Background: As of 13 July 2020, 12.9 million COVID-19 cases have been reported worldwide. Prior studies have demonstrated that local socioeconomic and built environment characteristics may significantly contribute to viral transmission and incidence rates, thereby accounting for some of the spatial variation observed. Due to uncertainties, non-linearities, and multiple interaction effects observed in the associations between COVID-19 incidence and socioeconomic, infrastructural, and built environment characteristics, we present a structured multimethod approach for analysing cross-sectional incidence data within in an Exploratory Spatial Data Analysis (ESDA) framework at the NUTS3 (county) scale. Methods: By sequentially conducting a geospatial analysis, an heuristic geographical interpretation, a Bayesian machine learning analysis, and parameterising a Generalised Additive Model (GAM), we assessed associations between incidence rates and 368 independent variables describing geographical patterns, socioeconomic risk factors, infrastructure, and features of the build environment. A spatial trend analysis and Local Indicators of Spatial Autocorrelation were used to characterise the geography of age-adjusted COVID-19 incidence rates across Germany, followed by iterative modelling using Bayesian Additive Regression Trees (BART) to identify and measure candidate explanatory variables. Partial dependence plots were derived to quantify and contextualise BART model results, followed by the parameterisation of a GAM to assess correlations. Results: A strong south-to-north gradient of COVID-19 incidence was identified, facilitating an empirical classification of the study area into two epidemic subregions. All preliminary and final models indicated that location, densities of the built environment, and socioeconomic variables were important predictors of incidence rates in Germany. The top ten predictor variables' partial dependence exhibited multiple non-linearities in the relationships between key predictor variables and COVID-19 incidence rates. The BART, partial dependence, and GAM results indicate that the strongest predictors of COVID-19 incidence at the county scale were related to community interconnectedness, geographical location, transportation infrastructure, and labour market structure.

BackgroundInjury is a truly global health issue that has enormous societal and economic consequences in all countries. Interpersonal violence is now widely recognized as important global public health issues that can be addressed through evidence-based interventions. In South Africa, as in many low- and middle-income countries (LMIC), a lack of ongoing, systematic injury surveillance has limited the ability to characterize the burden of violence-related injury and to develop prevention programmes.ObjectiveTo describe the profile of trauma presenting to the trauma centre of Groote Schuur Hospital in Cape Town, South Africa – relating to interpersonal violence, using data collected from a newly implemented surveillance system. Particular emphasis was placed on temporal aspects of injury epidemiology, as well as age and sex differentiation.DesignData were collected prospectively using a standardized trauma admissions form for all patients presenting to the trauma centre. An epidemiological analysis was conducted on 16 months of data collected from June 2010 to October 2011.ResultsA total of 8445 patients were included in the analysis, in which the majority were violence-related. Specifically, 35% of records included violent trauma and, of those, 75% of victims were male. There was a clear temporal pattern: a greater proportion of intentional injuries occur during the night, while unintentional injury peaks late in the afternoon. In total, two-third of all intentional trauma is inflicted on the weekends, as is 60% of unintentional trauma. Where alcohol was recorded in the record, 72% of cases involved intentional injury. Sex was again a key factor as over 80% of all records involving alcohol or substance abuse were associated with males. The findings highlighted the association between violence, young males, substance use, and weekends.ConclusionsThis study provides the basis for evidence-based interventions to reduce the burden of intentional injury. Furthermore, it demonstrates the value of locally appropriate, ongoing, systematic public health surveillance in LMIC.

BackgroundMany factors contribute to socioeconomic status (SES), yet in most survival studies only income is used as a measure for determining SES. We used a complex, composite, census-based metric for socioeconomic deprivation to better distinguish individuals with lower SES and assess its impact on survival and staging trends of oral cancers.MethodsOropharyngeal (OPC) and oral cavity cancer (OCC) cases were identified from the British Columbia cancer registry between 1981–2009 and placed into affluent and deprived neighborhoods using postal codes linked to VANDIX (a composite SES index based on 7 census variables encompassing income, housing, family structure, education, and employment). Stage and cancer-specific survival rates were examined by sex, SES, and time period.ResultsApproximately 50 % of OPC and OCC cases of both sexes resided in SES deprived neighborhoods. Numbers of cases have increased in recent years for all but OCC in men. The deprivation gap in survival between affluent and deprived neighborhoods widened in recent years for OPC and OCC in men, while decreasing for OPC and increasing slightly for OCC in women. Greater proportions of OCC cases were diagnosed at later stage disease for both sexes residing in deprived neighborhoods, a trend not seen for OPC.ConclusionSES remains a significant independent determinant of survival for both OPC and OCC when using a composite metric for SES. OPC survival rates among men have improved, albeit at slower rates in deprived communities. OCC screening programs need to be targeted towards SES-deprived neighborhoods where greater proportions of cases were diagnosed at a later stage and survival rates have significantly worsened in both sexes.

