The City of Toronto adopted a Vision Zero strategy in 2016 that aims to eliminate deaths and serious injuries from vehicular collisions. The strategy includes policies to improve lighting to reduce collision risks, and past research has suggested lighting as a road safety factor. We apply Bayesian spatial analysis (including Poisson log-normal regression modelling, shared component spatial modelling, and Bayesian spatiotemporal modelling) to publicly available data on traffic collisions where persons are killed or seriously injured (KSI) based on Day/Dark conditions. We assess (1) links between KSI risk and socioeconomic and built environment factors, (2) spatial distributions of relative Day & Dark KSI risk, and (3) area-specific trends in space and time for Day-Dark KSI risk change across Toronto neighbourhoods. Our analysis does not find significant associations between socioeconomic/built environment factors and KSI risk, but we uncover neighbourhoods with heightened Dark KSI risk and pronounced Day-Dark KSI changes compared to Toronto\'s mean area trend. Findings highlight the need for increased policy attention for impacts of lighting on collisions and provide insight for focus regions for improved Vision Zero policy development.

This study has two primary research objectives: (1) to investigate the spatial clustering pattern of mobility reductions and COVID-19 cases in Toronto and their relationships with marginalized populations, and (2) to identify the most relevant socioeconomic characteristics that relate to human mobility and COVID-19 case rates in Toronto\'s neighbourhoods during five distinct time periods of the pandemic.
Using a spatial-quantitative approach, we combined hot spot analyses, Pearson correlation analyses, and Wilcoxon two-sample tests to analyze datasets including COVID-19 cases, a mobile device-derived indicator measuring neighbourhood-level time away from home (i.e., mobility), and socioeconomic data from 2016 census and Ontario Marginalization Index. Temporal variations among pandemic phases were examined as well.
The paper identified important spatial clustering patterns of mobility reductions and COVID-19 cases in Toronto, as well as their relationships with marginalized populations. COVID-19 hot spots were in more materially deprived neighbourhood clusters that had more essential workers and people who spent more time away from home. While the spatial pattern of clusters of COVID-19 cases and mobility shifted slightly over time, the group socioeconomic characteristics that clusters shared remained similar in all but the first time period. A series of maps and visualizations were created to highlight the dynamic spatiotemporal patterns.
Toronto\'s neighbourhoods have experienced the COVID-19 pandemic in significantly different ways, with hot spots of COVID-19 cases occurring in more materially and racially marginalized communities that are less likely to reduce their mobility. The study provides solid evidence in a Canadian context to enhance policy making and provide a deeper understanding of the social determinants of health in Toronto during the COVID-19 pandemic.
RéSUMé: OBJECTIFS: Cette étude a deux grands objectifs de recherche : 1) examiner les schémas d’agrégation spatiale des baisses de mobilité et des cas de COVID-19 à Toronto et leurs liens avec les populations marginalisées; et 2) cerner les caractéristiques socioéconomiques les plus pertinentes liées à la mobilité humaine et aux taux de cas de COVID-19 dans les quartiers de Toronto au cours de cinq périodes distinctes de la pandémie. MéTHODE: À l’aide d’une approche spatio-quantitative, nous avons combiné des analyses de points chauds, des analyses de corrélation de Pearson et des tests de Wilcoxon à deux échantillons pour analyser des ensembles de données incluant : les cas de COVID-19, un indicateur dérivé d’appareils mobiles pour mesurer le temps passé à l’extérieur du domicile au niveau du quartier (c.-à-d. la mobilité), ainsi que les données socioéconomiques du recensement de 2016 et de l’indice de marginalisation ontarien. Nous avons aussi examiné les variations temporelles entre les phases de la pandémie. RéSULTATS: Nous avons repéré d’importants schémas d’agrégation spatiale des baisses de mobilité et des cas de COVID-19 à Toronto, ainsi que leurs liens avec les populations marginalisées. Les points chauds de la COVID-19 se trouvaient dans des grappes de quartiers plus défavorisés sur le plan matériel, où il y avait davantage de travailleurs essentiels et de personnes passant du temps à l’extérieur de leur domicile. La structure spatiale des grappes de cas de COVID-19 et de la mobilité a légèrement changé au fil du temps, mais les caractéristiques des groupes socioéconomiques communes à toutes les grappes sont restées semblables durant toutes les périodes sauf la première. Nous avons créé une série de cartes et de visualisations pour faire ressortir les schémas spatio-temporels dynamiques. CONCLUSION: Les quartiers de Toronto ont vécu la pandémie de COVID-19 de façons très différentes : les points chauds des cas de COVID-19 sont survenus dans des communautés plus marginalisées sur le plan matériel et racial et moins susceptibles de réduire leur mobilité. L’étude fournit des preuves solides dans un contexte canadien pour améliorer l’élaboration des politiques et approfondir la compréhension des déterminants sociaux de la santé à Toronto pendant la pandémie de COVID-19.

