A virus that discriminates between rich and poor: Why the data collected matters in the fight against COVID-19

A spike in the number of COVID-19 cases in Montréal-Nord has a prominent anti-racism group demanding public health authorities collect statistics on race, language and income to better target efforts to combat the virus.

The most recent data from Montreal's public health department shows the borough of Montréal-Nord has 1,153 confirmed cases. That's more than any other borough or municipality on the island of Montreal.

Not far behind are the boroughs of Côte-des-Neiges–Notre-Dame-de-Grâce, with 1,137 cases, and Ahuntsic-Cartierville, with 1,064.

While the province is not currently collecting specific data based on race, language or income, Quebec's director of public health, Dr. Horacio Arruda, alluded Thursday to the fact that race and revenue could be at play in Montréal-Nord.

"There is a higher risk of vulnerability in that population because of the socio-economic level, because of the crowding of people in families," Arruda said during the daily government update. "There's going to be screening done tomorrow and in the [coming] days."

But the Montreal-based Center for Research Action on Race Relations says that is not enough. It's calling on public health officials to follow Toronto's lead and collect data on race, language spoken and household income of people who fall ill with COVID-19, in order to better evaluate people's needs.

The group's director, Fo Niemi, said public health data "shows an exponential explosion of cases in areas with high multicultural and multiracial densities" — neighbourhoods that are also overwhelmingly made up of low-income families.

"We have to understand that race and poverty and other socio-economic conditions play a very important role on how people live, adapt to, and cope with COVID-19," Niemi said.

Fewer resources make people more vulnerable

Prof. Geetanjali Datta, a social epidemiologist at Université de Montréal, agrees. She says collecting data simply on which neighbourhoods are affected by the outbreak is not enough.

She said there are other social determinants of health that can predict who is most vulnerable to infection.

"Traditionally what we know from other outbreaks and other infections is that those who are most vulnerable are often racialized populations, people who do not speak French or English, and people who have a lower revenue or lower socioeconomic status that are more highly impacted," said Datta.

"Those who are more vulnerable have fewer resources, are less capable to stay home for their work, and are less capable to socially distance," said Datta.

She said identifying those who are most affected by COVID-19 will allow public health experts to better develop interventions to help.

For instance, they could develop language materials to help inform a particular community, so its members can better protect themselves. They could purchase items such as masks and hand sanitizer for people who might not be able to afford to invest in personal protective gear.

Datta says similar data from the United States has shown "fault lines" according to social determinants of health, with people from black and Latino communities and other groups on the socio-economic rung bearing the brunt of COVID-19 cases.

However, the borough administration for Montréal-Nord says it is not in favour of investigating cases based on race or language.

Coun. Abdelhaq Sari says the borough favours widespread testing, with screening based on age and neighbourhood. Sari worries that testing based on race would stigmatize members of the community.

"What does it help me if I know a black man or an Arabic man [is infected], if they speak Arabic or if they speak Urdu or if they speak English?" said Sari. "It cannot help me to be more efficient in my actions."

Datta says investigating by race or language can be a sensitive issue, and some communities have experienced increased racism because of the pandemic.

"We certainly do not want that to escalate," she said. "This is why the messaging and the careful interpretation of statistics is important. It requires a delicate balance."