Shree Paradkar: Covidiots come in all colours. Using race-based data to demonize South Asians is a cruel twisting of the evidence

From the barbaric East Asians and their habits to the villainous South Asians and their dangerous socializing habits, the narrative has traced an interesting if richly trajectory in the eight months since it has afflicted us.

Across the U.K., Canada, the U.S. and other nations, the pandemic is unveiling what health experts have always known: structures birthed in bias and driven by principles of profit have gone on to exacerbate the suffering of people living in the margins.

In June, a by Public Health England said Black and Asian people in England are up to 50 per cent more likely to die after being infected with COVID-19.

In the U.S., by the APM research lab shows Black, Indigenous and Latino Americans experience a death rate triple or more that of white Americans from COVID-19, adjusted for age.

And a StatsCan report last month found people in large visible minority neighbourhoods in B.C, Quebec and Ontario had a much higher likelihood of dying than mostly white neighbourhoods.

There is a growing discussion, in particular, on the role of South Asians who account for nearly half the cases of COVID-19 in the GTA’s Peel region, although they populate about a third of it. Of the 1,417 new cases of COVID-19 Ontario reported Wednesday, about a third, or 463, came from Peel.

All this data.

Data is important to pinpoint where weaknesses lie and where solutions are needed. But of what use data if the collection itself is seen as action against those inequities? Of what use data if the analysis is used to blame communities for cultural deficiencies and individuals for systemic failures?

As the Peel example shows, layer that data with anecdotes and personal experiences of irresponsible socializing and snap, a simplistic narrative is born.

In published last week in the Royal Society of Canada, University of Toronto professor Rinaldo Walcott slammed the gap between calls for race-based data collection and claims it leads to better policy making.

“Race-based data can quite frankly slow down reform,” he wrote. “ ‘Doing the research’ when a problem is already identified and its solutions known, means the collection of race-based data does not actually add much to policymaking. In fact, in some cases, it can do more harm than good.”

Toronto Public Health data has consistently shown disproportionate impacts of COVID in the city’s northwest. Sané Dube, a manager of Community and Policy with Social Medicine at the University Health Network, often takes the 29 Dufferin bus that goes through some of the worst-affected areas. “The 29 often looks like there’s no pandemic. The bus is so full. And people who are going to work are on that bus. Same with the 35 on Jane.”

Public health could ask the TTC to provide more buses on those routes, she says, so that people — many of whom are essential workers, “you know, the people we need to work to be able to survive the pandemic” — don’t have to be on crowded buses.

That is one example of evidence-based action.

If Black people have long been treated as having a cultural abnormality with their broken families — think of the single-mom and absent-father tropes — without a thought to why those families have been ripped apart, now it’s the turn of South Asians to be demonized for the opposite, their multi-generation family homes and their socializing habits.

That there is an affordable housing crisis is well-known. Earlier this month Brampton Mayor Patrick Brown Peel was getting an isolation hotel, a place for people with precarious employment or living in crowded housing to isolate safely. This is another example of evidence-based action. But why the delay?

“That Peel is getting this now — we are in Month 8 of the pandemic. Why are we just getting this now?” Dube asks.

“There is complexity behind this data that goes far deeper than South Asian “culture” or “values,”” Seher Shafiq in First Policy Response, a new project by Ryerson Leadership Lab and other institutions that publishes policy ideas, where she is a managing editor.

“South Asians, like their other racialized peers on the frontlines of this pandemic, are disproportionately employed in precarious jobs in the service industry and gig economy – brewing Tim Hortons coffee, bagging groceries and delivering UberEats orders. This means they are exposed to the virus in their day-to-day lives.”

This “model minority” was by the pandemic recession in October, according to StatsCan.

It’s easier to pathologize communities than implement evidence-based action. Easier to berate people for parties and “multi-day weddings” than to examine if there are adequate testing sites, if they are easily accessible by public transit and if there are adequate supports for those who do test positive.

I have little doubt there are brown covidiots out there, in large homes and small, who think they are impervious to the virus and socialize irresponsibly. I have seen no evidence yet that they are disproportionately more so than any other racial or ethnic group. If there is a blip in numbers after Diwali this past weekend, will it be solidly more than the blip after Thanksgiving? More than after Christmas?

Covidiocy may be unrelated to race but this much is clear: race and culture are very much related to who gets scrutiny and who escapes it.

As East Asians — ironically among the least impacted by the virus — will testify, it doesn’t take long for the blame game to spill over to people and their cultures.

Shree Paradkar is a Toronto-based columnist covering issues around race and gender for the Star. Follow her on Twitter: