Evidence map›Paper›PMID 37526916›Full record

ArticleCanadian journal of public health = Revue canadienne de sante publique2023

COVID-19 case rates, spatial mobility, and neighbourhood socioeconomic characteristics in Toronto: a spatial-temporal analysis.

Jack Forsyth, Lu Wang, Andrea Thomas-Bachli

Abstract read
In one paragraph

Article in Canadian journal of public health = Revue canadienne de sante publique, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Jack ForsythToronto Metropolitan University, Toronto, ON, Canada.
Lu WangToronto Metropolitan University, Toronto, ON, Canada. luwang@torontomu.ca.
Andrea Thomas-BachliBlueDot, Toronto, ON, Canada.

Funding

CIHR OV7-170378
6 · The paper itself

Abstract

objectivesThis study has two primary research objectives: (1) to investigate the spatial clustering pattern of mobility reductions and COVID-19 cases in Toronto and their relationships with marginalized populations, and (2) to identify the most relevant socioeconomic characteristics that relate to human mobility and COVID-19 case rates in Toronto's neighbourhoods during five distinct time periods of the pandemic.

methodsUsing a spatial-quantitative approach, we combined hot spot analyses, Pearson correlation analyses, and Wilcoxon two-sample tests to analyze datasets including COVID-19 cases, a mobile device-derived indicator measuring neighbourhood-level time away from home (i.e., mobility), and socioeconomic data from 2016 census and Ontario Marginalization Index. Temporal variations among pandemic phases were examined as well.

resultsThe paper identified important spatial clustering patterns of mobility reductions and COVID-19 cases in Toronto, as well as their relationships with marginalized populations. COVID-19 hot spots were in more materially deprived neighbourhood clusters that had more essential workers and people who spent more time away from home. While the spatial pattern of clusters of COVID-19 cases and mobility shifted slightly over time, the group socioeconomic characteristics that clusters shared remained similar in all but the first time period. A series of maps and visualizations were created to highlight the dynamic spatiotemporal patterns.

conclusionToronto's neighbourhoods have experienced the COVID-19 pandemic in significantly different ways, with hot spots of COVID-19 cases occurring in more materially and racially marginalized communities that are less likely to reduce their mobility. The study provides solid evidence in a Canadian context to enhance policy making and provide a deeper understanding of the social determinants of health in Toronto during the COVID-19 pandemic.

Indexed as

COVID-19HumansOntarioPandemicsResidence CharacteristicsSocioeconomic FactorsCOVID-19Hot spot analysisMarginalizationMobilityNeighbourhood healthToronto

Identifiers

PMID37526916
PMCPMC10486339

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.