Ofer Amram

Proximity of public elementary schools to major roads in Canadian urban areas

BackgroundEpidemiologic studies have linked exposure to traffic-generated air and noise pollution with a wide range of adverse health effects in children. Children spend a large portion of time at school, and both air pollution and noise are elevated in close proximity to roads, so school location may be an important determinant of exposure. No studies have yet examined the proximity of schools to major roads in Canadian cities.MethodsData on public elementary schools in Canadas 10 most populous cities were obtained from online databases. School addresses were geocoded and proximity to the nearest major road, defined using a standardized national road classification scheme, was calculated for each school. Based on measurements of nitrogen oxide concentrations, ultrafine particle counts, and noise levels in three Canadian cities we conservatively defined distances < 75 m from major roads as the zone of primary interest. Census data at the city and neighborhood levels were used to evaluate relationships between school proximity to major roads, urban density, and indicators of socioeconomic status.ResultsAddresses were obtained for 1,556 public elementary schools, 95% of which were successfully geocoded. Across all 10 cities, 16.3% of schools were located within 75 m of a major road, with wide variability between cities. Schools in neighborhoods with higher median income were less likely to be near major roads (OR per

A protocol for determining differences in consistency and depth of palliative care service provision across community sites.

20,000 increase: 0.81; 95% CI: 0.65, 1.00), while schools in densely populated neighborhoods were more frequently close to major roads (OR per 1,000 dwellings/km2: 1.07; 95% CI: 1.00, 1.16). Over 22% of schools in the lowest neighborhood income quintile were close to major roads, compared to 13% of schools in the highest income quintile.ConclusionsA substantial fraction of students at public elementary schools in Canada, particularly students attending schools in low income neighborhoods, may be exposed to elevated levels of air pollution and noise while at school. As a result, the locations of schools may negatively impact the healthy development and academic performance of a large number of Canadian children.

A web-based model to support patient-to-hospital allocation in mass casualty incidents

Numerous accounts document the difficulty in obtaining accurate data regarding the extent and composition of palliative care services. Compounding the problem is the lack of standardisation regarding categorisation and reporting across jurisdictions. In this study, we gathered both quantitative and spatial--or geographical--data to develop a composite picture that captures the extent, composition and depth of palliative care in the Canadian province of British Columbia (BC). The province is intensely urban in the southwest and is rural or remote in most of the remainder. For this study, we conducted a detailed telephone survey of all palliative care home care teams and facilities hosting designated beds in BC. We used geographic information systems to geocode locations of all hospice and hospital facilities. In-home care data was obtained individually from each of five BC regional health authorities. In addition, we purchased accurate road travel time data to determine service areas around palliative facilities and to determine populations outside of a 1-hour travel time to a facility. With this data, we were able to calculate three critical metrics: (i) the population served within 1 hour of palliative care facilities--and more critically those not served; (ii) a matrix that determines access to in-home palliative care measured by both diversity of professionals as well as population served per palliative team member; and (iii) a ranking of palliative care services across the province based on physical accessibility as well as the extent of in-home care. In combination, these metrics provide the basis for identifying areas of vulnerability with respect to not meeting potential palliative care need. In addition, the ranking provides a basis for rural/urban comparisons. Finally, the protocol introduced can be used in other areas and provides a means of comparing palliative care service provision amongst multiple jurisdictions.

Mass casualty modelling: a spatial tool to support triage decision making

BACKGROUND: In a mass casualty situation, evacuation of severely injured patients to the appropriate health care facility is of critical importance. The prehospital stage of a mass casualty incident (MCI) is typically chaotic, characterized by dynamic changes and severe time constraints. As a result, those involved in the prehospital evacuation process must be able to make crucial decisions in real time. This article presents a model intended to assist in the management of MCIs. The Mass Casualty Patient Allocation Model has been designed to facilitate effective evacuation by providing key information about nearby hospitals, including driving times and real-time bed capacity. These data will enable paramedics to make informed decisions in support of timely and appropriate patient allocation during MCIs. The model also enables simulation exercises for disaster preparedness and first response training. METHODS: Road network and hospital location data were used to precalculate road travel times from all locations in Metro Vancouver to all Level I to III trauma hospitals. Hospital capacity data were obtained from hospitals and were updated by tracking patient evacuation from the MCI locations. In combination, these data were used to construct a sophisticated web-based simulation model for use by emergency response personnel. RESULTS: The model provides information critical to the decision-making process within a matter of seconds. This includes driving times to the nearest hospitals, the trauma service level of each hospital, the location of hospitals in relation to the incident, and up-to-date hospital capacity. CONCLUSION: The dynamic and evolving nature of MCIs requires that decisions regarding prehospital management be made under extreme time pressure. This model provides tools for these decisions to be made in an informed fashion with continuously updated hospital capacity information. In addition, it permits complex MCI simulation for response and preparedness training.

