Impact of age, race and ethnicity on the prevalence of COVID-19 in California

Abstract

Covid-19 is a global public health disease that has significantly impacted the world from various domains. Numerous existing studies have analyzed the association of coronavirus with different industries, with the impact of individual patient characteristics on coronavirus transmission being a topic of significant interest. In this study, linear regression models were used to examine the effects of age, race and population distribution on coronavirus morbidity and mortality using data collected on coronavirus in California, USA, for November. Statistical analysis found that coronavirus transmission was significantly influenced by race, which produces consistency with some studies today. Further research is needed on specific differences in coronavirus development between individual races. In addition, the association between age and coronavirus prevalence could not be determined due to the lack of data and limitations of statistical models. Imbalances in healthcare resources, differences in vaccination rates and living environments are all considerable reasons for the association between racial factors and coronavirus transmission. Accordingly, countermeasures can be considered to help mitigate the efficiency of coronavirus transmission and its negative effects on social development.