At the start of the pandemic, COVID-19 was once termed “the great equalizer”. A calamitous Grim Reaper that took no sides to race, ethnicity, income, or privilege. Anyone and everyone was at risk.

Today, It’s March 29th, 2021, and I write this paper sitting in my single room–an archetypal experience for many among this suburban neighbourhood of middle-class families. It has been a year where in-person interactions have been scant, and I’ve been longing to meet with my friends to play sports, go to the movies, or even just have a face-to-face conversation.

On the other side of the city, and against the backdrop of Ontario’s looming third wave, 27-year old Rechev Brown is waiting for the bus en-route to his job as an essential worker at the grocery store. It’s not long before he is joined by plenty of others from his community, all off to front-line work: groceries, postal service, and manufacturing. Rechev’s mother is asthmatic and he would prefer to stay home to limit the risk of spreading the disease to her. Unfortunately, like many in this part of the city, he has no choice other than to board the overcrowded buses in order to bring home some income. It’s been day-after-day of more in-person interactions than he would prefer–or feel safe with.

Stories like Rechev’s shed light on the contrasting situations experienced by individuals of different neighbourhoods, incomes, and social classes. For some, the pandemic has been a nuisance: working from home, Zoom fatigue, and missing friends and colleagues. For others, the pandemic is a perilous threat faced on a daily basis, exacerbated by disparate access to services. In this tale of two inner-cities, I will elucidate how societal predispositions have left systemically disadvantaged Northwest Toronto more profoundly impacted by the pandemic.

Since having been first detected in humans in December 2019, the COVID-19 virus has quickly spread to millions. Its effectiveness to spread is attributed to its mode of transmission via respiratory droplets – aqueous particles consisting of saliva, mucus, and other matter derived from the respiratory tract. Importantly, respiratory droplets can remain suspended in the air up to 6 feet from an infected person. As a result, the term “physical distancing” was coined, and public health agencies around the world began recommending that individuals stay at least 6 feet apart. However, even staying 6 feet apart (especially indoors) does not guarantee zero risk, and as Rechev’s story points out, social and income predispositions make this a hopeful fantasy for many financially vulnerable families.

In fact, data from Statistics Canada demonstrates that lower-income families were at a much higher risk of becoming infected due to their employment. At the peak of the first wave in Spring 2020, many employments shifted to operating completely online (“teleworking”) in an effort to limit contact, and thus the spread of the disease. However, the extent to which this shift to telework occurred was bifurcated along clear lines of income: nationwide, 25% of families occupy jobs in which both spouses can work from home. This number rises to 54% among those who make up the top 10% by family earnings. However, only a meek 8.1% of families in the lowest 10% (by family earnings) occupy jobs in which both spouses can work from home. As a result, economically disadvantaged families are regularly commuting to work, putting them at an increased risk of contracting COVID-19. In Toronto, low-income individuals comprised 51% of COVID-19 cases, despite making up only 30% of the population.

Moreover, this issue is exacerbated by a systemic, disproportionate access to the services meant to support these essential workers. For example, much of Northwest (NW) Toronto is poorly serviced by public transportation: no subway or LRT exists, and bus service is the only option for many. Furthermore, NW Toronto also has the highest proportion of workers in the transportation and warehousing industry (frontline workers). The result has been an overcrowding of bus routes despite the ongoing pandemic. For this part of the city, a lack of services even extends to healthcare. While much of Southern and Central Toronto have an adequate proportion of physicians to match the healthcare need, many neighbourhoods in NW Toronto have a low number of physicians relative to the primary care needs. Therefore, not only are individuals in NW Toronto at a higher risk of contracting COVID-19, but they are also at a higher risk of not receiving the appropriate care to treat it.

When factors such as employment, public transportation, and healthcare are compounded, a clear picture is painted of the disparities experienced by NW Torontonians. COVID-19 cases have been almost 10x higher in NW Toronto relative to Southern Toronto and the Yonge-Line Corridor. The following table neatly summarizes the three neighbourhoods most and least impacted by COVID-19, by measure of case rate per 100,000 people.

