he COVID-19 epidemic in Canada has varied in size and trajectory across provinces and large cities. 1,2 At the national level 3 and within regions, 4,5 the burden of confirmed SARS-CoV-2 cases and severe COVID-19 outcomes has fallen disproportionately on socially and economically marginalized communities. 6 Social determinants of health refer to nonmedical factors influencing health outcomes, and structural determinants encompass cultural norms, policies and institutions that generate social stratification and determine socioeconomic position. 7,8 In Canada and elsewhere, data have consistently highlighted the importance of determinants such as household size and density, work in essential services and structural racism (measured by proxy) in the relative risk of COVID-19. [9][10][11][12][13][14][15][16][17] Understanding the factors associated with geographic patterns of transmission within cities can help identify the populations and, specifically, the contexts with the greatest risks. Geographic analyses can enable better allocation of resources, tailoring of policies and implementation of context-specific
Background Inequities in the burden of COVID-19 were observed early in Canada and around the world, suggesting economically marginalized communities faced disproportionate risks. However, there has been limited systematic assessment of how heterogeneity in risks has evolved in large urban centers over time. Purpose To address this gap, we quantified the magnitude of risk heterogeneity in Toronto, Ontario from January to November 2020 using a retrospective, population-based observational study using surveillance data. Methods We generated epidemic curves by social determinants of health (SDOH) and crude Lorenz curves by neighbourhoods to visualize inequities in the distribution of COVID-19 and estimated Gini coefficients. We examined the correlation between SDOH using Pearson-correlation coefficients. Results Gini coefficient of cumulative cases by population size was 0.41 (95% confidence interval [CI]:0.36–0.47) and 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); multigenerational households (0.19, 95%CI:0.15–0.23); and essential workers (0.28, 95%CI:0.23–0.34). Conclusions There was rapid epidemiologic transition from higher- to lower-income neighborhoods with Lorenz curve transitioning from below to above the line of equality across SDOH. Moving forward necessitates integrating programs and policies addressing socioeconomic inequities and structural racism into COVID-19 prevention and vaccination programs.
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Background Gay, bisexual, and other men who have sex with men (gbMSM) experience disproportionate risks of HIV acquisition and transmission. In 2017, Montréal became the first Canadian Fast-Track City, setting the 2030 goal of zero new HIV infections. To inform local elimination efforts, we estimate the evolving role of prevention and sexual behaviours on HIV transmission dynamics among gbMSM in Montréal between 1975 and 2019. Methods Data from local bio-behavioural surveys were analyzed to develop, parameterize, and calibrate an agent-based model of sexual HIV transmission. Partnership dynamics, HIV’s natural history, and treatment and prevention strategies were considered. The model simulations were analyzed to estimate the fraction of HIV acquisitions and transmissions attributable to specific groups, with a focus on age, sexual partnering level, and gaps in the HIV care-continuum. Results The model-estimated HIV incidence peaked in 1985 (2.3 per 100 person years (PY); 90% CrI: 1.4–2.9 per 100 PY) and decreased to 0.1 per 100 PY (90% CrI: 0.04–0.3 per 100 PY) in 2019. Between 2000–2017, the majority of HIV acquisitions and transmissions occurred among men aged 25–44 years, and men aged 35–44 thereafter. The unmet prevention needs of men with > 10 annual anal sex partners contributed 90–93% of transmissions and 67–73% of acquisitions annually. The primary stage of HIV played an increasing role over time, contributing to 11–22% of annual transmissions over 2000–2019. In 2019, approximately 70% of transmission events occurred from men who had discontinued, or never initiated antiretroviral therapy. Conclusions The evolving HIV landscape has contributed to the declining HIV incidence among gbMSM in Montréal. The shifting dynamics identified in this study highlight the need for continued population-level surveillance to identify gaps in the HIV care continuum and core groups on which to prioritize elimination efforts.
doi: medRxiv preprint NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.
Background: Two vaccines against Clostridioides difficile infections (CDI) are currently in phase III trials. To enable decision-making on their use in public health programs, national disease epidemiology is necessary. Objectives: To determine the epidemiology of hospital-acquired CDI (HA-CDI) and communityassociated CDI (CA-CDI) in Canada using provincial surveillance data and document discrepancies in CDI-related definitions among provincial surveillance programs. Methods: Publicly-available CDI provincial surveillance data from 2011 to 2016 that distinguished between HA-CDI and CA-CDI were included and the most common surveillance definitions for each province were used. The HA-, CA-CDI incidence rates and CA-CDI proportions (%) were calculated for each province. Both HA-and CA-CDI incidence rates were examined for trends. Types of disparities were summarized and detailed discrepancies were documented. Results: Canadian data were analyzed from nine provinces. The HA-CDI rates ranged from 2.1/10,000 to 6.5/10,000 inpatient-days, with a decreasing trend over time. Available data on CA-CDI showed that both rates and proportions have been increasing over time. Discrepancies among provincial surveillance definitions were documented in CDI case classifications, surveillance populations and rate calculations. Conclusion: In Canada overall, the rate of HA-CDI has been decreasing and the rate of CA-CDI has been increasing, although this calculation was impeded by discrepancies in CDI-related definitions among provincial surveillance programs. Nationally-adopted common definitions for CDI would enable better comparisons of CDI rates between provinces and a calculation of the pan-Canadian burden of illness to support vaccine decision-making.
Background: Inequities in the burden of COVID-19 observed across Canada suggest heterogeneity within community transmission. Objectives: To 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). Design: Retrospective, population-based observational study using surveillance data from Ontario's Case and Contact Management system. Setting: Toronto, Canada. Participants: Laboratory-confirmed cases of COVID-19 (N=33,992). Measurements: We 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. Results: The 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. Limitations: Study 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. Conclusion: COVID-19 is increasingly concentrated by SDOH given socioeconomic inequities and structural racism. Primary Funding Source: Canadian Institutes of Health Research.
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