Statistical method to determine the need for hospitalization of COVID-19 patients

Abstract

The growth rate of COVID-19 is causing worldwide concern. The development of indirect methods used to determine hospitalizations only for necessary cases is of fundamental importance to prevent overcrowding in the health system. The general objective of this article is to propose a statistical method, based on logistic regression, capable of indicating whether a patient who tests positive for COVID-19 should be directed to home isolation or be admitted to a hospital, based on blood tests and age. The data was collected from 5,645 blood tests of patients in March and April 2020. Based on the use of the independent variables ‘C-reactive protein,’ ‘neutrophils,’ and ‘monocytes,’ as well as the age of the patient affected by COVID-19, it is possible to predict with a reasonable degree of accuracy whether, upon arriving at the hospital and testing positive, the individual should be recommended to isolate at home or be admitted to a healthcare facility.