Selected article for: "multiple regression model and regression model"

Author: Cernuda-Martínez, José A; Fernández-García, Andrea
Title: Estimation of the number of preventable COVID-19 deaths in relation to the restrictive measures adopted in America.
  • Cord-id: bn8utztc
  • Document date: 2021_1_1
  • ID: bn8utztc
    Snippet: INTRODUCTION In America, the United States was particularly affected by the COVID-19 pandemic. OBJECTIVEs To estimate how many daily COVID-19 deaths per 100,000 population would have been avoided if each one of five restrictive measures had been implemented at the time of diagnosis and to estimate a multiple linear regression model predictive of the number of deaths per 100,000 population based on the measures adopted by the countries. METHODS A simple linear regression was performed between the
    Document: INTRODUCTION In America, the United States was particularly affected by the COVID-19 pandemic. OBJECTIVEs To estimate how many daily COVID-19 deaths per 100,000 population would have been avoided if each one of five restrictive measures had been implemented at the time of diagnosis and to estimate a multiple linear regression model predictive of the number of deaths per 100,000 population based on the measures adopted by the countries. METHODS A simple linear regression was performed between the days elapsed since the first COVID-19 diagnosed case and the implementation of each one of the five restrictive measures by the 27 American countries studied and the number of COVID-19 deaths per 100,000 population. RESULTS For each day between the first COVID-19 reported case and the adoption of restrictive measures, between 0.250 (p = 0.021) and 0.600 (p = 0.001) patients per 100,000 population died, depending on the measure in question. CONCLUSIONS Adoption of restrictive measures and social distancing are necessary for reducing the number of people infected with COVID-19 and their mortality. In addition, promptness of their establishment is essential in order to reduce the number of deaths.

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