Racial Disparities in Coronavirus Disease 2019 (COVID-19) Mortality Are Driven by Unequal Infection Risks

Background

As of 1 November 2020, there have been >230 000 deaths and 9 million confirmed and probable cases attributable to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the United States. However, this overwhelming toll has not been distributed equally, with geographic, race/ethnic, age, and socioeconomic disparities in exposure and mortality defining features of the US coronavirus disease 2019 (COVID-19) epidemic.

Methods

We used individual-level COVID-19 incidence and mortality data from the state of Michigan to estimate age-specific incidence and mortality rates by race/ethnic group. Data were analyzed using hierarchical Bayesian regression models, and model results were validated using posterior predictive checks.

Results

In crude and age-standardized analyses we found rates of incidence and mortality more than twice as high than for Whites for all groups except Native Americans. Blacks experienced the greatest burden of confirmed and probable COVID-19 (age-standardized incidence, 1626/100 000 population) and mortality (age-standardized mortality rate, 244/100 000). These rates reflect large disparities, as Blacks experienced age-standardized incidence and mortality rates 5.5 (95% posterior credible interval [CrI], 5.4–5.6) and 6.7 (95% CrI, 6.4–7.1) times higher than Whites, respectively. We found that the bulk of the disparity in mortality between Blacks and Whites is driven by dramatically higher rates of COVID-19 infection across all age groups, particularly among older adults, rather than age-specific variation in case-fatality rates.

Conclusions

This work suggests that well-documented racial disparities in COVID-19 mortality in hard-hit settings, such as Michigan, are driven primarily by variation in household, community, and workplace exposure rather than case-fatality rates.

There are no equal opportunity infectors: Epidemiological modelers must rethink our approach to inequality in infection risk

Mathematical models have come to play a key role in global pandemic preparedness and outbreak response: helping to plan for disease burden, hospital capacity, and inform nonpharmaceutical interventions. Such models have played a pivotal role in the COVID-19 pandemic, with transmission models—and, by consequence, modelers—guiding global, national, and local responses to SARS-CoV-2. However, these models have largely not accounted for the social and structural factors, which lead to socioeconomic, racial, and geographic health disparities. In this piece, we raise and attempt to clarify several questions relating to this important gap in the research and practice of infectious disease modeling: Why do epidemiologic models of emerging infections typically ignore known structural drivers of disparate health outcomes? What have been the consequences of a framework focused primarily on aggregate outcomes on infection equity? What should be done to develop a more holistic approach to modeling-based decision-making during pandemics? In this review, we evaluate potential historical and political explanations for the exclusion of drivers of disparity in infectious disease models for emerging infections, which have often been characterized as “equal opportunity infectors” despite ample evidence to the contrary. We look to examples from other disease systems (HIV, STIs) and successes in including social inequity in models of acute infection transmission as a blueprint for how social connections, environmental, and structural factors can be integrated into a coherent, rigorous, and interpretable modeling framework. We conclude by outlining principles to guide modeling of emerging infections in ways that represent the causes of inequity in infection as central rather than peripheral mechanisms.

Burden of medically attended influenza infection and cases averted by vaccination - United States, 2013/14 through 2015/16 influenza seasons

BACKGROUND

In addition to preventing hospitalizations and deaths due to influenza, influenza vaccination programs can reduce the burden of outpatient visits for influenza. We estimated the incidence of medically-attended influenza at three geographically diverse sites in the United States, and the cases averted by vaccination, for the 2013/14 through 2015/16 influenza seasons.

METHODS

We defined surveillance populations at three sites from the United States Influenza Vaccine Effectiveness Network. Among these populations, we identified outpatient visits laboratory-confirmed influenza via active surveillance, and identified all outpatient visits for acute respiratory illness from healthcare databases. We extrapolated the total number of outpatient visits for influenza from the proportion of surveillance visits with a positive influenza test. We combined estimates of incidence, vaccine coverage, and vaccine effectiveness to estimate outpatient visits averted by vaccination.

