Structural racism and COVID-19 response: Higher risk of exposure drives disparate COVID-19 deaths among Black and Hispanic/Latinx residents of Illinois, USA

Abstract

BACKGROUND: Structural racism has driven and continues to drive policies that create the social, economic, and community factors resulting in residential segregation, lack of access to adequate healthcare, and lack of employment opportunities that would allow economic mobility. This results in overall poorer population health for minoritized people. In 2020, Black and Hispanic/Latinx communities throughout the United States, including the state of Illinois, experienced disproportionately high rates of COVID-19 cases and deaths. Public health officials in Illinois implemented targeted programs at state and local levels to increase intervention access and reduce disparities. METHODS: To quantify how disparities in COVID outcomes evolved through the epidemic, data on SARS-CoV-2 diagnostic tests, COVID-19 cases, and COVID-19 deaths were obtained from the Illinois National Electronic Disease Surveillance System for the period from March 1 to December 31, 2020. Relative risks of COVID-19 cases and deaths were calculated for Black and Hispanic/Latinx vs. White residents, stratified by age group and epidemic interval. Deaths attributable to racial/ethnic disparities in incidence and case fatality were estimated with counterfactual simulations. RESULTS: Disparities in case and death rates became less drastic after May 2020, but did not disappear, and were more pronounced at younger ages. From March to May of 2020, the risk of a COVID-19 case for Black and Hispanic/Latinx populations was more than twice that of Whites across all age groups. The relative risk of COVID-19 death reached above 10 for Black and Hispanic/Latinx individuals under 50 years of age compared to age-matched Whites in the early epidemic. In all Illinois counties, relative risk of a COVID-19 case was the same or significantly increased for minoritized populations compared to the White population. 79.3% and 86.7% of disparities in deaths among Black and Hispanic/Latinx populations, respectively, were attributable to differences in age-adjusted incidence compared to White populations rather than differences in case fatality ratios. CONCLUSIONS: Racial and ethnic disparities in the COVID-19 pandemic are products of society, not biology. Considering age and geography in addition to race/ethnicity can help to identify the structural factors driving poorer outcomes for certain groups. Studies and policies aimed at reducing inequalities in disease exposure will reduce disparities in mortality more than those focused on drivers of case fatality.

Tracking changes in SARS-CoV-2 transmission with a novel outpatient sentinel surveillance system in Chicago, USA

“…Although the daily volume of sentinel samples fluctuated substantially over the study period and the sentinel population was not demographically representative of Chicago’s population at-large, R(t) estimated from sentinel cases was in good agreement with R(t) estimated from hospital data in the general population. Since the COVID-19 pandemic did not affect various racial and ethnic groups to the same extent in Illinois [17], and the sentinel population was more Hispanic/Latino than the general population, the small divergence between sentinel R(t) and hospital-based R(t) could indicate true differences in transmission dynamics between the sentinel and general populations. However, the general agreement in sentinel R(t) and hospital admissions R(t) is impressive given the biased sampling frame of the sentinel cases.…”

“…Incident cases, the fraction of diagnostic tests that return a positive result (test positivity rate, TPR), or any other metric based on diagnostic testing in the general population is subject to bias due to fluctuating access to, availability of, and demand for diagnostic testing. These factors vary across time, geography, age, and racial and ethnic groups, and the data needed to control for these biases is often unavailable [1,[13][14][15][16][17]. The timeliness of data can also be hampered by long turn-around-times and delays in vendors' reporting of test results to health agencies [14].…”

Using machine learning to improve our understanding of COVID-19 infection in children

“…Hispanic males with age less than 8.12 had a high the chance of the infection. In addition, other studies have also reported a discordance of COVID-19 prevalence in Hispanic ethnicities [22]. It is not surprising that the top few important symptoms were gastrointestinal, fever, and congestion as literature suggests these as the common symptoms during COVID-19 infection [23].…”

Reflecting on the COVID‐19 pandemic and moving forward: Make it Matter

“…Services for individuals with childhood-onset disability and their families required rapid shifts to remote or hybrid delivery, 1 while some families experienced a dramatic decline in access. 2 Disparities related to race that existed prior to the pandemic were magnified 3 and disabled children were disproportionately affected by school and health care disruptions. 4 The pandemic demanded reliance on online technology as our main source of connection with colleagues.…”