Neighbourhood-level socio-demographic characteristics and risk of COVID-19 incidence and mortality in Ontario, Canada: A population-based study

We aimed to estimate associations between COVID-19 incidence and mortality with neighbourhood-level immigration, race, housing, and socio-economic characteristics. We conducted a population-based study of 28,808 COVID-19 cases in the provincial reportable infectious disease surveillance systems (Pub...

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Bibliographic Details
Published in:PloS one Vol. 17; no. 10; p. e0276507
Main Authors: van Ingen, Trevor, Brown, Kevin A., Buchan, Sarah A., Akingbola, Samantha, Daneman, Nick, Warren, Christine M., Smith, Brendan T.
Format: Journal Article
Language:English
Published: United States Public Library of Science 20.10.2022
Public Library of Science (PLoS)
Subjects:
Biology and Life Sciences
Canada
Census of Population
Confidence intervals
Coronaviruses
COVID-19
COVID-19 - epidemiology
Demographics
Demography
Disease transmission
Earth Sciences
Economics
Evaluation
Family Characteristics
Health risks
Health surveillance
Households
Housing
Humans
Immigrants
Immigration
Incidence
Indigenous peoples
Infectious diseases
Low income groups
Medicine and Health Sciences
Mortality
Neighborhoods
Ontario - epidemiology
Pandemics
People and places
Population studies
Population-based studies
Populations
Public health
Race
Residence Characteristics
Social Sciences
Sociodemographics
Socioeconomic Factors
Socioeconomics
Statistical models
Surveillance systems
Trends
Ontario
Canada
Ontario Canada
United Kingdom > UK
United States > US
ISSN:1932-6203, 1932-6203
Online Access:Get full text
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Summary:We aimed to estimate associations between COVID-19 incidence and mortality with neighbourhood-level immigration, race, housing, and socio-economic characteristics. We conducted a population-based study of 28,808 COVID-19 cases in the provincial reportable infectious disease surveillance systems (Public Health Case and Contact Management System) which includes all known COVID-19 infections and deaths from Ontario, Canada reported between January 23, 2020 and July 28, 2020. Residents of congregate settings, Indigenous communities living on reserves or small neighbourhoods with populations <1,000 were excluded. Comparing neighbourhoods in the 90th to the 10th percentiles of socio-demographic characteristics, we estimated the associations between 18 neighbourhood-level measures of immigration, race, housing and socio-economic characteristics and COVID-19 incidence and mortality using Poisson generalized linear mixed models. Neighbourhoods with the highest proportion of immigrants (relative risk (RR): 4.0, 95%CI:3.5-4.5) and visible minority residents (RR: 3.3, 95%CI:2.9-3.7) showed the strongest association with COVID-19 incidence in adjusted models. Among individual race groups, COVID-19 incidence was highest among neighbourhoods with the high proportions of Black (RR: 2.4, 95%CI:2.2-2.6), South Asian (RR: 1.9, 95%CI:1.8-2.1), Latin American (RR: 1.8, 95%CI:1.6-2.0) and Middle Eastern (RR: 1.2, 95%CI:1.1-1.3) residents. Neighbourhoods with the highest average household size (RR: 1.9, 95%CI:1.7-2.1), proportion of multigenerational families (RR: 1.8, 95%CI:1.7-2.0) and unsuitably crowded housing (RR: 2.1, 95%CI:2.0-2.3) were associated with COVID-19 incidence. Neighbourhoods with the highest proportion of residents with less than high school education (RR: 1.6, 95%CI:1.4-1.8), low income (RR: 1.4, 95%CI:1.2-1.5) and unaffordable housing (RR: 1.6, 95%CI:1.4-1.8) were associated with COVID-19 incidence. Similar inequities were observed across neighbourhood-level sociodemographic characteristics and COVID-19 mortality. Neighbourhood-level inequities in COVID-19 incidence and mortality were observed in Ontario, with excess burden experienced in neighbourhoods with a higher proportion of immigrants, racialized populations, large households and low socio-economic status.
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Competing Interests: The authors have declared that no competing interests exist.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0276507