Impact of the Geographic Resolution on Population Synthesis Quality

Microsimulation-based models, increasingly used in the transportation domain, require richer datasets than traditional models. Precisely enumerated population data being usually unavailable, transportation researchers generate their statistical equivalent through population synthesis. While various synthesizers are proposed to optimize the accuracy of synthetic populations, no insight is given regarding the impact of the geographic resolution on population synthesis quality. In this paper, we synthesize populations for the Census Metropolitan Areas of Montreal, Toronto, and Vancouver at various geographic resolutions using the enhanced iterative proportional updating algorithm. We define accuracy (representativeness of the sociodemographic characteristics of the entire population) and precision (representativeness of the real population’s spatial heterogeneity) as metrics of synthetic populations’ quality and measure the impact of the reference resolution on them. Moreover, we assess census targets’ harmonization and double geographic resolution control as means of quality improvement. We find that with a less aggregate reference resolution, the gain in precision is higher than the loss in accuracy. The most disaggregate resolution is thus found to be the best choice. Harmonization proves to further optimize synthetic populations while double control harms their quality. Hence, synthesizing at the Dissemination Area resolution using harmonized census targets is found to yield optimal synthetic populations.

Routine and sentinel surveillance methods

Surveillance, whether active or passive, is a dynamic process. It is fundamental to public health decision-making and subsequent action. Choice of diseases for surveillance, development of methods, ongoing systematic evaluation and dissemination to those who need to know, are each components which require expert, knowledgeable attention. The communication age will greatly redefine approaches to surveillance, both for data acquisition and dissemination. Especially in the dissemination area, the public health community needs to strengthen its capacity

Detection of COVID-19 case clusters in Québec, May–October 2020

Objectives The Quebec Public Health Institute (INSPQ) was mandated to develop an automated tool for detecting space-time COVID-19 case clusters to assist regional public health authorities in identifying situations that require public health interventions. This article aims to describe the methodology used and to document the main outcomes achieved. Methods New COVID-19 cases are supplied by the “Trajectoire de santé publique” information system, geolocated to civic addresses and then aggregated by day and dissemination area. To target community-level clusters, cases identified as residents of congregate living settings are excluded from the cluster detection analysis. Detection is performed using the space-time scan statistic and Poisson statistical model, and implemented in the SaTScan software. Information on detected clusters is disseminated daily via an online interactive mapping interface. Results The number of clusters detected tracked with the number of new cases. Slightly more than 4900 statistically significant (p ≤ 0.01) space-time clusters were detected over 14 health regions from May to October 2020. The Montréal region was the most affected. Conclusion Considering the objective of timely cluster detection, the use of near-real-time health surveillance data of varying quality over time and by region constitutes an acceptable compromise between timeliness and data quality. This tool serves to supplement the epidemiologic investigations carried out by regional public health authorities for purposes of COVID-19 management and prevention.

Does Subway Station Proximity Spur Residential Development? Analyzing The Impact Of The Sheppard Subway Line On Housing Development In The City Of Toronto.

This study examines the pace and scale of residential development within a 1-kilometer radius of subway stations along the Sheppard Subway line within the City of Toronto during the years 1991-2016. The dataset used for this study was obtained from Statistics Canada that contained data on the number of housing units per dissemination area within a 1-kilometer radius of a subway station in addition to several variables used for analysis. The difference- in-differences method was used, findings indicated insignificant results meaning the Sheppard Subway Line did not spur residential development at a rate faster than the one observed for the Sheppard West corridor. This was further proved by examining the pace of development during the pre-treated and post-treated period amongst both the treated and control groups, findings indicated that both groups received similar amounts of residential growth, such that the difference in residential construction between the two corridors was statistically insignificant.

Does Subway Station Proximity Spur Residential Development? Analyzing The Impact Of The Sheppard Subway Line On Housing Development In The City Of Toronto.

This study examines the pace and scale of residential development within a 1-kilometer radius of subway stations along the Sheppard Subway line within the City of Toronto during the years 1991-2016. The dataset used for this study was obtained from Statistics Canada that contained data on the number of housing units per dissemination area within a 1-kilometer radius of a subway station in addition to several variables used for analysis. The difference- in-differences method was used, findings indicated insignificant results meaning the Sheppard Subway Line did not spur residential development at a rate faster than the one observed for the Sheppard West corridor. This was further proved by examining the pace of development during the pre-treated and post-treated period amongst both the treated and control groups, findings indicated that both groups received similar amounts of residential growth, such that the difference in residential construction between the two corridors was statistically insignificant.