In the past decade, a group of studies has begun to explore the association between cannabis recreational use policies and traffic crashes. After these policies are set in place, several factors may affect cannabis consumption, including the number of cannabis stores (NCS) per capita. This study examines the association between the enactment of Canada\'s Cannabis Act (CCA) (18 October 2018) and the NCS (allowed to function from 1 April 2019) with traffic injuries in Toronto.
We explored the association of the CCA and the NCS with traffic crashes. We applied two methods: hybrid difference-in-difference (DID) and hybrid-fuzzy DID. We used generalised linear models using CCA and the NCS per capita as the main variables of interest. We adjusted for precipitation, temperature and snow. Information is gathered from Toronto Police Service, Alcohol and Gaming Commission of Ontario, and Environment Canada. The period of analysis was from 1 January 2016 to 31 December 2019.
Regardless of the outcome, neither the CCA nor the NCS is associated with concomitant changes in the outcomes. In hybrid DID models, the CCA is associated with non-significant decreases of 9% (incidence rate ratio 0.91, 95% confidence interval 0.74,1.11) in traffic crashes and in the hybrid-fuzzy DID models, the NCS are associated with nonsignificant decreases of 3% (95% confidence interval - 9%, 4%) in the same outcome.
This study observes that more research is needed to better understand the short-term effects (April to December 2019) of NCS in Toronto on road safety outcomes.

We evaluated the potential impacts from using a rapid same-day quantitative polymerase chain reaction (qPCR) monitoring method for beach posting outcomes at two Toronto beaches.
In total, 228 water samples were collected at Marie Curtis Park East and Sunnyside Beaches over the 2021 summer season. Water samples were processed using the USEPA 1609.1 Enterococcus qPCR-based method. Escherichia coli (E. coli) culture data and daily beach posting decisions were obtained from Toronto Public Health.
No significant correlation was observed between previous-day and same-day (retrospective) E. coli enumeration results at any Sunnyside Beach transect, and only relatively low (R = 0.41-0.56) or no significant correlation was observed at sampling transects for Marie Curtis Park East Beach. Comparing our same-day Enterococcus qPCR data to Toronto\'s 2-day E. coli geometric mean beach posting decisions, we noted the need for additional postings for 1 (2%) and 3 (8%) missed health-risk days at Sunnyside and Marie Curtis Park East Beaches, respectively. The qPCR data also pointed to incorrect postings for 12 (31%) and 6 (16%) lost beach days at Sunnyside and Marie Curtis Park East Beaches, respectively.
Application of a rapid Enterococcus qPCR method at two Toronto beaches revealed 5% of beach posting decisions were false negatives that missed health-risk days, while 23% of decisions were false positives resulting in lost beach days. Deployment of the rapid same-day qPCR method offers the potential to reduce both health risks and unnecessary beach postings.
RéSUMé: OBJECTIFS: Nous avons évalué, à deux plages de Toronto, l’effet possible de l’utilisation d’une méthode de surveillance rapide par PCR quantitative (qPCR) le même jour sur les avis de fermeture ou d’ouverture des plages. MéTHODE: En tout, 228 échantillons d’eau ont été prélevés aux plages Marie Curtis Park East et Sunnyside au cours de la saison estivale 2021. La présence d’Enterococcus dans les échantillons a été détectée par la méthode USEPA 1609.1, utilisant la qPCR. Les données sur les cultures d’Escherichia coli (E. coli) et les avis quotidiens de fermeture ou d’ouverture des plages ont été obtenus auprès du Bureau de santé de Toronto. RéSULTATS: Aucune corrélation significative n’a été observée entre les résultats (rétrospectifs) du dénombrement de E. coli obtenus la veille et le même jour dans les transects de la plage Sunnyside, et une corrélation significative faible (R = 0,41–0,56) ou nulle a été observée dans les transects d’échantillonnage de la plage Marie Curtis Park East. En comparant nos données sur Enterococcus obtenues le même jour par qPCR à la moyenne géométrique des avis de fermeture ou d’ouverture des plages sur deux jours liés à E. coli émis par le Bureau de santé de Toronto, nous avons remarqué qu’il aurait fallu émettre des avis de fermeture pour 1 jour de risques pour la santé manqué (2 %) à la plage Sunnyside et pour 3 jours de risques pour la santé manqués (8 %) à la plage Marie Curtis Park East. Les données de la qPCR ont aussi fait état d’avis de fermeture incorrects ayant entraîné la perte de 12 jours de plage (31 %) à Sunnyside et de 6 jours de plage (16 %) à Marie Curtis Park East. CONCLUSION: L’application d’une méthode de surveillance rapide d’Enterococcus par qPCR à deux plages de Toronto a montré que 5 % des avis étaient des faux négatifs qui n’ont pas détecté des jours de risques pour la santé, et que 23 % étaient des faux positifs qui ont entraîné des jours de plage perdus. Le déploiement de la méthode rapide par qPCR le même jour offre la possibilité de réduire à la fois les risques pour la santé et les avis de fermeture de plages inutiles.