Rapid urban expansion is a significant contributor to land cover change and poses a challenge to environmental sustainability, particularly in less developed countries. Insufficient data about urban expansion hinders effective land use planning. Therefore, a high need to collect, process, and disseminate land cover data exists. This study focuses on urban land cover change detection using Geographic Information Systems and remote sensing methods to produce baseline information in support for land use planning. We applied a supervised classification of land cover of LANDSAT data from 1987, 2002, and 2017. We mapped land cover transitions from 1987 to 2017 and computed the net land cover change during this time. Finally, we analyzed the mismatches between the past and current urban land cover and land use plans and quantified the non-urban development area lost to urban/built-up. Our results indicated an increase in urban/built-up and bare land cover types, while vegetation land cover decreased. We observed mismatches between past/current land cover and the existing land use plan. By providing detailed insights into mismatches between the regional land use plan and unregulated urban expansion, this study provides important information for a critical debate on the role and effectiveness of land use planning for environmental sustainability and sustainable urban development, particularly in less developed countries.

BackgroundOral cancer is an important health issue, with changing incidence in many countries. Oropharyngeal cancer (OPC, in tonsil and oropharygeal areas) is increasing, while oral cavity cancer (OCC, other sites in the mouth) is decreasing. There is the need to identify high risk groups and communities for further study and intervention. The objective of this study was to determine how the incidence of OPC and OCC varied by neighbourhood socioeconomic status (SES) in British Columbia (BC), including the magnitude of any inequalities and temporal trends.MethodsICDO-3 codes were used to identify OPC and OCC cases in the BC Cancer Registry from 1981–2010. Cases were categorized by postal codes into SES quintiles (q1-q5) using VANDIX, which is a census-based, multivariate weighted index based on neighbourhood average household income, housing tenure, educational attainment, employment and family structure. Age-standardized incidence rates were determined for OPC and OCC by sex and SES quintiles and temporal trends were then examined.ResultsIncidence rates are increasing in both men and women for OPC, and decreasing in men and increasing in women for OCC. This change is not linear or proportionate between different SES quintiles, for there is a sharp and dramatic increase in incidence according to the deprivation status of the neighbourhood. The highest incidence rates in men for both OPC and OCC were observed in the most deprived SES quintile (q5), at 1.7 times and 2.2 times higher, respectively, than men in the least deprived quintile (q1). For OPC, the age-adjusted incidence rates significantly increased in all SES quintiles with the highest increase observed in the most deprived quintile (q5). Likewise, the highest incidence rates for both OPC and OCC in women were observed in the most deprived SES quintile (q5), at 2.1 times and 1.8 times higher, respectively, than women in the least deprived quintile (q1).ConclusionWe report on SES disparities in oral cancer, emphasizing the need for community-based interventions that address access to medical care and the distribution of educational and health promotion resources among the most SES deprived communities in British Columbia.

BackgroundIn 2002, the WHO declared interpersonal violence to be a leading public health problem. Previous research demonstrates that urban spaces with a high incidence of violent trauma (hotspots) correlate with features of built environment and social determinants. However, there are few studies that analyse injury data across the axes of both space and time to characterise injury–environment relationships. This paper describes a spatiotemporal analysis of violent injuries in Vancouver, Canada, from 2001 to 2008.MethodsUsing geographic information systems, 575 violent trauma incidents were mapped and analysed using kernel density estimation to identify hotspot locations. Patterns between space, time, victim age and sex and mechanism of injury were investigated with an exploratory approach.ResultsSeveral patterns in space and time were identified and described, corresponding to distinct neighbourhood characteristics. Violent trauma hotspots were most prevalent in Vancouver's nightclub district on Friday and Saturday nights, with higher rates in the most socioeconomically deprived neighbourhoods. Victim sex, age and mechanism of injury also formed strong patterns. Three neighbourhood profiles are presented using the dual axis of space/time to describe the hotspot environments.ConclusionsThis work posits the value of exploratory spatial data analysis using geographic information systems in trauma epidemiology studies and further suggests that using both space and time concurrently to understand urban environmental correlates of injury provides a more granular or higher resolution picture of risk. We discuss implications for injury prevention and control, focusing on education, regulation, the built environment and injury surveillance.

