Evidence map›Paper›PMID 37581748›Full record

ArticleCanadian journal of public health = Revue canadienne de sante publique2023

Eviction filings during bans on enforcement throughout the COVID-19 pandemic: an interrupted time series analysis.

Erika M Brown, Rahim Moineddin, Ayu Hapsari, Peter Gozdyra, Steve Durant, Andrew D Pinto

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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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Erika M BrownCalifornia Policy Lab, Institute for Research on Labor & Employment, University of California, Berkeley, Berkeley, CA, USA.
Rahim MoineddinDepartment of Family and Community Medicine, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
Ayu HapsariUpstream Lab, MAP/Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, ON, Canada.
Peter GozdyraInstitute for Clinical Evaluative Sciences, Toronto, ON, Canada.
Steve DurantUpstream Lab, MAP/Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, ON, Canada.
Andrew D PintoDepartment of Family and Community Medicine, Faculty of Medicine, University of Toronto, Toronto, ON, Canada. andrew.pinto@utoronto.ca.ORCID http://orcid.org/0000-0003-1841-9347

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveBans on evictions were implemented to reduce the spread of COVID-19 and to protect vulnerable populations during a public health crisis. Our objective was to examine how three bans on eviction enforcement impacted eviction filings from March 2020 through January 2022 in Ontario, Canada.

methodsData were derived from eviction application records kept by the Ontario Landlord and Tenant Board. We used segmented regression analysis to model changes in the average weekly filing rates for evictions due to non-payment of rent (L1 filings) and reasons other than non-payment of rent (L2 filings).

resultsThe average number of weekly L1 and L2 applications dropped by 67.5 (95% CI: 55.2, 79.9) and 31.7 (95% CI: 26.7, 36.6) filings per 100,000 rental dwellings, respectively, following the first ban on eviction enforcement (p < 0.0001). Notably, they did not fall to zero. Level changes during the second and third bans were insubstantial and slope changes for L2 applications varied throughout the study period. The L1 filing rate appeared to increase towards the end of the study period (slope change: 1.3; 95% CI: 0.1, 2.6; p = 0.0387).

conclusionOur findings suggest that while the first ban on eviction enforcement appeared to substantially reduce filing rates, subsequent bans were less effective and none of them eliminated eviction filings altogether. Enacting upstream policies that tackle the root causes of displacement would better equip jurisdictions during future public health emergencies.

Indexed as

COVID-19FilingHousingHumansInterrupted Time Series AnalysisOntarioPandemicsCOVID-19 pandemicHealth policyHousing insecurityIntersectoral collaborationResidential evictionsSocial determinants of health

Identifiers

PMID37581748
PMCPMC10485221

What OpenQuestion holds

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Registered trials

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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.