This is an RSS newsfeed from BioMed Central It is intended to be used with an RSS reader. For more information about RSS newsfeeds from BioMed Central, visit http://www.biomedcentral.com/info/about/rss/ http://www.ij-healthgeographics.com The latest articles from International Journal of Health Geographics (ISSN 1476-072X) published by BioMed Central Background: Chronic exposure to traffic-related air pollution is associated with a variety of health impacts in adults and recent studies show that exposure varies spatially, with some residents in a community more exposed than others. A spatial exposure simulation model (SESM) which incorporates six microenvironments (home indoor, work indoor, other indoor, outdoor, in-vehicle to work and in-vehicle other) is described and used to explore spatial variability in estimates of exposure to traffic-related nitrogen dioxide (not including indoor sources) for working people. The study models spatial variability in estimated exposure aggregated at the census tracts level for 382 census tracts in the Greater Vancouver Regional District of British Columbia, Canada. Summary statistics relating to the distributions of the estimated exposures are compared visually through mapping. Observed variations are explored through analyses of model inputs. Results: Two sources of spatial variability in exposure to traffic-related nitrogen dioxide were identified. Median estimates of total exposure ranged from 8 g/m3 to 35 g/m3 of annual average hourly NO2 for workers in different census tracts in the study area. Exposure estimates are highest where ambient pollution levels are highest. This reflects the regional gradient of pollution in the study area and the relatively high percentage of time spent at home locations. However, for workers within the same census tract, variations were observed in the partial exposure estimates associated with time spent outside the residential census tract. Simulation modeling shows that some workers may have exposures 1.3 times higher than other workers residing in the same census tract because of time spent away from the residential census tract, and that time spent in work census tracts contributes most to the differences in exposure. Exposure estimates associated with the activity of commuting by vehicle to work were negligible, based on the relatively short amount of time spent in this microenvironment compared to other locations. We recognize that this may not be the case for pollutants other than NO2. These results represent the first time spatially disaggregated variations in exposure to traffic-related air pollution within a community have been estimated and reported. Conclusions: The results suggest that while time spent in the home indoor microenvironment contributes most to between-census tract variation in estimates of annual average exposures to traffic-related NO2, time spent in the work indoor microenvironment contributes most to within-census tract variation, and time spent in transit by vehicle makes a negligible contribution. The SESM has potential as a policy evaluation tool, given input data that reflect changes in pollution levels or work flow patterns due to traffic demand management and land use development policy. http://www.ij-healthgeographics.com/content/7/1/39 Eleanor M Setton, C. Peter Keller, Denise Cloutier-Fisher and Perry W Hystad International Journal of Health Geographics 2008, 7:39 2008-07-18 doi:10.1186/1476-072X-7-39 International Journal of Health Geographics 1476-072X 7 39 2008-07-18 'Mashup' was originally used to describe the mixing together of musical tracks to create a new piece of music. The term now refers to Web sites or services that weave data from different sources into a new data source or service. Using a musical metaphor that builds on the origin of the word 'mashup', this paper presents a demonstration "playlist" of four geo-mashup vignettes that make use of a range of Web 2.0, Semantic Web, and 3-D Internet methods, with outputs/end-user interfaces spanning the flat Web (two-dimensional -- 2-D maps), a three-dimensional -- 3-D mirror world (Google Earth) and a 3-D virtual world (Second Life (R)). The four geo-mashup "songs" in this "playlist" are: 'Web 2.0 and GIS (Geographic Information Systems) for infectious disease surveillance', 'Web 2.0 and GIS for molecular epidemiology', 'Semantic Web for GIS mashup', and 'From Yahoo! Pipes to 3-D, avatar-inhabited geo-mashups'. It is hoped that this showcase of examples and ideas, and the pointers we are providing to the many online tools that are freely available today for creating, sharing and reusing geo-mashups with minimal or no coding, will ultimately spark the imagination of many public health practitioners and stimulate them to start exploring the use of these methods and tools in their day-to-day practice. The paper also discusses how today's Web is rapidly evolving into a much more intensely immersive, mixed-reality and ubiquitous socio-experiential Metaverse that is heavily interconnected through various kinds of user-created mashups. http://www.ij-healthgeographics.com/content/7/1/38 Maged N Kamel Boulos, Matthew Scotch, Kei-Hoi Cheung and David Burden International Journal of Health Geographics 2008, 7:38 2008-07-18 doi:10.1186/1476-072X-7-38 International Journal of Health Geographics 1476-072X 7 38 2008-07-18 Background: Health professionals, policy-makers and researchers need to be able to explore potential associations between prevalence rates and quality of care with a range of possible determinants including socio-economic deprivation and morbidity levels to determine the impact of commissioning and service delivery. In the UK, data in