Background:Climate change has increased the frequency and intensity of extremely hot weather. The health risks associated with extemely hot weather are not uniform across affected areas owing to variability in heat exposure and social vulnerability, but these differences are challenging to map with precision.Objectives:We developed a spatially and temporally stratified case-crossover approach for delineation of areas with higher and lower risks of mortality on extremely hot days and applied this approach in greater Vancouver, Canada.Methods:Records of all deaths with an extremely hot day as a case day or a control day were extracted from an administrative vital statistics database spanning the years of 1998–2014. Three heat exposure and 11 social vulnerability variables were assigned at the residential location of each decedent. Conditional logistic regression was used to estimate the odds ratio for a 1°C increase in daily mean temperature at a fixed site with an interaction term for decedents living above and below different values of the spatial variables.Results:The heat exposure and social vulnerability variables with the strongest spatially stratified results were the apparent temperature and the labor nonparticipation rate, respectively. Areas at higher risk had values ≥ 34.4°C for the maximum apparent temperature and ≥ 60% of the population neither employed nor looking for work. These variables were combined in a composite index to quantify their interaction and to enhance visualization of high-risk areas.Conclusions:Our methods provide a data-driven framework for spatial delineation of the temperature-–mortality relationship by heat exposure and social vulnerability. The results can be used to map and target the most vulnerable areas for public health intervention.Citation:Ho HC, Knudby A, Walker BB, Henderson SB. 2017. Delineation of spatial variability in the temperature–mortality relationship on extremely hot days in greater Vancouver, Canada. Environ Health Perspect 125:66–75; http://dx.doi.org/10.1289/EHP224

Introduction: Both socioeconomic status and travel time to cancer treatment have been associated with treatment choice and patient outcomes. An improved understanding of the relationship between these two dimensions of access may enable cancer control experts to better target patients with poor access, particularly in isolated suburban and rural communities. Methods: Using geographical information systems, head and neck cancer patients across British Columbia, Canada from 1981 to 2009, were mapped and their travel times to the nearest treatment center at their time of diagnosis were modelled. Patients' travel times were analysed by urban, suburban, and rural neighborhood types and an index of multiple socioeconomic deprivation was used to assess the role of socioeconomic status in patients' spatial access. Results: Significant associations between socioeconomic deprivation and spatial access to treatment were identified, with the most deprived quintiles of patients experiencing nearly twice the travel time as the least deprived quintile. The sharpest disparities were observed among the most deprived patient populations in suburban and rural areas. However, the establishment of new treatment centers has decreased overall travel times by 28% in recent decades. Conclusions: Residence in a neighborhood with high socioeconomic deprivation is strongly associated with head and neck cancer patients' spatial access to cancer treatment centers. Patients residing in the most socioeconomically deprived neighborhoods consistently have longer travel times in urban, suburban, and rural communities in the study area.Key words: cancer treatment, socioeconomic status, deprivation, head and neck cancers, spatial access, geographic information systems, Canada.© BB Walker, N Schuurman, A Auluck, SA Lear, M Rosin 2017. A Licence to publish this material has been given to James Cook University, http://www.jcu.edu.au 2 IntroductionWith an estimated 525 000 new cases in 2012, head and neck cancers are the eighth most common non-melanoma cancers globally 1. This number is expected to grow significantly in the coming decades, resulting in increased demand for treatment 2 .To maximize efficiency, comprehensive cancer treatment facilities are most commonly located in areas where they service the largest proportion of the patient population, generally in large urban centers. This results in a geographical inequity, such that individuals living farther from a cancer treatment center experience a greater travel burden in order to attend their treatment, particularly those living in rural and remote areas , and survival 14. The time required for patients to travel from the home to a cancer treatment center is therefore an important factor throughout the continuum of care, and may inform more efficient and equitable cancer control programs and policy.The travel time required for an individual to reach a treatment center provides a quantitative measure of access 15 . However, an individual's access to a health service may also be measured as the ...