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Abstract Background Rates for Diabetes Mellitus continue to rise in most urban areas of the United States, with a disproportionate burden suffered by minorities and low income populations. This paper presents an approach that utilizes address level data to understand the geography of this disease by analyzing patients seeking diabetes care through an emergency department in a Los Angeles County hospital. The most vulnerable frequently use an emergency room as a common care access point, and such care is especially costly. A fine scale GIS analysis reveals hotspots of diabetes related health problems and provides output useful in a clinic setting. Indeed these results were used to support the work of a progressive diabetes clinic to guide management and intervention strategies. Results Hotspots of diabetes related health problems, including neurological and kidney issues were mapped for vulnerable populations in a central section of Los Angeles County. The resulting spatial grid of rates and significance were overlaid with new patient residential addresses attending an area clinic. In this way neighbourhood diabetes health characteristics are added to each patient's individual health record. Of the 29 patients, 4 were within statistically significant hotspots for at least one of the conditions being investigated. Conclusions Although exploratory in nature, this approach demonstrates a novel method to conduct GIS based investigations of urban diabetes while providing support to a progressive diabetes clinic looking for novel means of managing and intervention. In so doing, this analysis adds to a relatively small literature on fine scale GIS facilitated diabetes research. Similar data should be available for most hospitals, and with due consideration for preserving spatial confidentiality, analysis outputs such as those presented here should become more commonly employed in other investigations of chronic diseases.

Abstract This paper offers a state-of-the-art overview of the intertwined privacy, confidentiality, and security issues that are commonly encountered in health research involving disaggregate geographic data about individuals. Key definitions are provided, along with some examples of actual and potential security and confidentiality breaches and related incidents that captured mainstream media and public interest in recent months and years. The paper then goes on to present a brief survey of the research literature on location privacy/confidentiality concerns and on privacy-preserving solutions in conventional health research and beyond, touching on the emerging privacy issues associated with online consumer geoinformatics and location-based services. The 'missing ring' (in many treatments of the topic) of data security is also discussed. Personal information and privacy legislations in two countries, Canada and the UK, are covered, as well as some examples of recent research projects and events about the subject. Select highlights from a June 2009 URISA (Urban and Regional Information Systems Association) workshop entitled 'Protecting Privacy and Confidentiality of Geographic Data in Health Research' are then presented. The paper concludes by briefly charting the complexity of the domain and the many challenges associated with it, and proposing a novel, 'one stop shop' case-based reasoning framework to streamline the provision of clear and individualised guidance for the design and approval of new research projects (involving geographical identifiers about individuals), including crisp recommendations on which specific privacy-preserving solutions and approaches would be suitable in each case.

Abstract Background An epidemic may exhibit different spatial patterns with a change in geographic scale, with each scale having different conduits and impediments to disease spread. Mapping disease at each of these scales often reveals different cluster patterns. This paper will consider this change of geographic scale in an analysis of yellow fever deaths for New Orleans in 1878. Global clustering for the whole city, will be followed by a focus on the French Quarter, then clusters of that area, and finally street-level patterns of a single cluster. The three-dimensional visualization capabilities of a GIS will be used as part of a cluster creation process that incorporates physical buildings in calculating mortality-to-mortality distance. Including nativity of the deceased will also capture cultural connection. Results Twenty-two yellow fever clusters were identified for the French Quarter. These generally mirror the results of other global cluster and density surfaces created for the entire epidemic in New Orleans. However, the addition of building-distance, and disease specific time frame between deaths reveal that disease spread contains a cultural component. Same nativity mortality clusters emerge in a similar time frame irrespective of proximity. Italian nativity mortalities were far more densely grouped than any of the other cohorts. A final examination of mortalities for one of the nativity clusters reveals that further sub-division is present, and that this pattern would only be revealed at this scale (street level) of investigation. Conclusion Disease spread in an epidemic is complex resulting from a combination of geographic distance, geographic distance with specific connection to the built environment, disease-specific time frame between deaths, impediments such as herd immunity, and social or cultural connection. This research has shown that the importance of cultural connection may be more important than simple proximity, which in turn might mean traditional quarantine measures should be re-evaluated.

Abstract Background Geographic Information Systems (GIS) can provide valuable insight into patterns of human activity. Online spatial display applications, such as Google Earth, can democratise this information by disseminating it to the general public. Although this is a generally positive advance for society, there is a legitimate concern involving the disclosure of confidential information through spatial display. Although guidelines exist for aggregated data, little has been written concerning the display of point level information. The concern is that a map containing points representing cases of cancer or an infectious disease, could be re-engineered back to identify an actual residence. This risk is investigated using point mortality locations from Hurricane Katrina re-engineered from a map published in the Baton Rouge Advocate newspaper, and a field team validating these residences using search and rescue building markings. Results We show that the residence of an individual, visualized as a generalized point covering approximately one and half city blocks on a map, can be re-engineered back to identify the actual house location, or at least a close neighbour, even if the map contains little spatial reference information. The degree of re-engineering success is also shown to depend on the urban characteristic of the neighborhood. Conclusion The results in this paper suggest a need to re-evaluate current guidelines for the display of point (address level) data. Examples of other point maps displaying health data extracted from the academic literature are presented where a similar re-engineering approach might cause concern with respect to violating confidentiality. More research is also needed into the role urban structure plays in the accuracy of re-engineering. We suggest that health and spatial scientists should be proactive and suggest a series of point level spatial confidentiality guidelines before governmental decisions are made which may be reactionary toward the threat of revealing confidential information, thereby imposing draconian limits on research using a GIS.