Increasing concentration of COVID-19 by socioeconomic determinants and geography in Toronto, Canada: an observational study
| Autor: | Kamil Malikov, Tyler Williamson, Gary Moloney, Jeffrey C. Kwong, Stefan Baral, Kristy C.Y. Yiu, Andrew Calzavara, Mathieu Maheu-Giroux, Dariya Darvin, Heather Rilkoff, Sharon E. Straus, Adrienne K Chan, Alan Katz, Rafal Kustra, David Landsman, Beate Sander, Huiting Ma, Yiqing Xia, Effie Gournis, Sharmistha Mishra |
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| Rok vydání: | 2021 |
| Předmět: |
Epidemiology
Disease transmission Population Distribution (economics) SDOH social determinants of health Social determinants of health LTCH long-term care homes Environmental health Humans Lorenz curve education Socioeconomic status Gini coefficients Retrospective Studies Systemic Racism Ontario DA dissemination area education.field_of_study Geography Gini coefficient SARS-CoV-2 business.industry Population size COVID-19 Lorenz curves Health equity CI confidence interval Health inequity Epidemiological transition Socioeconomic Factors STROBE Strengthening the Reporting of Observational Studies in Epidemiology Household income Original Article CCM+ Ontario's Case and Contact Management business Demography |
| Zdroj: | Annals of Epidemiology |
| DOI: | 10.1101/2021.04.01.21254585 |
| Popis: | BackgroundInequities in the burden of COVID-19 observed across Canada suggest heterogeneity within community transmission.ObjectivesTo quantify the magnitude of heterogeneity in the wider community (outside of long-term care homes) in Toronto, Canada and assess how the magnitude in concentration evolved over time (January 21 to November 21, 2020).DesignRetrospective, population-based observational study using surveillance data from Ontario’s Case and Contact Management system.SettingToronto, Canada.ParticipantsLaboratory-confirmed cases of COVID-19 (N=33,992).MeasurementsWe generated epidemic curves by SDOH and crude Lorenz curves by neighbourhoods to visualize inequities in the distribution of COVID-19 cases by social determinants of health (SDOH) and estimated the crude Gini coefficient. We examined the correlation between SDOH using Pearson correlation coefficients.ResultsThe Gini coefficient of cumulative cases by population size was 0.41 (95% CI: 0.36-0.47) and were estimated for: household income (0.20, 95%CI: 0.14-0.28); visible minority (0.21, 95%CI: 0.16-0.28); recent immigration (0.12, 95%CI: 0.09-0.16); suitable housing (0.21, 95%CI: 0.14-0.30); multi-generational households (0.19, 95%CI: 0.15-0.23); and essential workers (0.28, 95% CI: 0.23-0.34). Most SDOH were highly correlated.Locally acquired cases were concentrated in higher income neighbourhoods in the early phase of the epidemic, and then concentrated in lower income neighbourhoods. Mirroring the trajectory of epidemic curves by income, the Lorenz curve shifted over time from below to above the line of equality with a similar pattern across SDOH.LimitationsStudy relied on area-based measures of the SDOH and individual case counts of COVID-19. We cannot infer concentration of cases by specific occupational exposures given limitation to broad occupational categories.ConclusionCOVID-19 is increasingly concentrated by SDOH given socioeconomic inequities and structural racism.Primary Funding SourceCanadian Institutes of Health Research. |
| Databáze: | OpenAIRE |
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