Spatial Relationships Between Socio-Economic Status And Sources of Hazardous Air Pollution in the City of Toronto, Canada

This research paper identifies and characterizes areas in the City of Toronto that may be impacted by facilities that emit air pollutants. The impacted areas were isolated using a combination of K-Means cluster analysis and kernel density estimation to determine whether disparity in socio-economic status can be correlated with the location of these facilities. Dissemination Area (DA) level data from the 2006 Canadian Census were evaluated against pollution data provided by Environment Canada’s 2006 National Pollutant Release Inventory (NPRI) database. A total of 67 socio-economic variables from the 2006 Statistics Canada census were analysed. The City of Toronto’s 3,577 DAs were assigned to one of two cluster groups: Underprivileged Areas, or Areas of Affluence. The DAs represented by the two cluster groups were then analyzed alongside the NPRI pollution data, which had been developed into generalized concentration ranges using a 5km search radius. Although the Areas of Affluence cluster contains 15% more facilities (141) than the Underprivileged Areas (104), the latter are generally impacted by higher concentrations of a more diverse range of pollution. For example, a larger percent of Toronto residents living in Underprivileged Areas are exposed to the highest concentrations of total emissions, heavy metals, miscellaneous compounds, and non-carcinogenic emissions when compared to the population of DAs designated as Areas of Affluence. Conversely, a larger percent of residents living in Areas of Affluence are generally exposed to the highest concentrations of volatile organic compounds and carcinogenic emissions. The findings suggest an environmental justice concern, with respect to industrial air pollution within the City of Toronto.

Spatial Relationships Between Socio-Economic Status And Sources of Hazardous Air Pollution in the City of Toronto, Canada

This research paper identifies and characterizes areas in the City of Toronto that may be impacted by facilities that emit air pollutants. The impacted areas were isolated using a combination of K-Means cluster analysis and kernel density estimation to determine whether disparity in socio-economic status can be correlated with the location of these facilities. Dissemination Area (DA) level data from the 2006 Canadian Census were evaluated against pollution data provided by Environment Canada’s 2006 National Pollutant Release Inventory (NPRI) database. A total of 67 socio-economic variables from the 2006 Statistics Canada census were analysed. The City of Toronto’s 3,577 DAs were assigned to one of two cluster groups: Underprivileged Areas, or Areas of Affluence. The DAs represented by the two cluster groups were then analyzed alongside the NPRI pollution data, which had been developed into generalized concentration ranges using a 5km search radius. Although the Areas of Affluence cluster contains 15% more facilities (141) than the Underprivileged Areas (104), the latter are generally impacted by higher concentrations of a more diverse range of pollution. For example, a larger percent of Toronto residents living in Underprivileged Areas are exposed to the highest concentrations of total emissions, heavy metals, miscellaneous compounds, and non-carcinogenic emissions when compared to the population of DAs designated as Areas of Affluence. Conversely, a larger percent of residents living in Areas of Affluence are generally exposed to the highest concentrations of volatile organic compounds and carcinogenic emissions. The findings suggest an environmental justice concern, with respect to industrial air pollution within the City of Toronto.

Domestic violence and abuse related emergency room visits in Ontario, Canada

Background Hospitals’ emergency rooms (ERs) are generally the first point of contact of domestic violence and abuse (DVA) victims to the health care system. For efficient management and resource allocation for ERs to manage DVA-related emergencies in Canada, it is important to quantify and assess the pattern of these visits. Methods Aggregate DVA-related ER visits data, using relevant ICD-10-CA codes, from 2012 to 2016 were retrieved from IntelliHealth Ontario. The 2011 ON-Marg (Ontario Marginalization) indices were linked at the Dissemination Area level to ER data. Descriptive analyses including total number and rate of visits per 100,000 people were calculated, stratified by age and sex. The Slope Index of Inequality (SII) and Relative Index of Inequality (RII) were also assessed. Results From 2012 to 2016, 10,935 (81.2% by females and 18.8% by males) DVA-related visits were made to ERs in Ontario. An annual average of 25.5 visits per 100,000 females and 6.1 visits per 100,000 males was observed. Residential instability and deprivation were significant predictors of DVA-related ER visits. No particular site of injury was indicated in 38.5% of visits, 24.7% presented with cranio-maxillofacial (CMF) trauma in isolation, 28.9% presented with non-CMF injuries, and 7.9% visits presented with both CMF and non-CMF injuries. Conclusion This study identified that the burden of DVA-related ER visits is large enough to warrant timely public health interventions, and observed that certain populations in Ontario experience more DVA and/or are more prone to its impact. Our findings have important implications for various stakeholders involved in planning and implementing relevant policies and programs.

