BackgroundElectronic medical records (EMRs) used in primary care contain a breadth of data that can be used in public health research. Patient data from EMRs could be linked with other data sources, such as a postal code linkage with Census data, to obtain additional information on environmental determinants of health. While promising, successful linkages between primary care EMRs with geographic measures is limited due to ethics review board concerns. This study tested the feasibility of extracting full postal code from primary care EMRs and linking this with area-level measures of the environment to demonstrate how such a linkage could be used to examine the determinants of disease. The association between obesity and area-level deprivation was used as an example to illustrate inequalities of obesity in adults.MethodsThe analysis included EMRs of 7153 patients aged 20 years and older who visited a single, primary care site in 2011. Extracted patient information included demographics (date of birth, sex, postal code) and weight status (height, weight). Information extraction and management procedures were designed to mitigate the risk of individual re-identification when extracting full postal code from source EMRs. Based on patients’ postal codes, area-based deprivation indexes were created using the smallest area unit used in Canadian censuses. Descriptive statistics and socioeconomic disparity summary measures of linked census and adult patients were calculated.ResultsThe data extraction of full postal code met technological requirements for rendering health information extracted from local EMRs into anonymized data. The prevalence of obesity was 31.6 %. There was variation of obesity between deprivation quintiles; adults in the most deprived areas were 35 % more likely to be obese compared with adults in the least deprived areas (Chi-Square = 20.24(1), p < 0.0001). Maps depicting spatial representation of regional deprivation and obesity were created to highlight high risk areas.ConclusionsAn area based socio-economic measure was linked with EMR-derived objective measures of height and weight to show a positive association between area-level deprivation and obesity. The linked dataset demonstrates a promising model for assessing health disparities and ecological factors associated with the development of chronic diseases with far reaching implications for informing public health and primary health care interventions and services.

Private water supplies, which are the primary source of drinking water for rural communities in developed countries, are at risk of becoming fecally contaminated. It is important to identify the source of contamination in order to better understand and address this human health risk. Microbial source tracking methods using human, bovine and general Bacteroidales markers were performed on 716 well water samples from southeastern Ontario, which had previously tested positive for Escherichia coli. The results were then geospatially analyzed in order to elucidate contamination patterns. Markers for human feces were found in nearly half (49%) of all samples tested, and a statistically significant spatial cluster was observed. A quarter of the samples tested positive for only general Bacteroidales markers (25.7%) and relatively few bovine specific marker positives (12.6%) were found. These findings are fundamental to the understanding of pathogen dynamics and risk in the context of drinking well water and will inform future research regarding host-specific pathogens in private well water samples.

Objective: Emergency department (ED) overcrowding in Canada is an ongoing problem resulting in prolonged wait times, service declines, increased patient suffering, and adverse patient outcomes. We explored the relationship between socioeconomic status (SES) and ED use in Canada's universal health care system to improve our understanding of the nature of ED users to both improve health care to the most deprived populations and reduce ED patient input. Methods: This retrospective study took information from the National Ambulatory Care Reporting System (NACRS) database for all ED visits in Ontario between April 1, 2003, and March 31, 2010. As there is no direct measure of SES available from ED visit records, a proxy measure of SES was used, namely a deprivation index (DI) developed from material and social factors from the 2006 Canadian census using the patient's residential neighbourhood. DI scores were assigned to ED visit records using Statistics Canada's Postal Code Conversion File, which links postal and census geography. Results: A total of 36,765,189 visits occurred during the study period. A cross-province trend was found wherein the most deprived population used EDs disproportionately more than the least deprived population (relative risk: 1.971 95% confidence interval 1.969-1.973, p , 0.0001). This trend was stable across the entire study period, although the divergence is attenuating. Conclusion: Social determinants of health clearly impact ED use patterns. People of the lowest SES use ED services disproportionately more than other socioeconomic groups. Focused health system planning and policy development directed at optimizing health services for the lowest SES populations are essential to changing ED use patterns and may be one method of decreasing ED overcrowding. RÉ SUMÉObjectif: L'encombrement des services des urgences (SU) au Canada est un problè me chronique, qui a pour effets de prolonger les dé lais d'attente, de diminuer la qualité des services, d'accroître les souffrances des patients et d'alté rer l'é volution de leur é tat de santé . Nous avons donc examiné la relation entre le statut socioé conomique (SSE) des usagers et l'utilisation des SU dans le cadre du systè me de soins de santé universels au Canada afin de dé gager les caracté ristiques de ces usagers, et ce, dans l'optique d'amé liorer la qualité des soins donné s aux populations les plus dé favorisé es et de diminuer le nombre de patients dans les SU. Ré sultats: Au total, 36 765 189 consultations ont é té dé nombré es durant la pé riode à l'é tude. Une tendance gé né rale s'est dé gagé e de tous les SU de la province: les populations les plus dé favorisé es ont eu recours aux SU de maniè re disproportionné e par rapport aux populations les moins dé favorisé es (risque relatif: 1.971; intervalle de confiance à 95%: 1.969-1.973; p , 0.0001). La tendance s'est ré vé lé e stable tout le long de la pé riode à l'é tude, bien que l'é cart soit en voie de diminution maintenant. Conclusions: Les dé terminants sociaux de la santé ...

