ABSTRACT
COVID-19 is one of the largest public health emergencies in modern history. Here we present a detailed analysis from a large population center in Southern California (Orange County, population of 3.2 million) to understand heterogeneity in risks of infection, test positivity, and death. We used a combination of datasets, including a population-representative seroprevalence survey, to assess the true burden of disease as well as COVID-19 testing intensity, test positivity, and mortality. In the first month of the local epidemic, case incidence clustered in high income areas. This pattern quickly shifted, with cases next clustering in much higher rates in the north-central area which has a lower socio-economic status. Since April, a concentration of reported cases, test positivity, testing intensity, and seropositivity in a north-central area persisted. At the individual level, several factors (e.g., age, race/ethnicity, zip codes with low educational attainment) strongly affected risk of seropositivity and death.