RESULTS

Across the three sites and seasons, incidence of medically attended influenza ranged from 14 to 54 per 1000 population. Incidence was highest in children aged 6 months to 9 years (33 to 70 per 1000) and lowest in adults aged 18-49 years (21 to 27 per 1000). Cases averted ranged from 9 per 1000 vaccinees (Washington, 2014/15) to 28 per 1000 (Wisconsin, 2013/14).

DISCUSSION

Seasonal influenza epidemics cause a considerable burden of outpatient medical visits. The United States influenza vaccination program has caused meaningful reductions in outpatient visits for influenza, even in years when the vaccine is not well-matched to the dominant circulating influenza strain.

"You Have to Die Not to Come to Work": A Mixed Methods Study of Attitudes and Behaviors regarding Presenteeism, Absenteeism and Influenza Vaccination among Healthcare Personnel with Respiratory Illness in Israel, 2016-2019

INTRODUCTION

Healthcare personnel (HCP) have an increased risk of exposure to influenza and other respiratory pathogens. Increased presenteeism, decreased absenteeism, and low uptake of the influenza vaccine can contribute to the spread of influenza among HCP in healthcare settings. We used a mixed methods approach to investigate attitudes and behaviors of HCP in Israel towards influenza vaccination, presenteeism, and absenteeism.

METHODS

The study took place over three influenza seasons (2016-2017, 2017-2018, 2018-2019) at the largest hospital in southern Israel. We administered a Knowledge, Attitudes and Practices (KAP) questionnaire and conducted semi-structured interviews with HCP who had been recently ill with respiratory symptoms. The KAP questionnaire included closed-ended questions about attitudes and behaviors regarding influenza, working while sick, and influenza vaccination. The interviews investigated HCP's perceptions of influenza infection and attitudes about absenteeism, presenteeism, and the influenza vaccine.

RESULTS

We conducted 74 semi-structured interviews over three influenza seasons. Four HCP were interviewed twice, in separate seasons for different illness episodes. The 70 individuals interviewed included 16 physicians, 45 nurses or technicians, and 9 administrative staff. The median age was 42.5 years (range: 25-60), and most (79%) were female. Half (50%) got vaccinated against influenza before their illness episode. In interviews, most HCP said they come to work while sick (presenteeism) due to a strong personal work ethic and an institutional culture that discourages taking sick leave (absenteeism). HCP expressed skepticism about the effectiveness of the influenza vaccine as well as concern that the influenza vaccine causes severe illness.

DISCUSSION

Over three influenza seasons in Israel, HCP cited a number of reasons for working while sick, and doubted the usefulness of influenza vaccine. Addressing reasons for presenteeism and vaccine hesitancy among HCP is crucial to protect HCP and patients from influenza virus infection and other viral respiratory illnesses, such as COVID-19.

COVID-19 Immunization Coverage Among People With Sickle Cell Disease

This cross-sectional study compares the completion of the primary COVID-19 vaccine series in Michigan residents with vs without sickle cell disease and by age group.

1642. Comparing Viral Respiratory Infections Between Children Who Do and Do Not Attend Child Care

Background

Out-of-home child care (CC) is a risk factor for viral acute respiratory infection (ARI) in young children. Little is known, however, about differences in frequencies of viral infection between CC children and those cared for exclusively at home.

Methods

Using surveillance data from the HIVE household cohort in southeast Michigan from 2014–2018 (4 seasons), we analyzed 1022 illness cases from 354 children aged 0–6 years. Age groups were dichotomized as infants (aged <2 years) and toddlers/preschoolers (aged 2–6 years). Households were prospectively enrolled and nasal respiratory swabs were collected from children upon report of acute illness symptoms. We used real-time RT–PCR to test for 18 respiratory viruses.

