Evidence map›Paper›PMID 38162959›Full record

ArticleCanada communicable disease report = Releve des maladies transmissibles au Canada2022

Effectiveness of non-pharmaceutical interventions to reduce SARS-CoV-2 transmission in Canada and their association with COVID-19 hospitalization rates.

Erin E Rees, Brent P Avery, Hélène Carabin, Carolee A Carson, David Champredon, Simon de Montigny, Brendan Dougherty, Bouchra R Nasri, Nicholas H Ogden

Abstract read
In one paragraph

Article in Canada communicable disease report = Releve des maladies transmissibles au Canada, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

8 citing papers in PubMed.

  1. Assessing the costs and benefits of non-pharmaceutical pandemic measures using the economic values of social contacts.The European journal of health economics : HEPAC : health economics in prevention and care · 2026
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  8. Counterfactuals of effects of vaccination and public health measures on COVID-19 cases in Canada: What could have happened?Canada communicable disease report = Releve des maladies transmissibles au Canada · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Erin E ReesPublic Health Risk Sciences Division, National Microbiology Laboratory (PHRSD), Public Health Agency of Canada, Saint-Hyacinthe, QC and Guelph, ON.
Brent P AveryFood-borne Disease and Antimicrobial Resistance Surveillance Division, Centre for Food-borne and Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON.
Hélène CarabinGroupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC.
Carolee A CarsonFood-borne Disease and Antimicrobial Resistance Surveillance Division, Centre for Food-borne and Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON.
David ChampredonPublic Health Risk Sciences Division, National Microbiology Laboratory (PHRSD), Public Health Agency of Canada, Saint-Hyacinthe, QC and Guelph, ON.
Simon de MontignyGroupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC.
Brendan DoughertyFood-borne Disease and Antimicrobial Resistance Surveillance Division, Centre for Food-borne and Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON.
Bouchra R NasriCentre de recherche en santé publique (CReSP), Université de Montréal, Montréal, QC.
Nicholas H OgdenPublic Health Risk Sciences Division, National Microbiology Laboratory (PHRSD), Public Health Agency of Canada, Saint-Hyacinthe, QC and Guelph, ON.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Non-pharmaceutical interventions (NPIs) aim to reduce the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections mostly by limiting contacts between people where virus transmission can occur. However, NPIs limit social interactions and have negative impacts on economic, physical, mental and social well-being. It is, therefore, important to assess the impact of NPIs on reducing the number of coronavirus disease 2019 (COVID-19) cases and hospitalizations to justify their use. Methods: Dynamic regression models accounting for autocorrelation in time series data were used with data from six Canadian provinces (British Columbia, Alberta, Saskatchewan, Manitoba, Ontario, Québec) to assess 1) the effect of NPIs (measured using a stringency index) on SARS-CoV-2 transmission (measured by the effective reproduction number), and 2) the effect of the number of hospitalized COVID-19 patients on the stringency index. Results: Increasing stringency index was associated with a statistically significant decrease in the transmission of SARS-CoV-2 in Alberta, Saskatchewan, Manitoba, Ontario and Québec. The effect of stringency on transmission was time-lagged in all of these provinces except for Ontario. In all provinces except for Saskatchewan, increasing hospitalization rates were associated with a statistically significant increase in the stringency index. The effect of hospitalization on stringency was time-lagged. Conclusion: These results suggest that NPIs have been effective in Canadian provinces, and that their implementation has been, in part, a response to increasing hospitalization rates of COVID-19 patients.

Indexed as

COVID-19 hospitalization ratesdynamic regressionnon-pharmaceutical interventionsSARS-CoV-2 transmission

Identifiers

PMID38162959
PMCPMC10756332

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.