Abstract
BackgroundIndividual States of the USA have ethnic, economic, community health and education differences that influence the prevalence and outcomes of COVID-19 infection. We hypothesized that Statewide differences in the prevalence and fatality rates of COVID-19 infections are dependent on factors that may be determined by mathematical modeling.MethodsTwo separate statistical regression models were developed using COVID-19 case prevalence and case fatality rates functioning as dependent variables. We obtained data from the prevalence and deaths from COVID-19 cases for each state in the USA that was posted at 4 PM Central Standard Time on April 29, 2020 from the Worldometer website. Publicly available databases were utilized to obtain data for the independent variables in the model.ResultsModels are represented as follows:Statewide COVID-19 Prevalence ModelLog (Statewide COVID_19 case prevalence) = 1.847* (100–250 individuals/mile2) +3.0025*(250+ individuals/mile2) + 1.021* (% African American population) +1.029* (% Hispanic American population +2.164 *(% adults aged 85+)Model results are shown in Table 1.Statewide COVID-19 Case Fatality Rate ModelLog (Statewide COVID_19 case fatality rate) =2.194* (100–250 individuals/mile2) +2.758* (250+ individuals/mile2) +1.031* (% African American population) + 1.032* (% Hispanic American population) + 0.942 (% Native American population)+ 1.108 (% Asian American population) + 2.275 (% adults aged 85+)Model results are shown in Table 2.Table 1: COVID-19 Statewide Prevalence Model Table 2: COVID-19 Statewide Case Fatality Model ConclusionHigher State population density (See Figure 1 and Figure 2) and higher State populations of elderly persons correspond to increased prevalence and case-fatality rates of COVID-19 infections. Statewide data also shows health disparities for COVID-19 infections in Hispanic Americans, African Americans, and Asian Americans. Paradoxically, States with larger populations of Native Americans who have known poor outcomes from COVID-19 infection demonstrate a decrease in case-fatality rates, suggesting a large effect of healthcare inequality in this population.Figure 1: ANOVA one-way analysis of the association between COVID-19 prevalence and population density Figure 2: ANOVA one-way analysis of the association between COVID-19 death prevalence and population density Disclosures Eli D. Ehrenpreis, MD, FACG, AGAF, E2Bio Consultants (Board Member, Chief Executive Officer)E2Bio Life Sciences (Shareholder, Chief Executive Officer)Level Ex, Inc. (Consultant)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.