Results

We detected at least one virus in 855 illness cases (83% of all illnesses reported). Age at first illness onset in all four seasons was significantly younger among CC children than homecare children (P < 0.001) across all 4 years (average difference = 1.25 years). CC children <2 years had slightly lower odds of viral detection during illness (OR = 0.89, 95% CI [0.49, 1.61]) but higher odds at ages 2–6y (1.07 [0.65, 1.76]); neither was statistically significant. Neither CC nor homecare children were significantly more or less at risk for any particular pathogen—expect for rhinovirus in the <2-year group, where odds of rhinovirus infection were 58% lower (OR = 0.42) in CC children compared with homecare counterparts (95% CI, 0.21–0.83). Conversely, CC attendees under 3 more frequently had influenza, RSV, hMPV, parainfluenza, and coronavirus; however, none of these associations were significant. Odds of coinfection (> 1 virus detected) were higher among CC children, but not significant (OR = 1.4 [0.63, 2.96] and 1.2 [0.77, 1.88] in <2 year and 2–6 year age groups, respectively). Among all children <7 year, the mean number of pathogens detected was not different between CC and homecare individuals (1.20 vs. 1.23, P = 0.16).

Conclusion

As expected, results indicated that CC attendees aged 0–6y experienced illness episodes earlier in life compared with homecare children. Our analysis also indicated that, compared with children cared for at home, CC children were less at risk for rhinovirus infection when young but could potentially be at higher risk for viruses of greater clinical concern.

Disclosures

All authors: No reported disclosures.

Influenza vaccine effectiveness against hospitalized SARS-CoV-2 infection

Background

Some studies conducted before the Delta and Omicron variant-dominant periods have indicated that influenza vaccination provided protection against COVID-19 infection or hospitalization, but these results were limited by small study cohorts and a lack of comprehensive data on patient characteristics. No studies have examined this question during the Delta and Omicron periods (08/01/2021 to 2/22/2022).

Methods

We conducted a retrospective cohort study of influenza-vaccinated and unvaccinated patients in the Corewell Health East(CHE, formerly known as Beaumont Health), Corewell Health West(CHW, formerly known as Spectrum Health) and Michigan Medicine (MM) healthcare system during the Delta-dominant and Omicron-dominant periods. We used a test-negative, case-control analysis to assess the effectiveness of the influenza vaccine against hospitalized SARS-CoV-2 outcome in adults, while controlling for individual characteristics as well as pandameic severity and waning immunity of COVID-19 vaccine.

Results

The influenza vaccination has shown to provided some protection against SARS-CoV-2 hospitalized outcome across three main healthcare systems. CHE site (odds ratio [OR]=0.73, vaccine effectiveness [VE]=27%, 95% confidence interval [CI]: [18-35], p<0.001), CHW site (OR=0.85, VE=15%, 95% CI: [6-24], p<0.001), MM (OR=0.50, VE=50%, 95% CI: [40-58], p <0.001) and overall (OR=0.75, VE=25%, 95% CI: [20-30], p <0.001).

Conclusion

The influenza vaccine provides a small degree of protection against SARS-CoV-2 infection across our study sites.

Timing of Infection as a Key Driver of Racial/Ethnic Disparities in Coronavirus Disease 2019 Mortality Rates During the Prevaccine Period

Disparities in coronavirus disease 2019 mortality are driven by inequalities in group-specific incidence rates (IRs), case fatality rates (CFRs), and their interaction. For emerging infections, such as severe acute respiratory syndrome coronavirus 2, group-specific IRs and CFRs change on different time scales, and inequities in these measures may reflect different social and medical mechanisms. To be useful tools for public health surveillance and policy, analyses of changing mortality rate disparities must independently address changes in IRs and CFRs. However, this is rarely done. In this analysis, we examine the separate contributions of disparities in the timing of infection-reflecting differential infection risk factors such as residential segregation, housing, and participation in essential work-and declining CFRs over time on mortality disparities by race/ethnicity in the US state of Michigan. We used detailed case data to decompose race/ethnicity-specific mortality rates into their age-specific IR and CFR components during each of 3 periods from March to December 2020. We used these estimates in a counterfactual simulation model to estimate that that 35% (95% credible interval, 30%-40%) of deaths in black Michigan residents could have been prevented if these residents were infected along the timeline experienced by white residents, resulting in a 67% (61%-72%) reduction in the mortality rate gap between black and white Michigan residents during 2020. These results clearly illustrate why differential power to "wait out" infection during an infectious disease emergency-a function of structural racism-is a key, underappreciated, driver of inequality in disease and death from emerging infections.