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1.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-22280526

RESUMEN

BackgroundAs of December 30, 2021, Ontario long-term care (LTC) residents who received a third dose of COVID-19 vaccine [≥]84 days previously were offered a fourth dose to prevent a surge in COVID-19-related morbidity and mortality due to the Omicron variant. Seven months have passed since fourth doses were implemented, allowing for the examination of fourth dose protection over time. MethodsWe used a test-negative design and linked databases to estimate the marginal effectiveness (4 versus 3 doses) and vaccine effectiveness (VE; 2, 3, or 4 doses versus no doses) of mRNA vaccines among Ontario LTC residents aged [≥]60 years who were tested for SARS-CoV-2 between December 30, 2021 and August 3, 2022. Outcome measures included any Omicron infection, symptomatic infection, and severe outcomes (hospitalization or death). ResultsWe included 21,275 Omicron cases and 273,466 test-negative controls. The marginal effectiveness of a fourth dose <84 days ago compared to a third dose received [≥]84 days ago was 23% (95% Confidence Interval [CI] 17-29%), 36% (95%CI 26-44%), and 37% (95%CI 24-48%) against SARS-CoV-2 infection, symptomatic infection, and severe outcomes, respectively. Additional protection provided by a fourth dose compared to a third dose was negligible against all outcomes [≥]168 days after vaccination. Compared to unvaccinated individuals, vaccine effectiveness (VE) of a fourth dose decreased from 49% (95%CI 44%-54%) to 18% (95%CI 5-28%) against infection, 69% (95%CI 62-75%) to 44% (95%CI 24-59%) against symptomatic infection, and 82% (95%CI 77-86%) to 74% (95%CI 62-82%) against severe outcomes <84 days versus [≥]168 days after vaccination. ConclusionsOur findings suggest that fourth doses of mRNA COVID-19 vaccines provide additional protection against Omicron-related outcomes in LTC residents, but the protection wanes over time, with more waning seen against infection than severe outcomes.

2.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-22273111

RESUMEN

BackgroundShared and divergent predictors of clinical severity across respiratory viruses may support clinical and community responses in the context of a novel respiratory pathogen. MethodsWe conducted a retrospective cohort study to identify predictors of 30-day all-cause mortality following hospitalization with influenza (N=45,749; 2011-09 to 2019-05), respiratory syncytial virus (RSV; N=24,345; 2011-09 to 2019-04), or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; N=8,988; 2020-03 to 2020-12; pre-vaccine) using population-based health administrative data from Ontario, Canada. Multivariable modified Poisson regression was used to assess associations between potential predictors and mortality. We compared the direction, magnitude, and confidence intervals of risk ratios to identify shared and divergent predictors of mortality. Results3,186 (7.0%), 697 (2.9%) and 1,880 (20.9%) patients died within 30 days of hospital admission with influenza, RSV, and SARS-CoV-2, respectively. Shared predictors of increased mortality included: older age, male sex, residence in a long-term care home, and chronic kidney disease. Positive associations between age and mortality were largest for patients with SARS-CoV-2. Few comorbidities were associated with mortality among patients with SARS-CoV-2 as compared to those with influenza or RSV. ConclusionsOur findings may help identify patients at greatest risk of illness secondary to a respiratory virus, anticipate hospital resource needs, and prioritize local prevention and therapeutic strategies to communities with higher prevalence of risk factors.

3.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-22269169

RESUMEN

BackgroundBackground incidence rates are critical in pharmacovigilance to facilitate identification of vaccine safety signals. We estimated background incidence rates of nine adverse events of special interest related to COVID-19 vaccines in Ontario, Canada. MethodsWe conducted a population-based retrospective observational study using linked health administrative databases for hospitalizations and emergency department visits among Ontario residents. We estimated incidence rates of Bells palsy, idiopathic thrombocytopenia, febrile convulsions, acute disseminated encephalomyelitis, myocarditis, pericarditis, Kawasaki disease, Guillain-Barre syndrome, and transverse myelitis during five pre-pandemic years (2015- 2019) and 2020. ResultsThe average annual population was 14 million across all age groups with 51% female. The pre-pandemic mean annual rates per 100,000 population during 2015-2019 were 43.9 for idiopathic thrombocytopenia, 27.8 for Bells palsy, 25.0 for febrile convulsions, 22.8 for acute disseminated encephalomyelitis, 11.3 for myocarditis/pericarditis, 8.6 for pericarditis, 2.9 for myocarditis, 1.9 for Guillain-Barre syndrome, 1.7 for transverse myelitis, and 1.6 for Kawasaki disease. Females had higher rates of acute disseminated encephalomyelitis and transverse myelitis while males had higher rates of myocarditis, pericarditis, and Guillain-Barre syndrome. Bells palsy, acute disseminated encephalomyelitis, and Guillain-Barre syndrome increased with age. The mean rates of myocarditis and/or pericarditis increased with age up to 79 years; males had higher rates than females: from 12-59 years for myocarditis and [≥]12 years for pericarditis. Febrile convulsions and Kawasaki disease were predominantly childhood diseases and generally decreased with age. ConclusionsOur estimated background rates will permit estimating numbers of expected events for these conditions and facilitate detection of potential safety signals following COVID-19 vaccination.