England are only available nationally at practice postcode level. In Scotland, such data are available based on an aggregate of the practices population's postcodes. The use of data assigned to the practice postcode may underestimate the association between ill health and income deprivation. Here, we report on the impact of using data assigned to the practice population by comparing analyses using English and Scottish data. Results: Income deprivation based on data assigned to the practice postcode under-estimated deprivation compared to using income deprivation data assigned to the practice population for the five least deprived deciles, and over-estimated deprivation for the five most deprived deciles. The biggest differences were found for the most deprived decile. A similar trend was found for limiting long-term illness (LLTI). Differences between the QOF prevalence rates of the least and most deprived deciles using practice postcode data were similar (0.2% points or less) in England and Scotland for 8 out of 10 clinical domains. Using practice population assigned deprivation, differences in the prevalence rate between the least and most deprived deciles increase for all clinical domains. A similar trend was again found for LLTI. Using practice population assigned deprivation, differences for population achievement increase for all CHD quality indicators with the exception of beta-blockers (CHD10). With practice postcode assigned deprivation, significant differences between the least and most deprived deciles were found for 2 out 8 indicators, compared to 5 using practice population assigned deprivation. For LLTI differences between the lowest and most deprived deciles increased for all indicators when ill health assigned to the practice population was used. Conclusion: We have found, through comparing deprivation and ill health data assigned to either the practice postcode or the practice population postcode in Scotland, that analyses based on practice postcode assigned data under-estimated the relationship between deprivation and ill health for both prevalence and quality care. Given the importance of understanding the effect of deprivation and ill health on a range of determinants related to health care, policy makers should ensure that practice population data are available and used at national level in England and elsewhere where possible. http://www.ij-healthgeographics.com/content/7/1/37 Gary McLean, Bruce Guthrie, Graham Watt, Mark Gabbay and Catherine A O'Donnell International Journal of Health Geographics 2008, 7:37 2008-07-16 doi:10.1186/1476-072X-7-37 International Journal of Health Geographics 1476-072X 7 37 2008-07-16 Background: The Pennsylvania Cancer Atlas (PA-CA) is an interactive online atlas to help policy-makers, program managers, and epidemiologists with tasks related to cancer prevention and control. The PA-CA includes maps, graphs, tables, that are dynamically linked to support data exploration and decision-making with spatio-temporal cancer data. Our atlas development process follows a user-centered design approach. To assess the usability of the initial versions of the PA-CA, we developed and applied a novel strategy for soliciting user feedback through multiple distributed focus groups and surveys. Our process of acquiring user feedback leverages an online web application (e-Delphi). In this paper we describe the PA-CA, detail how we have adapted e-Delphi web application to support usability and utility evaluation of the PA-CA, and present the results of our evaluation. Results: We report results from four sets of users. Each group provided structured individual and group assessments of the PA-CA as well as input on the kinds of users and applications for which it is best suited.. Overall reactions to the PA-CA are quite positive. Participants did, however, provide a range of useful suggestions. Key suggestions focused on improving interaction functions, enhancing methods of temporal analysis, addressing data issues, and providing additional data displays and help functions. These suggestions were incorporated in each design and implementation iteration for the PA-CA and used to inform a set of web-atlas design principles. Conclusions: For the atlas, we find that a design that utilizes linked map, graph, and table views is understandable to and perceived to be useful by the target audience of cancer prevention and control professionals. However, it is clear that considerable variation in experience using maps and graphics exists and for those with less experience, integrated tutorials and help features are needed. In relation to our usability assessment strategy, we find that our distributed, web-based method for soliciting user input is generally effective. Advantages include the ability to gather information from users distributed in time and space and the relative anonymity of the participants while disadvantages include less control over when and how often participants provide input and challenges for obtaining rich input. http://www.ij-healthgeographics.com/content/7/1/36 Tanuka Bhowmick, Anthony C Robinson, Adrienne Gruver, Alan M MacEachren and Eugene J Lengerich International Journal of Health Geographics 2008, 7:36 2008-07-11 doi:10.1186/1476-072X-7-36 International Journal of Health Geographics 1476-072X 7 36 2008-07-11 Background: Since 1999, the expansion of the West Nile virus (WNV) epizooty has led public health authorities to build and operate surveillance systems in North America. These systems are very useful to collect data, but cannot be used to forecast the probable spread of the virus in coming years. Such forecasts, if proven reliable, would permit preventive