Spatial Access to Emergency Services in Low- and Middle-Income Countries: A GIS-Based Analysis

BackgroundDuring a mass casualty incident, evacuation of patients to the appropriate health care facility is critical to survival. Despite this, no existing system provides the evidence required to make informed evacuation decisions from the scene of the incident. To mitigate this absence and enable more informed decision making, a web based spatial decision support system (SDSS) was developed. This system supports decision making by providing data regarding hospital proximity, capacity, and treatment specializations to decision makers at the scene of the incident.MethodsThis web-based SDSS utilizes pre-calculated driving times to estimate the actual driving time to each hospital within the inclusive trauma system of the large metropolitan region within which it is situated. In calculating and displaying its results, the model incorporates both road network and hospital data (e.g. capacity, treatment specialties, etc.), and produces results in a matter of seconds, as is required in a MCI situation. In addition, its application interface allows the user to map the incident location and assists in the execution of triage decisions.ResultsUpon running the model, driving time from the MCI location to the surrounding hospitals is quickly displayed alongside information regarding hospital capacity and capability, thereby assisting the user in the decision-making process.ConclusionsThe use of SDSS in the prioritization of MCI evacuation decision making is potentially valuable in cases of mass casualty. The key to this model is the utilization of pre-calculated driving times from each hospital in the region to each point on the road network. The incorporation of real-time traffic and hospital capacity data would further improve this model.

A geospatial analysis of the relationship between neighbourhood socioeconomic status and adult severe injury in Greater Vancouver

Injury is a leading cause of the global disease burden, accounting for 10 percent of all deaths worldwide. Despite 90 percent of these deaths occurring in low and middle-income countries (LMICs), the majority of trauma research and infrastructure development has taken place in high-income settings. Furthermore, although accessible services are of central importance to a mature trauma system, there remains a paucity of literature describing the spatial accessibility of emergency services in LMICs. Using data from the Service Provision Assessment component of the Demographic and Health Surveys of Namibia and Haiti we defined the capabilities of healthcare facilities in each country in terms of their preparedness to provide emergency services. A Geographic Information System-based network analysis method was used to define 5- 10- and 50-kilometer catchment areas for all facilities capable of providing 24-hour care, higher-level resuscitative services or tertiary care. The proportion of a country’s population with access to each level of service was obtained by amalgamating the catchment areas with a population layer. A significant proportion of the population of both countries had poor spatial access to lower level services with 25% of the population of Haiti and 51% of the population of Namibia living further than 50 kilometers from a facility capable of providing 24-hour care. Spatial access to tertiary care was considerably lower with 51% of Haitians and 72% of Namibians having no access to these higher-level services within 50 kilometers. These results demonstrate a significant disparity in potential spatial access to emergency services in two LMICs compared to analogous estimates from high-income settings, and suggest that strengthening the capabilities of existing facilities may improve the equity of emergency services in these countries. Routine collection of georeferenced patient and facility data in LMICs will be important to understanding how spatial access to services influences outcomes.

Assessing access to paediatric trauma centres in Canada, and the impact of the golden hour on length of stay at the hospital: an observational study

Background Every year, injuries cost the Canadian healthcare system billions of dollars and result in thousands of emergency room visits, hospitalisations and deaths. The purpose of this study was to explore the relationship between neighbourhood socioeconomic status (NSES) and the rates of all-cause, unintentional and intentional severe injury in Greater Vancouver adults. A second objective was to determine whether the identified associations were spatially consistent or non-stationary. Methods Severe injury cases occurring between 2001 and 2006 were identified using the British Columbias Coroners Service records and the British Columbia Trauma Registry, and mapped by census dissemination areas using a geographical information system. Descriptive statistics and exploratory spatial data analysis methods were used to gain a better understanding of the data sets and to explore the relationship between the rates of severe injury and two measures of NSES (social and material deprivation). Ordinary least squares and geographically weighted regression were used to model these relationships at the global and local levels. Results Inverse relationships were identified between both measures of NSES and the rates of severe injury with the strongest associations located in Greater Vancouvers most socioeconomically deprived neighbourhoods. Social deprivation was found to have a slightly stronger relationship with the rates of severe injury than material deprivation. Conclusions Results of this study suggest that policies and programmes aimed at reducing the burden of severe injury in Greater Vancouver should take into account social and material deprivation, and should target the most socioeconomically deprived neighbourhoods in Greater Vancouver.

