The Collection of Racial Data About Covid-19

Why the disparate views about the collection of race data on COVID-19?

Posted Sep 28, 2020

As a race scholar trained in the United States, I am fascinated by the debate about the collection of race data on COVID-19 in Canada. Many academics have underscored the importance of race data on COVID-19 infection and death rates. They argue that in the absence of an adequate understanding of the social determinants of health, there is no way to curb the spread of COVID-19.1, 2 The absence of such data will exacerbate racial/ethnic disparities in COVID-19 infection rates.3 Opponents argue that race-based data on COVID-19 should not be collected because it can stigmatize and further marginalize racial minorities.

The two groups frequently say that the other group misunderstands the issues. The former group argues that not having data on racial inequalities does not eradicate racial inequality; it merely eradicates ways to address it.3 The latter group argues that the former group miscalculates the risk associated with de-identified data.4

The two groups have a common goal: they want to minimize the suffering and optimize the well-being of racial minorities. Although both groups have framed the debate in terms of right and wrong, it seems to me that the whole debate is really about differential vantage points. The former group believes in the possibility of improvement once data patterns reveal that racial minorities are more vulnerable to COVID-19. They believe that such a revelation will result in more resources being sent to racial minorities. They believe that such a revelation will usher in social change that will result in a more racially egalitarian society. The latter group feels like such a revelation will just make things worse. It will just give those who are racially biased yet another excuse to discriminate. Not surprisingly, the optimistic and pessimistic divide frequently occurs along socioeconomic lines, with academics frequently on the one hand and members of disadvantaged groups frequently on the other hand.

I am a quantitative sociologist who believes in the power of numbers and transparency. I must admit that I belong to the first group. Part of my predilection comes from my U.S. training where racial inequality is discussed openly. Part of my predilection comes from my socioeconomic privilege and my ability to address issues associated with racial bias when I have been slighted on account of my race. Nonetheless, as I become more familiar with these issues, I have frequently wondered if my preference would have been different if I had been raised in a country where one is told regularly that 'racism does not exist' or spent a longer share of my life living in communities where I have limited means to address racial discrimination.

Even acknowledging this, I continue to believe in the importance of collecting race data on COVID-19. I still believe that people will target resources and help diminish the vulnerability of minority communities when they see that racial minorities are more vulnerable to COVID-19. Overall, I believe in the good that comes with transparency and good social science.


Siddiqi, A., A. Blair, and A. Parnia. (April 16, 2020). A lack of data hides the unequal burden of COVID-19. The Toronto Star. 

Mulligan, K., J. Rayner, and O. Nnorom. (April 30, 2020). Race-based health data urgently needed during the coronavirus pandemic. The Conversation. 

Choi, K., A. Zajacova, M. Haan, P. Denice (May 20,2020). Data linking race and health predicts new COVID-19 hotspots. The Conversation.