Bipartisan politics and poverty as a risk factor for contagion and mortality from SARS-CoV-2 virus in the United States of America

by   Cesar R. Salas Guerra, et al.

In the United States, from the start of the COVID-19 pandemic to December 31, 2020, 341,199 deaths and more than 19,663,976 infections were recorded. Recent literature establishes that communities with poverty-related health problems, such as obesity, cardiovascular disease, diabetes, and hypertension, are more susceptible to mortality from SARS-CoV-2 infection. Additionally, controversial public health policies implemented by the nation's political leaders have highlighted the socioeconomic inequalities of minorities. Therefore, through multivariate correlational analysis using machine learning techniques and structural equations, we measure whether social determinants are associated with increased infection and death from COVID-19 disease. The PLS least squares regression analysis allowed identifying a significant impact between social determinants and COVID-19 disease through a predictive value of R2 = .916, e̱ṯa̱ = .836, p =. 000 (t-value = 66,137) shows that for each unit of increase in social determinants, COVID-19 disease increases by 91.6 clustering index used for correlational analysis generated a new data set comprising three groups: C1 Republicans, C2 and C3 Democrats from California, New York, Texas, and Florida. This analysis made it possible to identify the poverty variable as the main risk factor related to the high rates of infection in Republican states and a high positive correlation between the population not insured with a medical plan and high levels of virus contagion in the states of group C3. These findings explain the argument that poverty and lack of economic security put the public or private health system at risk and calamity.


page 15

page 16

page 22


The COVID-19 pandemic: socioeconomic and health disparities

Disadvantaged groups around the world have suffered and endured higher m...

SARS-CoV-2 Dissemination using a Network of the United States Counties

During 2020 and 2021, severe acute respiratory syndrome coronavirus 2 (S...

Building a COVID-19 Vulnerability Index

COVID-19 is an acute respiratory disease that has been classified as a p...

Using Machine Learning to Develop a Novel COVID-19 Vulnerability Index (C19VI)

COVID19 is now one of the most leading causes of death in the United Sta...

Translation-invariant functional clustering on COVID-19 deaths adjusted on population risk factors

The COVID-19 pandemic has taken the world by storm with its high infecti...

A Machine Learning Analysis of COVID-19 Mental Health Data

In late December 2019, the novel coronavirus (Sars-Cov-2) and the result...

Please sign up or login with your details

Forgot password? Click here to reset