Domestic Violence and Abuse Related Emergency Room Visits in Ontario, Canada

Background: Hospitals’ emergency rooms (ERs), are generally the first point of contact of domestic violence and abuse (DVA) victims to the health care system. For efficient management and resource allocation for ERs to manage DVA-related emergencies in Canada, it is important to quantify and assess the pattern of these visits.Methods: Aggregate DVA-related ER visits data, using relevant ICD-10-CA codes, from 2012 to 2016 were retrieved from IntelliHealth Ontario. The 2011 ON-Marg (Ontario Marginalization) indices were linked at the Dissemination Area level to ER data. Descriptive analyses including total number and rate of visits per 100,000 people were calculated, stratified by age and sex. The Slope Index of Inequality (SII) and Relative Index of Inequality (RII) were also assessed. Results: From 2012-2016, 10,935 (81.2% by females and 18.8% by males) DVA-related visits were made to ERs in Ontario. An annual average of 25.5 visits per 100,000 females and 6.1 visits per 100,000 males was observed. Residential instability and deprivation were significant predictors of DVA-related ER visits. No particular site of injury was indicated in 38.5% of visits, 24.7% presented with cranio-maxillofacial (CMF) trauma in isolation, 28.9% presented with non-CMF injuries, and 7.9% visits presented with both CMF and non-CMF injuries.Conclusion: This study identified that the burden of DVA-related ER visits is large enough to warrant timely public health interventions, and observed that certain populations in Ontario experience more DVA and/or are more prone to its impact. Our findings have important implications for various stakeholders involved in planning and implementing relevant policies and programs.

Spatial distribution of gambling: two indexes in support of the reduction of health inequalities

Background Many studies have showed that disadvantaged areas residents have greater access to gambling sites and are more affected by gambling. Our research proposes an innovative method to characterize gambling environments in Quebec and addresses social inequality with respect to gambling exposure. Methods This cross-sectional ecological study was carried out in 3 stages: a Gambling Exposure Index (GEI) was built and is composed of 3 dimensions: spatial accessibility to gambling sites, density of gambling places, and relative risk associated with the types of game. The two-step floating catchment area (2SFCA) method was used to combine these dimensions into an overall GEI index. Data was retrieved from a geocoded directory of gambling sites and commercial databases. The relative risk of games is expressed by prevalence rates for those specific games in a Quebec population prevalence survey. A Vulnerability to Gambling Index (VGI) was produced based on 6 socio-economic proxies of problem gambling from the 2016 Canadian census, which were weighted and aggregated at the dissemination area (DA) level. Spatial and descriptive statistical analyses were conducted to explore the relationship between VGI and GEI, and to identify highly exposed and vulnerable areas. Results Our analyzes reveal significant associations between the GEI and the VGI in 2 599 out of 13 420 Quebec DAs (p < 0.05). Sectors with a high GEI show an average distance to the closest gambling sites of 2.8 km compared with 13.5 km for more advantaged sectors. Conclusions The interactive online mapping of the two indexes and statistical analysis of the results are beneficial to the professionals working in several fields such as risk monitoring, management of zoning, licensing and gambling distribution, prevention and treatment services. The method and the associated tools can be adapted to address the problem of increased accessibility to other unhealthy products in vulnerable neighborhoods. Key messages Two innovative ecological indexes show that increased accessibility to gambling correlates with a higher vulnerability to gambling in many Quebec regions. The online interactive map on gambling exposure and vulnerability provides reliable criteria to municipal, regional and governmental bodies for a safer distribution of gambling offer.