Racial disparities in COVID-19 deaths and years of life lost in Connecticut: An examination of aggregation biases in COVID-19 analyses

Using a novel dataset provided by the Connecticut Department of Health (CTDoH), this manuscript shows the necessity for and added utility from analyzing disaggregated COVID-19 outcome data for applied research. Connecticut is currently ranked the fourth highest state in death rates per 100,000 people from COVID-19 in the United States. Using deidentified death record files provided by the CTDoH, we take a deep dive into the racial and geographic disparity of COVID-19 deaths. The data shows a disproportionately large effect on young minority populations. Comparing the number of deaths in the state from March through May during the pandemic to the previous eight years shows that all ethnic and racial groups have seen an increase in mortality in 2020, but this increase is significantly more dramatic in minority populations, at around a 2-fold increase for blacks and Hispanics. We observe a similar pattern spatially, as towns with a minority-white population have much higher COVID-19 death rates, with some clustering found around the state's major population centers. We also find very little death from COVID-19 in rural towns. We examine other causes of deaths from 2012-2020 as a point of comparison and find some evidence of racial disparities in other forms of death, though all are magnitudes smaller than COVID-19, suggesting that the impact of COVID-19 is unique. There is evidence of some differences in the types of comorbidities present in COVID-19 deaths, but the number of comorbidities is very similar across racial and ethnic groups. Our analysis conforms to much of the published research on racial disparities in COVID-19 deaths but differs in several conclusions. These differences arise because of data aggregation issues and have critical policy implications.