Several ursodeoxycholic acid (UDCA) treatment response definitions have been introduced in primary biliary cholangitis (PBC). However, the lack of a gold standard results in heterogeneity in second-line treatment research and clinical practice.
This study aimed to explore which UDCA treatment response endpoint serves as the most accurate predictive model of long-term outcome.
A systematic review and meta-analysis of UDCA treatment response endpoints (and corresponding validations) were performed.
Sixteen individual UDCA treatment response endpoints and 96 external validations were found. Barcelona, Paris-1, Paris-2, Rotterdam, Toronto and GLOBE and UK-PBC Risk Scores are currently most robustly validated in external populations. The results show that the continuous models (GLOBE and UK-PBC Risk Scores) serve as the most accurate predictive models. Besides standard UDCA treatment response endpoints, the alkaline phosphatase and total bilirubin normalization has been suggested as a new therapeutic target.
The GLOBE and UK-PBC Risk Scores are the most suitable for the real-world allocation of second-line therapies (obeticholic acid and fibrates). However, in the wake of the recent findings, alkaline phosphatase and total bilirubin normalization should be the primary outcome in trial research in PBC.

People experiencing homelessness were prioritized for COVID-19 vaccination in Toronto, Canada, due to the high risk of infection and associated complications relative to the general population. We aimed to ascertain COVID-19 vaccine coverage in this population and explore factors associated with the receipt of at least one dose. We collected survey and blood sample data from individuals ages 16+ recruited by random selection at 62 shelters, hotels and encampment sites between 16 June 2021 and 9 September 2021. We report vaccine coverage by dose number and explored sociodemographic, behavioral, health and housing factors associated with vaccination using multivariable modified Poisson regression. In total, 80.4% (95% CI 77.3-83.1%) received at least one vaccine dose, and 63.6% (CI 60.0-67.0%) received two or more doses. Vaccination was positively associated with age (every 10 years adjusted rate ratio (aRR) 1.05 [95% CI 1.03-1.08]), and receipt of influenza vaccination (aRR 1.19 [95% CI 1.11-1.27]). Factors negatively associated with vaccination included female gender (aRR 0.92 [95% CI 0.85-1.0]), Black racial self-identification (aRR 0.89 [95% CI 0.80-0.99]) and low frequencies of masking in public places (aRR 0.83 [95% CI 0.72-0.95]). COVID-19 vaccine coverage is very high among people experiencing homelessness in Toronto, suggesting advocacy and outreach efforts may have been effective.

