• Medicina intensiva · Mar 2021

    Mathematical model optimized for prediction and health care planning for COVID-19.

    • J M Garrido, D Martínez-Rodríguez, F Rodríguez-Serrano, J M Pérez-Villares, A Ferreiro-Marzal, M M Jiménez-Quintana, Grupo de Estudio COVID 19 Granada, and R J Villanueva.
    • Instituto de Investigación Biosanitaria ibs, GRANADA, Granada, España; Instituto de Biopatología y Medicina Regenerativa (IBIMER), Universidad de Granada, Granada, España; Servicio de Cirugía Cardiovascular, Hospital Virgen de las Nieves, Granada, España. Electronic address: josemgarrido@ugr.es.
    • Med Intensiva. 2021 Mar 6.

    ObjectiveThe COVID-19 pandemic has threatened to collapse hospital and ICU services, and it has affected the care programs for non-COVID patients. The objective was to develop a mathematical model designed to optimize predictions related to the need for hospitalization and ICU admission by COVID-19 patients.DesignProspective study.SettingProvince of Granada (Spain).PopulationCOVID-19 patients hospitalized, admitted to ICU, recovered and died from March 15 to September 22, 2020.Study VariablesThe number of patients infected with SARS-CoV-2 and hospitalized or admitted to ICU for COVID-19.ResultsThe data reported by hospitals was used to develop a mathematical model that reflects the flow of the population among the different interest groups in relation to COVID-19. This tool allows to analyse different scenarios based on socio-health restriction measures, and to forecast the number of people infected, hospitalized and admitted to the ICU.ConclusionsThe mathematical model is capable of providing predictions on the evolution of the COVID-19 sufficiently in advance as to anticipate the peaks of prevalence and hospital and ICU care demands, and also the appearance of periods in which the care for non-COVID patients could be intensified.Copyright © 2021. Publicado por Elsevier España, S.L.U.

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