Highest Incidence of COVID-19Lowest Incidence of COVID-19
NeighbourhoodLocation in TorontoCases per 100,000NeighbourhoodLocation in TorontoCases per 100,000
Downsview-Roding-CFBNW1007Kingsway SouthSW32
HumbermedeNW946North RiverdaleS59
Englemount-LawrenceNW814Blake-JonesS78

The conclusions from Table 1 can be extended to illustrate how racialized communities have been disproportion-ally impacted by the pandemic. All three neighbourhoods of highest incidence in Table 1 are also those with high proportions of Black residents. At the city-wide scale, people of colour account for 83% of COVID-19 cases, despite making up only half of Toronto’s population. Al-though most people infected experience mild to moderate symptoms, the disease can escalate to severe symptoms such as respiratory failure and cardiac, kidney, and liver injury, requiring hospitalization. Similarly, people of colour were overrepresented, accounting for 71% of hospitalizations in Toronto.

Why might certain individuals have more severe symptoms? Literature has suggested that cytokines – proteins re-leased by cells – may be important deter-miners of infection severity. First, Type I Interferons (IFN-I), a type of cytokine, has important antiviral functions such as inhibiting viral protein synthesis and inducing degradation of viral genetic material. However, Hadjadj et al. found that severe COVID-19 patients had markedly lower IFN-I responses, and in place, a higher expression of pro-inflammatory cytokines interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α). This observation was also validated by Del Valle and Co., who found that both IL-6 and TNF-α were independent predictors of COVID-19 severity. This over-expression of pro-inflammatory cytokines has come to be termed a “cytokine storm”; various mechanisms of storm to severity have been suggested, from inflammatory blood vessels to the recruitment of inappropriate cell types (e.g. Th2, which combats parasites). Kaneko et al. also postulated that the cytokine storm stunted the formation of germinal centers, locales responsible for B cell proliferation and the fine-tuning of antibodies.

Early research found that Black Americans had immunological predispositions that could increase their risk of severity. Specifically, a study of healthy white and black Americans found the latter to have an increased expression of inflammatory cytokines, possibly putting the group at a higher risk of cytokine-storm mediated effects. Alternatively, Gelaye and others hypothesize that chronic stress induced by socio-economic predispositions result in a de-creased activation of antiviral IFN-I genes. As explained previously, affected individuals would have one less weapon to fight off the infection.

 Nonetheless, whether Gelaye’s mechanism is validated or not, socio-economic factors have indeed exacerbated the effect of COVID-19 on low-income, racialized communities. In NW Toronto, many adults are working front-line jobs and commute on an overcrowded and poorly serviced public transport system. Access to physicians is also proportion-ally lower than in other parts of the city. When amalgamated, these factors undoubtedly increase the risk of contracting the disease, while poorer nutrition and elevated stress levels increase the risk of severity. These observations are not limited to Toronto; studies have re-ported disproportionate impacts on low-income/racialized populations in Montreal, Philadelphia, and more. If any-thing, the pandemic has helped bring to light the systemic predispositions faced by those in vulnerable communities. Learning about stories like Rechev’s will hopefully lead to more action for equitable access to public transportation and health care services. For those of us missing in-person interactions, let’s at least be thankful we don’t face too many.

Figure 1. Percentage of adults occupying jobs that can be performed at home, ordered by family earnings in increments of 10%. Only 8.1% of adults in the lowest 10% (by family earnings) occupy jobs that can be done at home. In contrast, the national average is 25%, and the value for those in the Top 10% is 54%.
Figure 2. Crowding on bus routes operated by the Toronto Transit Commission (TTC). Significant crowding occurs along the Jane St & Wilson Ave corridors in NW Toronto.
Figure 3. Percentage of black residents by census tract in Toronto. The city average is 8.9%. Northwest Toronto has the highest percentage of black residents in the city.
Figure 4. COVID-19 cases in Toronto as of June 26, 2020. The highest number of cases are found in Northwest Toronto
Figure 5. Percentage of occupations in manufacturing and utilities, both non-work-from-home employments. The highest proportions are found in NE and NW Toronto.
Figure 6. Distribution of physicians and primary care needs in Toronto. Southern and central Toronto is generally characterized by low primary need, with varying numbers of physicians. Of particular concern are regions in NW Toronto that have a high primary care need but low number of physicians.

