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IntroductionData on vaccine effectiveness (VE) against Omicron in adolescents are limited. We estimated 2-dose and 3-dose VE against Omicron and Delta in adolescents aged 12-17 years in Ontario, Canada. MethodsWe conducted a test-negative design study among SARS-CoV-2-tested adolescents aged 12-17 years between November 22, 2021 (date of first Omicron detection) and March 6, 2022; we assessed Delta outcomes prior to January 2, 2022. We used multivariable logistic regression to compare the odds of vaccination in cases to symptomatic test-negative controls and calculated VE as 1-adjusted odds ratio. ResultsVE was lower against symptomatic Omicron infection than against Delta and decreased more rapidly over time, from 51% (95%CI, 38-61%) in the 7-59 days following a second dose to 29% (95%CI, 17-38%) after 180 days, compared to 97% (95%CI, 94-99%) and 90% (95%CI, 79-95%) for the same intervals against symptomatic Delta infection. Overall, 2-dose VE against severe outcomes caused by Omicron was 85% (95%CI, 74-91%) [≥]7 days following a second dose and estimates were similar over time. VE against symptomatic Omicron infection was 62% (95%CI, 49-72%) [≥]7 days following a third dose. DiscussionTwo-dose VE against symptomatic Omicron infection wanes over time in adolescents. While lower than observed against Delta, protection against severe outcomes appears to be maintained over time. A third dose substantially improves protection against Omicron infection, but 3-dose VE is only moderate at approximately 60% in the early period following vaccination and the duration of this protection is unknown.
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BackgroundThe incidence of SARS-CoV-2 infection, including among those who have received 2 doses of COVID-19 vaccines, increased substantially following the emergence of Omicron in Ontario, Canada. MethodsApplying the test-negative study design to linked provincial databases, we estimated vaccine effectiveness (VE) against symptomatic infection and severe outcomes (hospitalization or death) caused by Omicron or Delta between December 6 and 26, 2021. We used multivariable logistic regression to estimate the effectiveness of 2 or 3 COVID-19 vaccine doses by time since the latest dose, compared to unvaccinated individuals. ResultsWe included 16,087 Omicron-positive cases, 4,261 Delta-positive cases, and 114,087 test-negative controls. VE against symptomatic Delta infection declined from 89% (95%CI, 86-92%) 7-59 days after a second dose to 80% (95%CI, 74-84%) after [≥]240 days, but increased to 97% (95%CI, 96-98%) [≥]7 days after a third dose. VE against symptomatic Omicron infection was only 36% (95%CI, 24-45%) 7-59 days after a second dose and provided no protection after [≥]180 days, but increased to 61% (95%CI, 56-65%) [≥]7 days after a third dose. VE against severe outcomes was very high following a third dose for both Delta and Omicron (99% [95%CI, 98-99%] and 95% [95%CI, 87-98%], respectively). ConclusionsIn contrast to high levels of protection against both symptomatic infection and severe outcomes caused by Delta, our results suggest that 2 doses of COVID-19 vaccines only offer modest and short-term protection against symptomatic Omicron infection. A third dose improves protection against symptomatic infection and provides excellent protection against severe outcomes for both variants.
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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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ObjectiveThe objective of this study was to estimate background rates of selected thromboembolic and coagulation disorders in Ontario, Canada. DesignPopulation-based retrospective observational study using linked health administrative databases. Records of hospitalizations and emergency department visits were searched to identify cases using diagnostic codes from the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Canada (ICD-10-CA). ParticipantsAll Ontario residents. Primary outcome measuresIncidence rates of stroke, deep vein thrombosis, pulmonary embolism, idiopathic thrombocytopenia, disseminated intravascular coagulation, and cerebral venous thrombosis during five pre-pandemic years (2015-2019, annually, averaged, and monthly average) and 2020. ResultsThe average annual population was 14 million with 51% female. The mean annual rates during 2015-2019 were 127.1/100,000 population (95% confidence interval [CI], 126.2, 127.9) for ischemic stroke, 22.0/100,000 (95%CI, 21.6, 22.3) for intracerebral haemorrhage, 9.4 (95%CI, 9.2, 9.7) for subarachnoid haemorrhage, 86.8/100,000 (95%CI, 86.1, 87.5) for deep vein thrombosis, 63.7/100,000 (95%CI, 63.1, 64.3) for pulmonary embolism, 6.1/100,000 (95%CI, 5.9, 6.3) for idiopathic thrombocytopenia, 1.6/100,000 (95%CI, 1.5, 1.7) for disseminated intravascular coagulation, and 1.5/100,000 (95%CI, 1.4, 1.6) for cerebral venous thrombosis. Rates were lower in 2020 than during the pre-pandemic years for ischemic stroke, deep vein thrombosis, and idiopathic thrombocytopenia. Rates were generally consistent over time, except for pulmonary embolism, which increased from 57.1 to 68.5 per 100,000 between 2015 and 2019. Rates were higher for females than males for subarachnoid haemorrhage, pulmonary embolism, and cerebral venous thrombosis, and vice versa for ischemic stroke and intracerebral haemorrhage. Rates increased with age for most of these conditions, but idiopathic thrombocytopenia demonstrated a bimodal distribution with incidence peaks at 0-19 years and [≥]60 years. ConclusionsOur estimated background rates help to contextualize observed events of these potential adverse events of special interest and to detect potential safety signals related to COVID-19 vaccines. Strengths and limitations of this study[tpltrtarr] Recent background rates of selected thromboembolic and coagulation disorders that are potential adverse events special interest related to COVID-19 vaccine are estimated. [tpltrtarr]Background rates during five pre-pandemic (2015-2019) years and 2020 will provide context for these events to identify vaccine safety signals. [tpltrtarr]We used recorded diagnostic codes in administrative data without information on clinical and/or diagnostic confirmation, and the validity of these data are imperfect, which may result in under or overestimation.
