How Disaggregated Data Can Pave the Way for a More Equitable Recovery

Reflections on COVID-19 racial and ethnic data challenges during Black History Month

Written by Alyson Marks and Chisato Kimura

Source: Yagazie Emezi, Getty Images

Around the world, racial and ethnic disparities are rampant across all sectors of society; from inequities in healthcare, education, and employment to housing, wealth, and criminal justice. Indigenous peoples and racial minorities are also systematically undercounted in censuses. COVID-19 has exacerbated these issues, as people of color, especially Black people, have been disproportionately impacted by the pandemic, both in terms of cases and deaths. Yet much of the COVID-19 data, including on vaccinations, is still not being disaggregated by race or ethnicity, further hampering governments’ ability to formulate effective policies to respond to the pandemic. With over a year since the first COVID-19 case and the rise of new variants and a resurgence in cases globally, countries must do better to disaggregate their data by race and ethnicity.

Racial Data Gaps Around the World

Globally, racial data has been historically lacking. For instance, since World War II, French law has largely prohibited the collection of data on an individual’s race, ethnicity, and religion, and statistical surveys in Germany only offer the category “person with a migrant background” to account for race. And in the U.S., the Black population has been disproportionally undercounted in the census since the 1960s, which limits their access to essential government services and funding, as electoral boundaries are based on population censuses.

These issues have only further intensified during the pandemic.

For most governments worldwide, the extent to which COVID-19 related health outcomes and socio-economic impacts differ for minorities remain largely unknown due to the lack of racial and ethnic data. In Southeast Asia, a review of the official COVID-19 data reporting platforms for Southeast Asian countries, including Cambodia, Malaysia, Myanmar, the Philippines, and Singapore indicates that none of these countries’ governments are collecting and publishing data disaggregated by ethnicity. The same is true for countries in South America, including Brazil, areas of Canada, and especially the U.S. As of October 2020, there were still states in the U.S. not reporting COVID-19 cases and fatalities by race, such as Nebraska, where racial minorities make up more than 17% of the population. And for those states who are disaggregating their data by race, many are failing to collect or report data on specific ethnic groups, including Pacific Islanders, Native Americans, and Asians.

Similarly, with COVID-19 cases and deaths, racial and ethnic data are lacking on who is getting vaccinated. In the U.S., just 20 states include race and ethnicity data on their vaccine dashboards, and only after facing public backlash did the U.K.’s National Health Service recently agree to start recording COVID-19 vaccine ethnicity data.

Yet, with the limited racial data we do have on the impacts of COVID-19, we know that the virus disproportionally impacts ethnic minorities worldwide. For example, indigenous communities in Latin America are among the hardest hit, and Black people in the U.S. account for 21 percent of COVID-19 deaths where race is known, despite making up only 13.4% of the U.S. population. In fact, people of color are likely to be even more significantly impacted than studies show.

The Crucial Need for Disaggregated Data by Race and Ethnicity

Accurate and comprehensive data are critical to defeating this virus. Yet, when the data are not disaggregated by race, policymakers cannot understand the full scope of the problem and ensure equitable access to treatment, testing, and resources. For instance, according to SDSN USA’s recent report, Never More Urgent, the U.S. Centers for Disease Control reported that missing COVID-19 data in indigenous communities stymied efforts to understand what made some communities more vulnerable to the virus than others.

In the few countries that publish disaggregated COVID-19 data by race and ethnicity, the data have been instrumental in highlighting the pandemic’s impact on minorities beyond just the health impacts. For example, despite an increased risk, people of color continue to face greater barriers to COVID-19 testing compared to non-minorities, which are often due to existing social inequalities and environmental factors.

Disaggregated data by race and ethnicity are also helping governments determine where they need to target mitigation efforts. This includes identifying emerging pockets of outbreaks in minority communities and determining where to expand access to testing and vaccines. The data have also been beneficial in enabling governments to plan more culturally appropriate testing, vaccine, and advocacy efforts in minority communities that have been most impacted.

Furthermore, without disaggregated data by race and ethnicity, existing racial gaps and disparities are likely to continue to increase, and it will continue to hamper governments’ efforts to address these issues in the future.

The Way Forward

While it may be more logistically challenging for governments to disaggregate COVID-19 data by race and ethnicity, it is sorely needed.

Fortunately, there are a number of reports and guidance materials available for governments to improve data disaggregation for marginalized groups. For example, UNOCHR’s report, A Human Rights-Based Approach to Data, advocates for involving ethnic minorities and marginalized groups in all aspects of data collection activities, and facilitating the participation of these groups in developing policies. It also posits that National Statistics Offices (NSOs) may need to explore alternate sampling and data collection approaches to allow for disaggregation, particularly for vulnerable communities. The OECD’s Diversity Statistics in the OECD working paper reviews how OECD countries are collecting data on racial and ethnic groups and also offers recommendations for improving disaggregation efforts, including developing national diversity statistical standards to standardize information and allow linking data across sources, and raising the policy importance of racial and ethnic data by including questions in both regular sample surveys and population censuses. Additionally, Colombia’s NSO, DANE, recently launched a new guide, Differential and Intersectional Approaches to Statistical Production, to encourage the standardization of more inclusive, disaggregated data across the national statistical system. Where possible, many of the same principles and recommendations could be applied to countries’ COVID-19 efforts.

There are also a number of organizations working to shine a spotlight on the need for more and better racial data on COVID-19, though based on our research, they are primarily U.S-based. These include: the advocacy group, Data For Black Lives, the COVID Tracking Project, which provides the most complete and up-to-date race and ethnicity data on COVID in the U.S., and the Urban Institute’s Racial Equity Analytics Lab, which generates timely race and ethnicity data and analyses to inform decision-making and identify patterns of structural racism.

The U.S. will become a non-white majority by 2045, and accurate population counts and demographic information will be crucial to prepare for this shift. President Biden’s recent Executive Order on advancing racial equity that established an “Equitable Data Working Group” and calls for the disaggregation of data by race, ethnicity, and other factors is a promising step forward. However, we are still many months away from fully recovering from the pandemic, and it’s clear that racial and ethnic minorities are bearing the brunt of the virus’ impact. Governments must urgently prioritize the collection and publication of COVID-19 data on race and ethnicity to ensure not only an equitable, but an effective recovery effort.