chile or USA Right Now? 2020 Mar. [On line]. | Link |Canals M. Proyección de la demanda de camas UCI (datos hasta el 30 de marzo de 2020). Escuela de Salud Pública, Universidad de Chile. 2020. [On line]. | Link |
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