OBJECTIVE: Homicide rate is associated with a large variety of factors and therefore unevenly distributed over time and space. This study aims to explore homicide patterns and their spatial associations with different socioeconomic and built-environment conditions in 140 neighbourhoods of the city of Toronto, Canada.
METHODS: A homicide dataset covering the years 2012 to 2021 and neighbourhood-based indicators were analysed using spatial techniques such as Kernel Density Estimation, Global/Local Moran\'s I and Kulldorff\'s SatScan spatio-temporal methodology. Geographically weighted regression (GWR) and multi-scale GWR (MGWR) were used to analyse the spatially varying correlations between the homicide rate and independent variables. The latter was particularly suitable for manifested spatial variations between explanatory variables and the homicide rate and it also identified spatial non-stationarities in this connection.
RESULTS: The adjusted R2 of the MGWR was 0.53, representing a 4.35 and 3.74% increase from that in the linear regression and GWR models, respectively. Spatial and spatio-temporal high-risk areas were found to be significantly clustered in downtown and the north-western parts of the city. Some variables (e.g., the population density, material deprivation, the density of commercial establishments and the density of large buildings) were significantly associated with the homicide rate in different spatial ways.
CONCLUSIONS: The findings of this study showed that homicide rates were clustered over time and space in certain areas of the city. Socioeconomic and the built environment characteristics of some neighbourhoods were found to be associated with high homicide rates but these factors were different for each neighbourhood.

Since Angus Campbell and colleagues first introduced the \"levels of conceptualization\" (LoC) framework as a measure of political sophistication, a number of scholars have applied the approach to subsequent American national elections. In this study, we present the first application of the LoC framework to a municipal election, and focus upon the 2018 Toronto mayoral race. After describing the method and data we use to adapt the framework to this new context, we replicate previous analyses, and find that LoC is related to local voter turnout and several measures of political sophistication. We then consider the question of whether major candidates were discussed at different LoC, and if their supporters view local politics at different LoC. We conclude by making the case that the LoC framework is helpful for resolving the debate over whether local politics are ideological or managerial in nature.

BACKGROUND: Disproportionate risks of COVID-19 in congregate care facilities including long-term care homes, retirement homes, and shelters both affect and are affected by SARS-CoV-2 infections among facility staff. In cities across Canada, there has been a consistent trend of geographic clustering of COVID-19 cases. However, there is limited information on how COVID-19 among facility staff reflects urban neighborhood disparities, particularly when stratified by the social and structural determinants of community-level transmission.
OBJECTIVE: This study aimed to compare the concentration of cumulative cases by geography and social and structural determinants across 3 mutually exclusive subgroups in the Greater Toronto Area (population: 7.1 million): community, facility staff, and health care workers (HCWs) in other settings.
METHODS: We conducted a retrospective, observational study using surveillance data on laboratory-confirmed COVID-19 cases (January 23 to December 13, 2020; prior to vaccination rollout). We derived neighborhood-level social and structural determinants from census data and generated Lorenz curves, Gini coefficients, and the Hoover index to visualize and quantify inequalities in cases.
RESULTS: The hardest-hit neighborhoods (comprising 20% of the population) accounted for 53.87% (44,937/83,419) of community cases, 48.59% (2356/4849) of facility staff cases, and 42.34% (1669/3942) of other HCW cases. Compared with other HCWs, cases among facility staff reflected the distribution of community cases more closely. Cases among facility staff reflected greater social and structural inequalities (larger Gini coefficients) than those of other HCWs across all determinants. Facility staff cases were also more likely than community cases to be concentrated in lower-income neighborhoods (Gini 0.24, 95% CI 0.15-0.38 vs 0.14, 95% CI 0.08-0.21) with a higher household density (Gini 0.23, 95% CI 0.17-0.29 vs 0.17, 95% CI 0.12-0.22) and with a greater proportion working in other essential services (Gini 0.29, 95% CI 0.21-0.40 vs 0.22, 95% CI 0.17-0.28).
CONCLUSIONS: COVID-19 cases among facility staff largely reflect neighborhood-level heterogeneity and disparities, even more so than cases among other HCWs. The findings signal the importance of interventions prioritized and tailored to the home geographies of facility staff in addition to workplace measures, including prioritization and reach of vaccination at home (neighborhood level) and at work.

In 2015, Toronto\'s largest LGBTQ2S organization, the city, and a private donor collaborated and proposed what they believed constituted the world\'s first LGBTQ2S sport and recreation facility in Toronto\'s Moss Park neighborhood. While conceived as a site that would expand community services in an underserved community, this project was met with criticism from segments of the Moss Park community. Using qualitative interviews with both representatives from the LGBTQ2S organization and local residents, the purpose of this was to analyze justifications behind the project and concerns from the community. In so doing, the authors reflect upon the relationship between sport, recreation, and leisure-based place-making and questions of queer/de-queering politics by exploring the transformative or assimilationist aspects of queer recreation practices, the homonormativity of leisure spaces, and spiritual displacement associated with queer gentrification.