Development of a Causal Model to Study the Disparate Effects of COVID-19 on Minorities

Abstract

This paper proposes a systems engineering perspective to analyze the causes of COVID-19 health disparities impact and interventions to minimize the impact on minorities. The impact of the novel coronavirus has shown to be more intense on minorities. The percentage of COVID-19 case count and fatality rate for minorities is much higher than that of the general population, showing that they are more significantly affected than others. Many different factors influence this impact, ranging from economic to cultural. In this paper, these factors are shown to be connected through a causal model analyzing the effects of each factor, after which, potential interventions are suggested. Many factors are identified, such as high employment in the service industry or lower likelihood to have insurance. From this, a causal model is created showing the impact of each factor. Using this causal model, one can identify the high-impact factors causing a disparate impact as well as suggest possible interventions including making testing and treatment more accessible, reducing healthcare bias, and improving healthcare for immigrants.