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BackgroundNursing home (NH) residents are prioritized for COVID-19 vaccination. We report monthly mortality, hospitalizations, and emergency department (ED) visit incidence rates (IRs) during 2010-2020 to provide context for COVID-19 vaccine safety assessments. MethodsWe observed outcomes among NH residents using administrative databases. IRs were calculated by month, sex, and age group. Comparisons between months were assessed using one-sample t-tests; comparisons by age and sex were assessed using chi-squared tests. ResultsFrom 2010-2019, there were 83,453 (SD: 652.4) NH residents per month, with an average of 2.3 (SD: 0.28) deaths, 3.1 (SD: 0.16) hospitalizations, and 3.6 (SD: 0.17) ED visits per 100 residents per month. From March to December 2020, mortality IRs were increased, but hospitalization and ED visit IRs were reduced (p<0.05). ConclusionWe identified consistent monthly mortality, hospitalization, and ED visit IRs during 2010-2019. Marked differences in these rates were observed during 2020, coinciding with the COVID-19 pandemic.
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Shelter-in-place mandates and closure of non-essential businesses have been central to COVID-19 response strategies including in Toronto, Canada. Approximately half of the working population in Canada are employed in occupations that do not allow for remote work suggesting potentially limited impact of some of the strategies proposed to mitigate COVID-19 acquisition and onward transmission risks and associated morbidity and mortality. We compared per-capita rates of COVID-19 cases and deaths from January 23, 2020 to January 24, 2021, across neighborhoods in Toronto by proportion of the population working in essential services. We used person-level data on laboratory-confirmed COVID-19 community cases (N=74,477) and deaths (N=2319), and census data for neighborhood-level attributes. Cumulative per-capita rates of COVID-19 cases and deaths were 3-fold and 2.5-fold higher, respectively, in neighborhoods with the highest versus lowest concentration of essential workers. Findings suggest that the population who continued to serve the essential needs of society throughout COVID-19 shouldered a disproportionate burden of transmission and deaths. Taken together, results signal the need for active intervention strategies to complement restrictive measures to optimize both the equity and effectiveness of COVID-19 responses.
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BackgroundOptimizing the public health response to reduce coronavirus disease 2019 (COVID-19) burden necessitates characterizing population-level heterogeneity of COVID-19 risks. However, heterogeneity in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing may introduce biased estimates depending on analytic design. MethodsWe explored the potential for collider bias and characterized individual, environmental, and social determinants of testing and diagnosis using cross-sectional analyses among 14.7 million community-dwelling people in Ontario, Canada. Among those diagnosed, we used separate analytic designs to compare predictors of: 1) individuals testing positive versus negative; 2) symptomatic individuals only testing positive versus testing negative; and 3) individuals testing positive versus individuals not testing positive (i.e., testing negative or not being tested). Analyses included tests conducted between March 1 and June 20, 2020. ResultsOf a total of 14,695,579 individuals, 758,691 were tested for SARS-CoV-2, of whom 25,030 (3.3%) tested positive. The further the odds of testing from the null, the more variability observed in the odds of diagnosis across analytic design, particularly among individual factors. There was less variability in testing by social determinants across analytic designs. Residing in areas with highest household density (adjusted odds ratio [aOR]: 1.86; 95%CI: 1.75-1.98), highest proportion of essential workers (aOR: 1.58; 95%CI: 1.48-1.69), lowest educational attainment (aOR: 1.33; 95%CI: 1.26-1.41), and highest proportion of recent immigrants (aOR: 1.10; 95%CI: 1.05-1.15) were consistently related to increased odds of SARS-CoV-2 diagnosis regardless of analytic design. InterpretationWhere testing is limited, risk factors may be better estimated using population comparators rather than test-negative comparators. Optimizing COVID-19 responses necessitates investment and sufficient coverage of structural interventions tailored to heterogeneity in social determinants of risk, including household crowding, occupation, and structural racism.