Community mapping of sex work criminalization and violence: impacts on HIV treatment interruptions among marginalized women living with HIV in Vancouver, Canada

Objectives In Canada injuries are a leading cause of death and morbidity among the paediatric population. Trauma systems have been established across North America to provide comprehensive injury care and to lead injury control efforts. However, not all populations have equal access to trauma care services. This is an observational study with the aim of assessing the impact of geographical access to paediatric trauma centres (PTCs) on patient outcomes, and to determine spatial access to PTCs across Canada. Setting To examine the relationship between access to PTC and injury outcome, length of stay at the PTC was determined for all injured patients who live within and outside of 60 min driving time of the PTC. To determine spatial access to PTCs across Canada, a list of level 1 and 2 PTCs was identified across Canada. A 1 h driving time catchment was created around each PTC in order to estimate spatial accessibility. Participants Hospital administration data sets from British Columbia (BC) and the Nova Scotia (NS) trauma registry were used to assess the impact of spatial access on paediatric injury (ages 0–15 years) outcomes. The data sets provided case-level data including the Injury Severity Score, postal code of place of residence, age and length of hospital stay. Results In NS and BC, average length of stay at the hospital is significantly lower inside 60 min driving time compared to outside of 60 min driving time from a PTC (p<0.05, using a non-parametric t test). In Canada, approximately 65% of the paediatric population resides within 1 h of a PTC. Conclusions This paper highlights differences in injury outcomes as a result of access. However, further investigation is needed as other considerations such as type of injury, age and/or gender may also affect injury outcomes.

The Association between Regional Environmental Factors and Road Trauma Rates: A Geospatial Analysis of 10 Years of Road Traffic Crashes in British Columbia, Canada

Despite the high HIV burden faced by sex workers, data on access and retention in antiretroviral therapy (ART) are limited. Using an innovative spatial epidemiological approach, we explored how the social geography of sex work criminalization and violence impacts HIV treatment interruptions among sex workers living with HIV in Vancouver over a 3.5-year period. Drawing upon data from a community-based cohort (AESHA, 2010–2013) and linked external administrative data on ART dispensation, GIS mapping and multivariable logistic regression with generalized estimating equations to prospectively examine the effects of spatial criminalization and violence near women’s places of residence on 2-day ART interruptions. Analyses were restricted to 66 ART-exposed women who contributed 208 observations and 83 ART interruption events. In adjusted multivariable models, heightened density of displacement due to policing independently correlated with HIV treatment interruptions (AOR: 1.02, 95%CI: 1.00–1.04); density of legal restrictions (AOR: 1.30, 95%CI: 0.97–1.76) and a combined measure of criminalization/violence (AOR: 1.00, 95%CI: 1.00–1.01) were marginally correlated. The social geography of sex work criminalization may undermine access to essential medicines, including HIV treatment. Interventions to promote ‘enabling environments’ (e.g. peer-led models, safer living/working spaces) should be explored, alongside policy reforms to ensure uninterrupted treatment access.

Socio economic status and traumatic brain injury amongst pediatric populations: a spatial analysis in Greater Vancouver

Background British Columbia, Canada is a geographically large jurisdiction with varied environmental and socio-cultural contexts. This cross-sectional study examined variation in motor vehicle crash rates across 100 police patrols to investigate the association of crashes with key explanatory factors. Methods Eleven crash outcomes (total crashes, injury crashes, fatal crashes, speed related fatal crashes, total fatalities, single-vehicle night-time crashes, rear-end collisions, and collisions involving heavy vehicles, pedestrians, cyclists, or motorcyclists) were identified from police collision reports and insurance claims and mapped to police patrols. Six potential explanatory factors (intensity of traffic law enforcement, speed limits, climate, remoteness, socio-economic factors, and alcohol consumption) were also mapped to police patrols. We then studied the association between crashes and explanatory factors using negative binomial models with crash count per patrol as the response variable and explanatory factors as covariates. Results Between 2003 and 2012 there were 1,434,239 insurance claim collisions, 386,326 police reported crashes, and 3,404 fatal crashes. Across police patrols, there was marked variation in per capita crash rate and in potential explanatory factors. Several factors were associated with crash rates. Percent roads with speed limits ≤ 60 km/hr was positively associated with total crashes, injury crashes, rear end collisions, and collisions involving pedestrians, cyclists, and heavy vehicles; and negatively associated with single vehicle night-time crashes, fatal crashes, fatal speeding crashes, and total fatalities. Higher winter temperature was associated with lower rates of overall collisions, single vehicle night-time collisions, collisions involving heavy vehicles, and total fatalities. Lower socio-economic status was associated with higher rates of injury collisions, pedestrian collisions, fatal speeding collisions, and fatal collisions. Regions with dedicated traffic officers had fewer fatal crashes and fewer fatal speed related crashes but more rear end crashes and more crashes involving cyclists or pedestrians. The number of traffic citations per 1000 drivers was positively associated with total crashes, fatal crashes, total fatalities, fatal speeding crashes, injury crashes, single vehicle night-time crashes, and heavy vehicle crashes. Possible explanations for these associations are discussed. Conclusions There is wide variation in per capita rates of motor vehicle crashes across BC police patrols. Some variation is explained by factors such as climate, road type, remoteness, socioeconomic variables, and enforcement intensity. The ability of explanatory factors to predict crash rates would be improved if considered with local traffic volume by all travel modes.