Ethnicity and COVID-19 infection: are the pieces of the puzzle falling into place?

Ethnic minority representation in UK COVID-19 trials: systematic review and meta-analysis

BACKGROUND

The COVID-19 pandemic has highlighted health disparities affecting ethnic minority communities. There is growing concern about the lack of diversity in clinical trials. This study aimed to assess the representation of ethnic groups in UK-based COVID-19 randomised controlled trials (RCTs).

METHODS

A systematic review and meta-analysis were undertaken. A search strategy was developed for MEDLINE (Ovid) and Google Scholar (1st January 2020-4th May 2022). Prospective COVID-19 RCTs for vaccines or therapeutics that reported UK data separately with a minimum of 50 participants were eligible. Search results were independently screened, and data extracted into proforma. Percentage of ethnic groups at all trial stages was mapped against Office of National Statistics (ONS) statistics. Post hoc DerSimonian-Laird random-effects meta-analysis of percentages and a meta-regression assessing recruitment over time were conducted. Due to the nature of the review question, risk of bias was not assessed. Data analysis was conducted in Stata v17.0. A protocol was registered (PROSPERO CRD42021244185).

RESULTS

In total, 5319 articles were identified; 30 studies were included, with 118,912 participants. Enrolment to trials was the only stage consistently reported (17 trials). Meta-analysis showed significant heterogeneity across studies, in relation to census-expected proportions at study enrolment. All ethnic groups, apart from Other (1.7% [95% CI 1.1-2.8%] vs ONS 1%) were represented to a lesser extent than ONS statistics, most marked in Black (1% [0.6-1.5%] vs 3.3%) and Asian (5.8% [4.4-7.6%] vs 7.5%) groups, but also apparent in White (84.8% [81.6-87.5%] vs 86%) and Mixed 1.6% [1.2-2.1%] vs 2.2%) groups. Meta-regression showed recruitment of Black participants increased over time (p = 0.009).

CONCLUSIONS

Asian, Black and Mixed ethnic groups are under-represented or incorrectly classified in UK COVID-19 RCTs. Reporting by ethnicity lacks consistency and transparency. Under-representation in clinical trials occurs at multiple levels and requires complex solutions, which should be considered throughout trial conduct. These findings may not apply outside of the UK setting.

Income differences in COVID-19 incidence and severity in Finland among people with foreign and native background: A population-based cohort study of individuals nested within households

BACKGROUND

Although intrahousehold transmission is a key source of Coronavirus Disease 2019 (COVID-19) infections, studies to date have not analysed socioeconomic risk factors on the household level or household clustering of severe COVID-19. We quantify household income differences and household clustering of COVID-19 incidence and severity.

METHODS AND FINDINGS

We used register-based cohort data with individual-level linkage across various administrative registers for the total Finnish population living in working-age private households (N = 4,315,342). Incident COVID-19 cases (N = 38,467) were identified from the National Infectious Diseases Register from 1 July 2020 to 22 February 2021. Severe cases (N = 625) were defined as having at least 3 consecutive days of inpatient care with a COVID-19 diagnosis and identified from the Care Register for Health Care between 1 July 2020 and 31 December 2020. We used 2-level logistic regression with individuals nested within households to estimate COVID-19 incidence and case severity among those infected. Adjusted for age, sex, and regional characteristics, the incidence of COVID-19 was higher (odds ratio [OR] 1.67, 95% CI 1.58 to 1.77, p < 0.001, 28.4% of infections) among individuals in the lowest household income quintile than among those in the highest quintile (18.9%). The difference attenuated (OR 1.23, 1.16 to 1.30, p < 0.001) when controlling for foreign background but not when controlling for other household-level risk factors. In fact, we found a clear income gradient in incidence only among people with foreign background but none among those with native background. The odds of severe illness among those infected were also higher in the lowest income quintile (OR 1.97, 1.52 to 2.56, p < 0.001, 28.0% versus 21.6% in the highest quintile), but this difference was fully attenuated (OR 1.08, 0.77 to 1.52, p = 0.64) when controlling for other individual-level risk factors-comorbidities, occupational status, and foreign background. Both incidence and severity were strongly clustered within households: Around 77% of the variation in incidence and 20% in severity were attributable to differences between households. The main limitation of our study was that the test uptake for COVID-19 may have differed between population subgroups.

CONCLUSIONS

Low household income appears to be a strong risk factor for both COVID-19 incidence and case severity, but the income differences are largely driven by having foreign background. The strong household clustering of incidence and severity highlights the importance of household context in the prevention and mitigation of COVID-19 outcomes.

Association between living in municipalities with high crowding conditions and poverty and mortality from COVID-19 in Mexico

Background

The World Health Organization stated a pandemic by severe acute respiratory syndrome coronavirus SARS-Cov2 (COVID-19) on March, 2020 with devastating implications for populations, healthcare systems, and economies globally.

