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BackgroundIn Canada, all provinces implemented vaccine passports in 2021 to increase vaccine uptake and reduce transmission in non-essential indoor spaces. We evaluate the impact of vaccine passport policies on first-dose COVID-19 vaccination coverage by age, area-level income and proportion racialized. MethodsWe performed interrupted time-series analyses using vaccine registry data linked to census information in Quebec and Ontario (20.5 million people [≥]12 years; unit of analysis: dissemination area). We fit negative binomial regressions to weekly first-dose vaccination, using a natural spline to capture pre-announcement trends, adjusting for baseline vaccination coverage (start: July 3rd; end: October 23rd Quebec, November 13th Ontario). We obtain counterfactual vaccination rates and coverage, and estimated vaccine passports impact on vaccination coverage (absolute) and new vaccinations (relative). ResultsIn both provinces, pre-announcement first-dose vaccination coverage was 82% ([≥]12 years). The announcement resulted in estimated increases in vaccination coverage of 0.9 percentage points (p.p.;95%CI:0.4-1.2) in Quebec and 0.7 p.p. (95%CI:0.5-0.8) in Ontario. In relative terms, these increases correspond to 23% (95%CI:10-36%) and 19% (95%CI:15-22%) more vaccinations. The impact was larger among people aged 12-39 (1-2 p.p.). There was little variability in the absolute impact by area-level income or proportion racialized in either province. ConclusionsIn the context of high baseline vaccine coverage across two provinces, the announcement of vaccine passports led to a small impact on first-dose coverage, with little impact on reducing economic and racial inequities in vaccine coverage. Findings suggest the need for other policies to further increase vaccination coverage among lower-income and more racialized neighbourhoods and communities. Key messagesO_LIVaccine passport policies increased COVID-19 vaccination coverage by approximately 1 percentage point (19 to 23% increase in vaccinations) in Quebec and Ontario, Canada. C_LIO_LIAlthough vaccine passport policies increased vaccination coverage, absolute gains were limited in the context of high prior vaccine coverage. C_LIO_LIVaccine passports had little impact on reducing economic and racial inequities in vaccine coverage. C_LI
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BackgroundEpidemic waves of COVID-19 strained hospital resources. We describe temporal trends in mortality risk and length of stay in intensive cares units (ICUs) among COVID-19 patients hospitalized through the first three epidemic waves in Canada. MethodsWe used population-based provincial hospitalization data from Ontario and Quebec to examine mortality risk and lengths of ICU stay. For each province, adjusted estimates were obtained using marginal standardization of logistic regression models, adjusting for patient-level characteristics and hospital-level determinants. ResultsUsing all hospitalizations from Ontario (N=26,541) and Quebec (N=23,857), we found that unadjusted in-hospital mortality risks peaked at 31% in the first wave and was lowest at the end of the third wave at 6-7%. This general trend remained after controlling for confounders. The odds of in-hospital mortality in the highest hospital occupancy quintile was 1.2 (95%CI: 1.0-1.4; Ontario) and 1.6 (95%CI: 1.3-1.9; Quebec) times that of the lowest quintile. Variants of concerns were associated with an increased in-hospital mortality. Length of ICU stay decreased over time from a mean of 16 days (SD=18) to 15 days (SD=15) in the third wave but were consistently higher in Ontario than Quebec by 3-6 days. ConclusionIn-hospital mortality risks and lengths of ICU stay declined over time in both provinces, despite changing patient demographics, suggesting that new therapeutics and treatment, as well as improved clinical protocols, could have contributed to this reduction. Continuous population-based monitoring of patient outcomes in an evolving epidemic is necessary for health system preparedness and response.
