Intersectionality and developing evidence-based policy

It is reassuring to see that ministers in the UK are formally acknowledging how people from minority ethnic (ie, defined here as all ethnicities other than White British) backgrounds have been disproportionately affected by COVID-19. However, crucial gaps exist in the collection, analysis, and translation of data to assess the effects of multiple intersecting factors on individuals and communities. The Science and Technology Committee and Health and Social Care Committee report, Coronavirus: lessons learned to date,¹ dedicates thirteen paragraphs to how ethnicity ties into disparities and makes five recommendations for how the government could avoid these inequities in the future.

This report and those preceding it2, 3 acknowledge poorer COVID-19 outcomes for minority ethnic people than for White British people; they also point to structural and systemic inequalities contributing to the disproportionate effect of the pandemic and the importance of socioeconomic status. The Science and Technology Committee and Health and Social Care Committee report also goes further to attribute increased exposure to the virus to an over-representation of minority ethnic staff in front-line roles, which intersects with other risk factors, such as little access to appropriate personal protective equipment. However, reports still do not make explicit recommendations about how data should be gathered and analysed to investigate how the intersections of occupational risk, ethnicity, and other social and biological factors affect health. The continued failure to strengthen the collection and interpretation of meaningful data around health inequities in diverse populations inhibits the development of evidence-based policy to protect and support minority ethnic communities and key risk groups, such as health-care workers.

Ethnicity, occupation, gender, socio-economic status, migration status, and other sociodemographic factors —including protected characteristics—are too often considered separately and without acknowledging hetero-geneity and intersectionality within populations. As a result, policy making often overlooks how multiple social identities intersect at an individual level to reflect interlocking systems of marginalisation and disadvantage and exacerbate health inequities.

One of the important obstacles in identifying and explaining the over-representation of COVID-19-related deaths in minority ethnic people has been the scarcity of available data across these intersecting factors, for example ethnicity and occupational risk.⁴ Early in the pandemic, research showing the disproportionate effects of COVID-19 on health-care workers from minority ethnic backgrounds had to rely on media reports, underscoring the low availability of robust primary data.⁵ Subsequently, primary research⁶ has been done and new data have been synthesised,⁷ strengthening evidence for the effects of COVID-19 on minority ethnic communities. However, mechanisms are not in place for accessible collection, analysis, and translation of data to assess the effects of multiple intersecting factors on individuals and communities.

Calls for meaningful data for ethnicity6, 8 and the use of an intersectional framework when developing public policy9, 10 have largely gone unheeded, at great human cost. We should build on urgent public health responses, such as the UK research study into ethnicity and COVID-19 outcomes among health-care workers (UK-REACH; ISRCTN11811602), and demand a framework for data gathering that facilitates easy inter-sectional analysis. The upcoming independent public inquiry into the government's handling of the COVID-19 pandemic should include a review of how relevant data are collected and made accessible. Surely one of the key lessons that we should learn from the response to this pandemic is the importance of setting up a robust system for data collection, aggregation, and analysis as a pandemic-preparedness measure rather than a response. This action will not only help to ensure future responses are quicker and more effective than was the initial response to COVID-19 but also that the government is better prepared to identify and address the multiple and intersecting factors driving health inequities.

MP reports grants from Sanofi, grants and personal fees from Gilead Sciences, and personal fees from QIAGEN, unrelated to this Correspondence. All other authors declare no competing interests. MP and LBN are joint senior authors.