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Economically marginalized communities have faced disproportionately higher risks for infection and death from COVID-19 across Canada. It was anticipated that health disparities would dissipate over time and during subsequent waves. We used person-level surveillance and neighbourhood-level income data to explore, using Lorenz curves and Gini coefficients, magnitude of inequalities in COVID-19 hospitalizations and deaths over five waves of COVID-19 in Ontario, Canada (population 14 million) between February 26, 2020 and February 28, 2022. We found that despite attempts at equity-informed policies alongside fluctuating levels of public health measures, inequalities in hospitalizations and deaths by income remained at levels observed during the first wave - prior to vaccination, discussion or implementation of equity-informed policies - and despite rising levels of hybrid immunity. There was no change in the magnitude of inequalities across all waves evaluated. Our findings indicate that interventions did not sufficiently address differential exposure risks amplified at the intersections of household crowding and size, workplace exposures, and systemic barriers to prevention and care (including access to therapeutics). Equity and effectiveness of programs are inherently linked and ongoing evaluation of both is central to inform the public health response to future waves of COVID-19 and other rapidly emergent pandemics.
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Vaccination induced antibody and T-cell immune responses are important for systemic protection from COVID-19. Because SARS-CoV-2 infects and is transmitted by oral-pharyngeal mucosa, we wished to test mucosal antibodies elicited by natural infection or intramuscular vaccine injection. In a non-randomized observational study, we measured antibodies against the SARS-CoV-2 RBD in plasma and saliva from convalescent or vaccinated individuals and tested their neutralizing potential using a replication competent rVSV-eGFP-SARS-CoV-2. We found IgG and IgA anti-RBD antibodies as well as neutralizing activity in convalescent plasma and saliva. Two doses of mRNA vaccination (BNT162b2 or mRNA-1273) induced high levels of IgG anti-RBD in saliva, a subset of whom also had IgA, and significant neutralizing activity. We detected anti-RBD IgG and IgA with significant neutralizing potential in the plasma of single dose Ad26.COV2.S vaccinated individuals, and we detected slight amounts of anti-RBD antibodies in matched saliva. The role of salivary antibodies in protection against SARS-CoV-2 infection is unknown and merits further investigation. This study was not designed to, nor did it study the full kinetics of the antibody response or protection from infection, nor did it address variants of SARS-CoV-2.
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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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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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BackgroundA hospital-level pandemic response involves anticipating local surge in healthcare needs. MethodsWe developed a mechanistic transmission model to simulate a range of scenarios of COVID-19 spread in the Greater Toronto Area. We estimated healthcare needs against 2019 daily admissions using healthcare administrative data, and applied outputs to hospital-specific data on catchment, capacity, and baseline non-COVID admissions to estimate potential surge by day 90 at two hospitals (St. Michaels Hospital [SMH] and St. Josephs Health Centre [SJHC]). We examined fast/large, default, and slow/small epidemics, wherein the default scenario (R0 2.4) resembled the early trajectory in the GTA. ResultsWithout further interventions, even a slow/small epidemic exceeded the citys daily ICU capacity for patients without COVID-19. In a pessimistic default scenario, for SMH and SJHC to remain below their non-ICU bed capacity, they would need to reduce non-COVID inpatient care by 70% and 58% respectively. SMH would need to create 86 new ICU beds, while SJHC would need to reduce its ICU beds for non-COVID care by 72%. Uncertainty in local epidemiological features was more influential than uncertainty in clinical severity. If physical distancing reduces contacts by 20%, maximizing the diagnostic capacity or syndromic diagnoses at the community-level could avoid a surge at each hospital. InterpretationAs distribution of the citys surge varies across hospitals over time, efforts are needed to plan and redistribute ICU care to where demand is expected. Hospital-level surge is based on community-level transmission, with community-level strategies key to mitigating each hospitals surge.
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Background: Scientific editors (i.e., those who make decisions on the content and policies of a journal) have a central role in the editorial process at biomedical journals. However, very little is known about the training needs of these editors or what competencies are required to perform effectively in this role. Methods: We conducted a survey of perceptions and training needs among scientific editors from major editorial organizations around the world, followed by a modified Delphi process in which we invited the same scientific editors to rate the importance of competency-related statements obtained from a previous scoping review. Results: A total of 148 participants completed the survey of perceptions and training needs. At least 80% of participants agreed on six of the 38 skill and expertise-related statements presented to them as being important or very important to their role as scientific editors. At least 80% agreed on three of the 38 statements as necessary skills they perceived themselves as possessing (well or very well). The top five items on participants' list of top training needs were training in statistics, research methods, publication ethics, recruiting and dealing with peer reviewers, and indexing of journals. The three rounds of the Delphi were completed by 83, 83, and 73 participants, respectively, which ultimately produced a list of 23 "highly rated" competency-related statements and another 86 "included" items. Conclusion: Both the survey and the modified Delphi process will be critical for understanding knowledge and training gaps among scientific editors when designing curriculum around core competencies in the future.