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BackgroundThere is a growing recognition that strategies to reduce SARS-CoV-2 transmission should be responsive to local transmission dynamics. Studies have revealed inequalities along social determinants of health, but little investigation was conducted surrounding geographic concentration within cities. We quantified social determinants of geographic concentration of COVID-19 cases across sixteen census metropolitan areas (CMA) in four Canadian provinces. MethodsWe used surveillance data on confirmed COVID-19 cases at the level of dissemination area. Gini (co-Gini) coefficients were calculated by CMA based on the proportion of the population in ranks of diagnosed cases and each social determinant using census data (income, education, visible minority, recent immigration, suitable housing, and essential workers) and the corresponding share of cases. Heterogeneity was visualized using Lorenz (concentration) curves. ResultsGeographic concentration was observed in all CMAs (half of the cumulative cases were concentrated among 21-35% of each citys population): with the greatest geographic heterogeneity in Ontario CMAs (Gini coefficients, 0.32-0.47), followed by British Columbia (0.23-0.36), Manitoba (0.32), and Quebec (0.28-0.37). Cases were disproportionately concentrated in areas with lower income, education attainment, and suitable housing; and higher proportion of visible minorities, recent immigrants, and essential workers. Although a consistent feature across CMAs was concentration by proportion visible minorities, the magnitude of concentration by social determinants varied across CMAs. InterpretationThe feature of geographical concentration of COVID-19 cases was consistent across CMAs, but the pattern by social determinants varied. Geographically-prioritized allocation of resources and services should be tailored to the local drivers of inequalities in transmission in response to SARS-CoV-2s resurgence.
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BackgroundInequities in the burden of COVID-19 observed across Canada suggest heterogeneity within community transmission. ObjectivesTo quantify the magnitude of heterogeneity in the wider community (outside of long-term care homes) in Toronto, Canada and assess how the magnitude in concentration evolved over time (January 21 to November 21, 2020). DesignRetrospective, population-based observational study using surveillance data from Ontarios Case and Contact Management system. SettingToronto, Canada. ParticipantsLaboratory-confirmed cases of COVID-19 (N=33,992). MeasurementsWe generated epidemic curves by SDOH and crude Lorenz curves by neighbourhoods to visualize inequities in the distribution of COVID-19 cases by social determinants of health (SDOH) and estimated the crude Gini coefficient. We examined the correlation between SDOH using Pearson correlation coefficients. ResultsThe Gini coefficient of cumulative cases by population size was 0.41 (95% CI: 0.36-0.47) and were estimated for: household income (0.20, 95%CI: 0.14-0.28); visible minority (0.21, 95%CI: 0.16-0.28); recent immigration (0.12, 95%CI: 0.09-0.16); suitable housing (0.21, 95%CI: 0.14-0.30); multi-generational households (0.19, 95%CI: 0.15-0.23); and essential workers (0.28, 95% CI: 0.23-0.34). Most SDOH were highly correlated. Locally acquired cases were concentrated in higher income neighbourhoods in the early phase of the epidemic, and then concentrated in lower income neighbourhoods. Mirroring the trajectory of epidemic curves by income, the Lorenz curve shifted over time from below to above the line of equality with a similar pattern across SDOH. LimitationsStudy relied on area-based measures of the SDOH and individual case counts of COVID-19. We cannot infer concentration of cases by specific occupational exposures given limitation to broad occupational categories. ConclusionCOVID-19 is increasingly concentrated by SDOH given socioeconomic inequities and structural racism. Primary Funding SourceCanadian Institutes of Health Research.
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BackgroundThe Canadian epidemics of COVID-19 exhibit distinct early trajectories, with Quebec bearing a very high initial burden. The semaine de relache, or March break, took place two weeks earlier in Quebec as compared to the rest of Canada. This event may have played a role in the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We aimed to examine the role of case importation in the early transmission dynamics of SARS-CoV-2 in Quebec. MethodsUsing detailed surveillance data, we developed and calibrated a deterministic SEIR-type compartmental model of SARS-CoV-2 transmission. We explored the impact of altering the number of imported cases on hospitalizations. Specifically, we investigated scenarios without case importation after March break, and as scenarios where cases were imported with the same frequency/timing as neighboring Ontario. ResultsA total of 1,544 and 1,150 returning travelers were laboratory-confirmed in Quebec and Ontario, respectively (with symptoms onset before 2020-03-25). The cumulative number of hospitalizations could have been reduced by 55% (95%CrI: 51-59%) had no cases been imported after Quebecs March break. However, had Quebec experienced Ontarios number of imported cases, cumulative hospitalizations would have only been reduced by 12% (95%CrI: 8-16%). InterpretationOur results suggest that case importation played an important role in the early spread of COVID-19 in Quebec. Yet, heavy importation of SARS-CoV-2 in early March could be insufficient to resolve interprovincial heterogeneities in cumulative hospitalisations. The importance of other factors-public health preparedness, responses, and capacity-should be investigated.