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
Author Information
  1. Erin E Rees: Public Health Risk Sciences Division, National Microbiology Laboratory (PHRSD), Public Health Agency of Canada, Saint-Hyacinthe, QC and Guelph, ON.
  2. Brent P Avery: Food-borne Disease and Antimicrobial Resistance Surveillance Division, Centre for Food-borne and Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON.
  3. Hélène Carabin: Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC.
  4. Carolee A Carson: Food-borne Disease and Antimicrobial Resistance Surveillance Division, Centre for Food-borne and Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON.
  5. David Champredon: Public Health Risk Sciences Division, National Microbiology Laboratory (PHRSD), Public Health Agency of Canada, Saint-Hyacinthe, QC and Guelph, ON.
  6. Simon de Montigny: Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC.
  7. Brendan Dougherty: Food-borne Disease and Antimicrobial Resistance Surveillance Division, Centre for Food-borne and Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON.
  8. Bouchra R Nasri: Centre de recherche en santé publique (CReSP), Université de Montréal, Montréal, QC.
  9. Nicholas H Ogden: Public Health Risk Sciences Division, National Microbiology Laboratory (PHRSD), Public Health Agency of Canada, Saint-Hyacinthe, QC and Guelph, ON.

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.

Keywords

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Word Cloud

Created with Highcharts 10.0.0transmissionstringencyNPIsSARS-CoV-2COVID-19hospitalizationprovinceseffectindexratesinterventionsnumberSaskatchewanOntarioreducecoronavirus2socialassessregressiondataCanadianAlbertaManitobaQuébecmeasuredeffectivepatientsassociatedstatisticallysignificanttime-laggedexceptincreasingnon-pharmaceuticalBackground:Non-pharmaceuticalaimincidencesevereacuterespiratorysyndromeinfectionsmostlylimitingcontactspeopleviruscanoccurHoweverlimitinteractionsnegativeimpactseconomicphysicalmentalwell-beingthereforeimportantimpactreducingdisease2019caseshospitalizationsjustifyuseMethods:DynamicmodelsaccountingautocorrelationtimeseriesusedsixBritishColumbia1usingreproductionhospitalizedResults:IncreasingdecreaseincreaseConclusion:resultssuggestimplementationpartresponseEffectivenessCanadaassociationdynamic

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