BackgroundHgb A1c levels may be higher in persons without diabetes of lower socio-economic status (SES) but evidence about this association is limited; there is therefore uncertainty about the inclusion of SES in clinical decision support tools informing the provision and frequency of Hgb A1c tests to screen for diabetes. We studied the association between neighborhood-level SES and Hgb A1c in a primary care population without diabetes.MethodsThis is a retrospective study using data routinely collected in the electronic medical records (EMRs) of forty six community-based family physicians in Toronto, Ontario. We analysed records from 4,870 patients without diabetes, age 45 and over, with at least one clinical encounter between January 1st 2009 and December 31st 2011 and one or more Hgb A1c report present in their chart during that time interval. Residential postal codes were used to assign neighborhood deprivation indices and income levels by quintiles. Covariates included elements known to be associated with an increase in the risk of incident diabetes: age, gender, family history of diabetes, body mass index, blood pressure, LDL cholesterol, HDL cholesterol, triglycerides, and fasting blood glucose.ResultsThe difference in mean Hgb A1c between highest and lowest income quintiles was -0.04% (p = 0.005, 95% CI -0.07% to -0.01%), and between least deprived and most deprived was -0.05% (p = 0.003, 95% CI -0.09% to -0.02%) for material deprivation and 0.02% (p = 0.2, 95% CI -0.06% to 0.01%) for social deprivation. After adjustment for covariates, a marginally statistically significant difference in Hgb A1c between highest and lowest SES quintile (p = 0.04) remained in the material deprivation model, but not in the other models.ConclusionsWe found a small inverse relationship between Hgb A1c and the material aspects of SES; this was largely attenuated once we adjusted for diabetes risk factors, indicating that an independent contribution of SES to increasing Hgb A1c may be limited. This study does not support the inclusion of SES in clinical decision support tools that inform the use of Hgb A1c for diabetes screening.

BackgroundCalls to a telephone health helpline (THHL) have been previously evaluated for the ability to monitor specific syndromes, such as fever and influenza-like-illness or gastrointestinal illness. This method of surveillance has been shown to be highly correlated with traditional surveillance methods, and to have potential for early detection of community-based illness. Self-sampling, or having a person take his/her own nasal swab, has also proven successful as a useful method for obtaining a specimen, which may be used for respiratory virus detection.MethodsThis study describes a self-swabbing surveillance system mediated by a nurse-led THHL in Ontario whereby syndromic surveillance concepts are used to recruit and monitor participants with influenza-like illness. Once recruited, participants collect a nasal specimen obtained by self-swabbing and submit for testing and laboratory confirmation. Enumeration of weekly case counts was used to evaluate the timeliness of the self-swabbing surveillance system through comparison to other respiratory virus and influenza surveillance systems in Ontario. The operational efficiency of the system was also evaluated.ResultsThe mean and median number of days between the day that a participant called the THHL, to the day a package was received at the laboratory for testing were approximately 10.4 and 8.6 days, respectively. The time between self-swab collection and package reception was 4.9 days on average, with a median of 4 days. The self-swabbing surveillance system adequately captured the 2014 influenza B season in a timely manner when compared to other Ontario-based sources of influenza surveillance data from the same year; however, the emergence of influenza B was not detected any earlier than with these other surveillance systems. Influenza A surveillance was also evaluated. Using the THHL self-swabbing system, a peak in the number of cases for influenza A was observed approximately one week after or during the same week as that reported by the other surveillance systems.ConclusionThis one-year pilot study suggests that the THHL self-swabbing surveillance system has significant potential as an adjunct tool for the surveillance of influenza viruses in Ontario. Recommendations for improving system efficacy are discussed.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-016-3674-9) contains supplementary material, which is available to authorized users.

Lyme borreliosis, caused by the bacterium, Borrelia burgdorferi, is an emerging vector-borne infectious disease in Canada. According to the Public Health Agency of Canada (PHAC), by the year 2020, 80% of Canadians will live in Lyme endemic areas. An understanding of the association of Ixodes scapularis, the main vector of Lyme disease, with it hosts is a fundamental component in assessing changes in the spatial distribution of human risk for Lyme disease. Through the application of Geographic Information System (GIS) mapping methods and spatial analysis techniques, this study examines the population dynamics of the black-legged Lyme tick and its primary host, the white-tailed deer, in eastern Ontario, Canada. By developing a habitat suitability model through a GIS-based multi-criteria decision making (MCDM) analysis, the relationship of the deer habitat suitability map was generated and the results were compared with deer harvest data. Tick submission data collected from two public health units between 2006 and 2012 were used to explore the relationship between endemic ticks and deer habitat suitability in eastern Ontario. The positive correlation demonstrated between the deer habitat suitability model and deer harvest data OPEN ACCESS ISPRS Int. J. Geo-Inf. 2015, 4 106 allows us to further analyze the association between deer habitat and black-legged ticks in our study area. Our results revealed that the high tick submission number corresponds with the high suitability. These results are useful for developing management strategies that aim to prevent Lyme from becoming a threat to public health in Canada. Further studies are required to investigate how tick survival, behaviour and seasonal activity may change with projected climate change.

Abstract.Research to date has provided limited insight into the complexity of water-borne pathogen transmission. Private well water supplies have been identified as a significant pathway in infectious disease transmission in both the industrialised and the developing world. Using over 90,000 private well water submission records representing approximately 30,000 unique well locations in south-eastern Ontario, Canada, a spatial analysis was performed in order to delineate clusters with elevated risk of E. coli contamination using 5 years of data (2008)(2009)(2010)(2011)(2012). Analyses were performed for all years independently and subsequently compared to each other. Numerous statistically significant clusters were identified and both geographic stability and variation over time were examined. Through the identification of spatial and temporal patterns, this study provides the basis for future investigations into the underlying causes of bacterial groundwater contamination, while identifying geographic regions that merit particular attention to public health interventions and improvement of water quality.

Using simple syndromes based on keyword classification of geolocated tweets, we found a correlation between tweets and two routine data sources for heat alerts, the only public health event detected during P/PAG. Further research is needed to understand the role for Twitter in surveillance.