4.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-21259420

RESUMEN

SARS-CoV-2 variants of concern (VOC) are more transmissible and have the potential for increased disease severity and decreased vaccine effectiveness. We estimated the effectiveness of BNT162b2 (Pfizer-BioNTech Comirnaty), mRNA-1273 (Moderna Spikevax), and ChAdOx1 (AstraZeneca Vaxzevria) vaccines against symptomatic SARS-CoV-2 infection and COVID-19 hospitalization or death caused by the Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), and Delta (B.1.617.2) VOCs in Ontario, Canada using a test-negative design study. Effectiveness against symptomatic infection [≥]7 days after two doses was 89-92% against Alpha, 87% against Beta, 88% against Gamma, 82-89% against Beta/Gamma, and 87-95% against Delta across vaccine products. The corresponding estimates [≥]14 days after one dose were lower. Effectiveness estimates against hospitalization or death were similar to, or higher than, against symptomatic infection. Effectiveness against symptomatic infection is generally lower for older adults ([≥]60 years) compared to younger adults (<60 years) for most of the VOC-vaccine combinations.

5.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-21257744

RESUMEN

ObjectivesTo estimate the effectiveness of mRNA COVID-19 vaccines against symptomatic infection and severe outcomes. DesignWe applied a test-negative design study to linked laboratory, vaccination, and health administrative databases, and used multivariable logistic regression adjusting for demographic and clinical characteristics associated with SARS-CoV-2 and vaccine receipt to estimate vaccine effectiveness (VE) against symptomatic infection and severe outcomes. SettingOntario, Canada between 14 December 2020 and 19 April 2021. ParticipantsCommunity-dwelling adults aged [≥]16 years who had COVID-19 symptoms and were tested for SARS-CoV-2. InterventionsPfizer-BioNTechs BNT162b2 or Modernas mRNA-1273 vaccine. Main outcome measuresLaboratory-confirmed SARS-CoV-2 by RT-PCR; hospitalization/death associated with SARS-CoV-2 infection. ResultsAmong 324,033 symptomatic individuals, 53,270 (16.4%) were positive for SARS-CoV-2 and 21,272 (6.6%) received [≥]1 vaccine dose. Among test-positive cases, 2,479 (4.7%) had a severe outcome. VE against symptomatic infection [≥]14 days after receiving only 1 dose was 60% (95%CI, 57 to 64%), increasing from 48% (95%CI, 41 to 54%) at 14-20 days after the first dose to 71% (95%CI, 63 to 78%) at 35-41 days. VE [≥]7 days after 2 doses was 91% (95%CI, 89 to 93%). Against severe outcomes, VE [≥]14 days after 1 dose was 70% (95%CI, 60 to 77%), increasing from 62% (95%CI, 44 to 75%) at 14-20 days to 91% (95%CI, 73 to 97%) at [≥]35 days, whereas VE [≥]7 days after 2 doses was 98% (95%CI, 88 to 100%). For adults aged [≥]70 years, VE estimates were lower for intervals shortly after receiving 1 dose, but were comparable to younger adults for all intervals after 28 days. After 2 doses, we observed high VE against E484K-positive variants. ConclusionsTwo doses of mRNA COVID-19 vaccines are highly effective against symptomatic infection and severe outcomes. Single-dose effectiveness is lower, particularly for older adults shortly after the first dose.

6.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-21254988

RESUMEN

PurposeThere is limited information on the role of individual- and neighbourhood-level characteristics in explaining the geographic variation in the novel coronavirus 2019 (COVID-19) between regions. This study quantified the magnitude of the variation in COVID-19 rates between neighbourhoods in Ontario, Canada, and examined the extent to which neighbourhood-level differences are explained by census-based neighbourhood measures, after adjusting for individual-level covariates (i.e., age, sex, and chronic conditions). MethodsWe conducted a multilevel population-based study of individuals nested within neighbourhoods. COVID-19 laboratory testing data were obtained from a centralized laboratory database and linked to health-administrative data. The median rate ratio and the variance partition coefficient were used to quantify the magnitude of the neighbourhood-level characteristics on the variation of COVID-19 rates. ResultsThe unadjusted median rate ratio for the between-neighbourhood variation in COVID-19 was 2.22. In the fully adjusted regression models, the individual- and neighbourhood-level covariates accounted for about 44% of the variation in COVID-19 between neighbourhoods, with 43% attributable to neighbourhood-level census-based characteristics. ConclusionNeighbourhood-level characteristics could explain almost half of the observed geographic variation in COVID-19. Understanding how neighbourhood-level characteristics influence COVID-19 rates can support jurisdictions in creating effective and equitable intervention strategies.

7.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-20129783

RESUMEN

BackgroundWe compared the risk of, testing for, and death following COVID-19 infection across three settings (long-term care homes (LTCH), shelters, the rest of the population) in the Greater Toronto Area (GTA), Canada. MethodsWe sourced person-level data from COVID-19 surveillance and reporting systems in Ontario, and examined settings with population-specific denominators (LTCH residents, shelters, and the rest of the population). We calculated cumulatively, the diagnosed cases per capita, proportion tested for COVID-19, daily and cumulative positivity, and case fatality proportion. We estimated the age- and sex-adjusted relative rate ratios for test positivity and case fatality using quasi-Poisson regression. ResultsBetween 01/23/2020-05/25/2020, we observed a shift in the proportion of cases: from travel-related and into LTCH and shelters. Cumulatively, compared to the rest of the population, the number of diagnosed cases per 100,000 was 59-fold and 18-fold higher among LTCH and shelter residents, respectively. By 05/25/2020, 77.2% of LTCH residents compared to 2.4% of the rest of the population had been tested. After adjusting for age and sex, LTCH residents were 2.5 times (95% confidence interval (CI): 2.3-2.8) more likely to test positive. Case fatality was 26.3% (915/3485), 0.7% (3/402), and 3.6% (506/14133) among LTCH residents, shelter population, and others in the GTA, respectively. After adjusting for age and sex, case fatality was 1.4-fold (95%CI: 1.1-1.9) higher among LTCH residents than the rest of the population. InterpretationHeterogeneity across micro-epidemics among specific populations in specific settings may reflect underlying heterogeneity in transmission risks, necessitating setting-specific COVID-19 prevention and mitigation strategies.

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