Objective

The present study explores the association between patients living in municipalities with crowding conditions and poverty and mortality from COVID-19 in Mexico; specifically evaluating the socioeconomic characteristics of the municipality in which the patients reside and some individual characteristics.

Methods

In the present study, we examined public information collected from the National Epidemiological Surveillance System informing all persons tested for SARS-CoV-2 and published by the Ministry of Health. The present analysis was restricted to those with the date of registration to October 12, 2021. The association between the main exposures (overcrowded conditions and poverty) and the outcomes of interest (death by COVID-19) was explored using Cox proportional hazard regression models, including frailty penalties to accommodate multilevel data and random effects for the municipality of case occurrence.

Results

A total of 9619917 subjects were included in the Epidemiological Surveillance System for viral respiratory disease platform. Of those for which results were available, 6141403 were negative for COVID-19 and 3478514 were positive for COVID-19; with a total of 273216 deaths in those who tested positive. Among those positive to COVID-19 mean age was 46.9. Patients living in municipalities with high rates of crowding conditions increased the risk of dying from COVID-19 by 8% (95% CI: 1.03, 1.14). Individuals living in municipalities with indigenous background was associated with an increased risk of dying from COVID-19 (HR = 1.10; 95% CI: 1.04, 1.17). Individuals living in municipalities with illiteracy (HR = 1.09; 95% CI: 1.03, 1.11), poverty (HR = 1.17; 95% CI: 1.14, 1.19), food insecurity (HR = 1.094; 95% CI 1.02, 1.06), limited access to social security (HR = 1.10; 95% CI: 1.08, 1.13) and health services (HR = 1.06; 95% CI: 1.04, 1.08) had a higher risk of mortality from COVID-19.

Conclusion

Our data suggest that patients living in municipalities with higher rates of crowding conditions and higher rates of poverty had elevated risk of mortality from COVID-19. In Mexico, the COVID-19 pandemic is a systemic crisis linked to human development since we have seen that it affects less developed and more vulnerable municipalities. Policies to reduce vulnerabilities and develop strategies to deal with health crises like the current one needs to be considered.

Unweighted lotteries and compounding injustice: reply to Schmidt et al

I argue that Schmidt et al, while correctly diagnosing the serious racial inequity in current ventilator rationing procedures, misidentify a corresponding racial inequity issue in alternative 'unweighted lottery' procedures. Unweighted lottery procedures do not 'compound' (in the relevant sense) prior structural injustices. However, Schmidt et al do gesture towards a real problem with unweighted lotteries that previous advocates of lottery-based allocation procedures, myself included, have previously overlooked. On the basis that there are independent reasons to prefer lottery-based allocation of scarce lifesaving healthcare resources, I develop this idea, arguing that unweighted lottery procedures fail to satisfy healthcare providers' duty to prevent unjust population-level health outcomes, and thus that lotteries weighted in favour of Black individuals (and others who experience serious health injustice) are to be preferred.

Differences in the Prevalence of SARS-CoV-2 Infection and Access to Care between Italians and Non-Italians in a Social-Housing Neighbourhood of Milan, Italy

The northern Italian region of Lombardy has been severely affected by the COVID-19 pandemic since its arrival in Europe. However, there are only a few published studies of the possible influence of social and cultural factors on its prevalence in the general population. This cross-sectional study of the San Siro social-housing neighbourhood of Milan, which was carried about between 23 December 2020 and 19 February 2021, found that the prevalence of anti-SARS-CoV-2 nucleocapsid antibodies in the population as a whole was 12.4% (253/2044 inhabitants), but there was a more than two-fold difference between non-Italians and Italians (23.3% vs. 9.1%). Multivariable analyses showed that being more than 50 years old, living in crowded accommodation, being a non-Italian, and having a low educational level were associated with higher odds of a positive SARS-CoV-2 test, whereas a higher level of education, retirement, and being a former or current cigarette smoker were inversely associated with SARS-CoV-2 infection. Our findings are in line with previous observations indicating that a lower socio-economic status may be a risk factor for COVID-19 and show that non-Italians are disproportionately affected by SARS-CoV-2 infection. This suggests that public health policies should focus more on disadvantaged populations.

COVID-19 and the gendered markets of people and products: explaining inequalities in infections and deaths

COVID-19 has exposed and exploited existing inequalities in gender to drive inequities in health outcomes. Evidence illustrates the relationship between occupation, ethnicity and gender to increase risk of infection in some places. Higher death rates are seen among people also suffering from non-communicable diseases - e.g. heart disease and lung disease driven by exposure to harmful patterns of exposure to corporate products (tobacco, alcohol, ultra-processed foods), corporate by-products (e.g. outdoor air pollution) or gendered corporate processes (e.g. gendered occupational risk). The paper argues that institutional gender blindness in the health system means that underlying gender inequalities have not been taken into consideration in policies and programmatic responses to COVID-19.