Works Cited

  1. E. Mauro, “Overcrowded buses worry commuters as COVID-19 cases rise, weather turns colder,” CBC, 19 September 2020. [Online]. Available: https://www.cbc.ca/news/canada/toronto/covid-pandemic-overcrowded-transit-toronto-1.5729256.
  2. A. G. Harrison, T. Lin and P. Wang, “Mechanisms of SARS-CoV-2 Transmission and Pathogenesis,” Trends in Immunology, vol. 41, no. 12, pp. 1100-1115, 2020.
  3. “Science Brief: SARS-CoV-2 and Potential Airborne Transmission,” Centers for Disease Control and Prevention (CDC), 5 October 2020. [Online]. Available: https://www.cdc.gov/coronavirus/2019-ncov/science/science-briefs/scientific-brief-sars-cov-2.html.
  4. “Social Distancing,” Centers for Disease Control and Prevention (CDC), 17 Nov 2020. [Online]. Available: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/social-distancing.html.
  5. “Labour Force Survey, April 2020,” Statistics Canada, Ottawa, 2020.
  6. J. Yang, K. Allen, R. Mendleson and A. Bailey, “Toronto’s COVID-19 divide: The city’s northwest corner has been ‘failed by the system’,” Toronto Star, 11 July 2020. [Online]. Available: https://www.thestar.com/news/gta/2020/06/28/torontos-covid-19-divide-the-citys-northwest-corner-has-been-failed-by-the-system.html.
  7. “COVID-19: Status of Cases in Toronto,” City of Toronto, 28 March 2021. [Online]. Available: https://www.toronto.ca/home/covid-19/covid-19-latest-city-of-toronto-news/covid-19-status-of-cases-in-toronto/.
  8. J. Cheung, “Black people and other people of colour make up 83% of reported COVID-19 cases in Toronto,” CBC, 1 August 2020. [Online]. Available: https://www.cbc.ca/news/canada/toronto/toronto-covid-19-data-1.5669091.
    9.D. A. Berlin, R. M. Gulick and F. J. Martinez, “Severe Covid-19,” New England Journal of Medicine, vol. 383, pp. 2451-2460, 2020.
    10.J. Hadjadj, N. Yatim, L. Barnabei, A. Corneau, J. Boussier, N. Smith and B. Terrier, “Impaired type I interferon activity and inflammatory responses in severe COVID-19 patients,” Science, vol. 369, no. 6504, pp. 718-724, 2020.
    11.D. M. Del Valle, S. Kim-Schulze, H.-H. Huang, M. Merad and S. Gnjatic, “An inflammatory cytokine signature predicts COVID-19 severity and survival,” Nature Medicine, vol. 26, p. 1636–1643, 2020.
  9. K. Zimmer, “The Immune Hallmarks of Severe COVID-19,” The Scientist, 16 September 2020. [Online]. Available: https://www.the-scientist.com/news-opinion/the-immune-hallmarks-of-severe-covid-19-67937.
  10. N. Kaneko, H.-H. Kuo, J. Boucau, R. F. Padera and S. Pillai, “The Immune Hallmarks of Severe COVID-19,” Cell, vol. 183, pp. 143-157, 2020.
  11. Y. Tal, A. Adini, A. Eran and I. Adini, “Racial disparity in Covid-19 mortality rates – A plausible explanation,” Clinical Immunology, vol. 217, 2020.
  12. B. Gelaye, S. Foster, M. Bhasin, A. Tawakol and G. Fricchione, “SARS-CoV-2 morbidity and mortality in racial/ethnic minority populations: A window into the stress related inflammatory basis of health disparities?,” Brain, behavior, & immunity – health, vol. 9, 2020.
  13. A. Luft, “COVID-19 hits poorer Montreal boroughs hardest, data reveals, with Montreal North bearing the brunt,” CTV News, 12 May 2020. [Online]. Available: https://montreal.ctvnews.ca/covid-19/covid-19-hits-poorer-montreal-boroughs-hardest-data-reveals-with-montreal-north-bearing-the-brunt-1.4935066.
  14. S. Barber, I. Headen, B. Branch, L. Tabb and K. Yadeta, “COVID-19 IN CONTEXT: RACISM, SEGREGATION, AND RACIAL INEQUITIES IN PHILADELPHIA,” June 2020. [Online]. Available: https://drexel.edu/uhc/resources/briefs/Covid-19%20in%20Context/.
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