Emergency Department Visits for COVID-19 by Race and Ethnicity — 13 States, October–December 2020

Abstract

Hispanic or Latino (Hispanic), non-Hispanic Black or African American (Black), and non-Hispanic American Indian or Alaska Native (AI/AN) persons have experienced disproportionately higher rates of hospitalization and death attributable to COVID-19 than have non-Hispanic White (White) persons (1-4). Emergency care data offer insight into COVID-19 incidence; however, differences in use of emergency department (ED) services for COVID-19 by racial and ethnic groups are not well understood. These data, most of which are recorded within 24 hours of the visit, might be an early indicator of changing patterns in disparities. Using ED visit data from 13 states obtained from the National Syndromic Surveillance Program (NSSP), CDC assessed the number of ED visits with a COVID-19 discharge diagnosis code per 100,000 population during October-December 2020 by age and race/ethnicity. Among 5,794,050 total ED visits during this period, 282,220 (4.9%) were for COVID-19. Racial/ ethnic disparities in COVID-19 ED visit rates were observed across age groups. Compared with White persons, Hispanic, AI/AN, and Black persons had significantly more COVID-19-related ED visits overall (rate ratio [RR] range = 1.39-1.77) and in all age groups through age 74 years; compared with White persons aged ≥75 years, Hispanic and AI/AN persons also had more COVID-19-related ED visits (RR = 1.91 and 1.22, respectively). These differences in ED visit rates suggest ongoing racial/ethnic disparities in COVID-19 incidence and can be used to prioritize prevention resources, including COVID-19 vaccination, to reach disproportionately affected communities and reduce the need for emergency care for COVID-19.NSSP data were used to assess ED visits with a COVID-19 diagnosis code* during October 1-December 31, 2020. NSSP receives ED visit records from 71% of hospitals in the United States. Data from 13 states (Connecticut,

Age, Disease Severity and Ethnicity Influence Humoral Responses in a Multi-Ethnic COVID-19 Cohort

“…The effects of ethnicity on SARS-CoV-2 infection and disease severity remain largely unknown [ 8 ]. Data reported by the Centre for Disease Control (CDC) suggest that COVID-19 disproportionally affects certain ethnicities [ 37 ]. However, due to other cofounding factors, such as socioeconomic factors and variable access to healthcare, it is challenging to determine whether there is an underlying mechanism to explain the observed disparities in the humoral response between different ethnic groups [ 8 ].…”

The Influence of COVID-19 on the Well-Being of People: Big Data Methods for Capturing the Well-Being of Working Adults and Protective Factors Nationwide

“…There are primarily two approaches to taking social media data, as psychological data and coding them into psychological variables. One such approach is machine learning, which includes methods such as regression and Latent Dirichlet Allocation ( Schwartz et al, 2013 ; Park et al, 2015 ), support vector machine ( Hutto and Gilbert, 2015 ), long short-term memory, convolutional neural network ( Wang et al, 2017 ; Husseini Orabi et al, 2018 ), cross autoencoder ( Lin et al, 2014 ), and the more recently introduced transformer-based pre-trained language models ( Zhang et al, 2020 ). The other is rule-based modeling, which includes the widely used Linguistic Inquiry Word Count (LIWC) and the sentiment analysis tool VADER (i.e., Valence Aware Dictionary and sEntiment Reasoner).…”

“…For example, a CDC official report suggested that the impact of COVID-19 on people is different by race (Smith et al, 2021). Specifically, Hispanic, Black, and Indian Americans have more disproportionate COVID-19 incidents, hospitalization, and mortality than White people (Smith et al, 2021). Moreover, socioeconomic status also influences the impact of COVID-19 such that the poor are likely to experience more difficulties during COVID-19 (Raut et al, 2020).…”

“…First, even though we controlled for some important variables (i.e., county-level GDP per capita and gender) in the analysis, there were some other factors that we were unable to identify (e.g., ethnicity, individual-level socioeconomic status) and, therefore, left uncontrolled. For example, a CDC official report suggested that the impact of COVID-19 on people is different by race ( Smith et al, 2021 ). Specifically, Hispanic, Black, and Indian Americans have more disproportionate COVID-19 incidents, hospitalization, and mortality than White people ( Smith et al, 2021 ).…”

Alternative Methods for Grouping Race and Ethnicity to Monitor COVID-19 Outcomes and Vaccination Coverage

“…Although race and ethnicity are not the only measures for assessing health disparities, these measures have been integral to CDC’s understanding of the health outcomes associated with COVID-19 ( 8 – 10 ). This analysis demonstrates that alternative methods for analyzing race and ethnicity data when data are incomplete can lead to different interpretations about disparities and highlights the importance of working with experts to identify methods for analyzing and tracking disparities when race and ethnicity data are incomplete.…”