measures to be put into place at the appropriate level of expected risk and at the appropriate time. It is within this context that the Multi-Agent Geo-Simulation approach has been selected to develop a system that simulates the interactions of populations of mosquitoes and birds over space and time in relation to the spread and transmission of WNV. This simulation takes place in a virtual mapping environment representing a large administrative territory (e.g. province, state) and carried out under various climate scenarios in order to simulate the effects of vector control measures such as larviciding at scales of 1/20 000 or smaller. Results: After setting some hypotheses, a conceptual model and system architecture were developed to describe the population dynamics and interactions of mosquitoes (genus Culex) and American crows, which were chosen as the main actors in the simulation. Based on a mathematical compartment model used to simulate the population dynamics, an operational prototype was developed for the Southern part of Quebec (Canada). The system allows users to modify the parameters of the model, to select various climate and larviciding scenarios, to visualize on a digital map the progression (on a weekly or daily basis) of the infection in and around the crows' roosts and to generate graphs showing the evolution of the populations. The basic units for visualisation are municipalities. Conclusion: In all likelihood this system might be used to support short term decision-making related to WNV vector control measures, including the use of larvicides, according to climatic scenarios. Once fully calibrated in several real-life contexts, this promising approach opens the door to the study and management of other zoonotic diseases such as Lyme disease. http://www.ij-healthgeographics.com/content/7/1/35 Mondher Bouden, Bernard Moulin and Pierre Gosselin International Journal of Health Geographics 2008, 7:35 2008-07-07 doi:10.1186/1476-072X-7-35 International Journal of Health Geographics 1476-072X 7 35 2008-07-07 Background: Every year, West Africa is afflicted with Meningococcal Meningitis (MCM) disease outbreaks. Although the seasonal and spatial patterns of disease cases have been shown to be linked to climate, the mechanisms responsible for these patterns are still not well identified. Results: A statistical analysis of annual incidence of MCM and climatic variables has been performed to highlight the relationships between climate and MCM for two highly afflicted countries: Niger and Burkina Faso. We found that disease resurgence in Niger and in Burkina Faso is likely to be partly controlled by the winter climate through enhanced Harmattan winds. Statistical models based only on climate indexes work well in Niger showing that 25% of the disease variance from year-to-year in this country can be explained by the winter climate but fail to represent accurately the disease dynamics in Burkina Faso. Conclusions: This study is an exploratory attempt to predict meningitis incidence by using only climate information. Although it points out significant statistical results it also stresses the difficulty of relating climate to interannual variability in meningitis outbreaks. http://www.ij-healthgeographics.com/content/7/1/34 Pascal Yaka, Benjamin Sultan, Helene Broutin, Serge Janicot, Solenne Philippon and Nicole Fourquet International Journal of Health Geographics 2008, 7:34 2008-07-02 doi:10.1186/1476-072X-7-34 International Journal of Health Geographics 1476-072X 7 34 2008-07-02 Background: Surveillance of infectious diseases increasingly relies on Geographic Information Systems (GIS). The integration of pathogen fine typing data in dynamic systems and visualization of spatio-temporal clusters are a technical challenge for system development. Results: An online geographic information system (EpiScanGIS) based on open source components has been launched in Germany in May 2006 for real time provision of meningococcal typing data in conjunction with demographic information (age, incidence, population density). Spatio-temporal clusters of disease detected by computer assisted cluster analysis (SaTScanTM) are visualized on maps. EpiScanGIS enables dynamic generation of animated maps. The system is based on open source components; its architecture is open for other infectious agents and geographic regions. EpiScanGIS is available at www.episcangis.org, and currently has 80 registered users, mostly from the public health service in Germany. At present more than 2,900 cases of invasive meningococcal disease are stored in the database (data as of June 3, 2008). Conclusions: EpiScanGIS exemplifies GIS applications and early-warning systems in laboratory surveillance of infectious diseases. http://www.ij-healthgeographics.com/content/7/1/33 Markus Reinhardt, Johannes Elias, Jurgen Albert, Matthias Frosch, Dag Harmsen and Ulrich Vogel International Journal of Health Geographics 2008, 7:33 2008-07-01 doi:10.1186/1476-072X-7-33 International Journal of Health Geographics 1476-072X 7 33 2008-07-01 Background: Mammography is essential for early detection of breast cancer and both reduced morbidity and increased survival among breast cancer victims. Utilization is lower than national guidelines, and evidence of a recent decline in mammography use has sparked concern. We demonstrate that regression models estimated over pooled samples of heterogeneous states may provide misleading information regarding predictors of health care utilization and that comprehensive cancer control efforts should focus on understanding these differences and underlying causal factors. Our study population includes all women over age 64 with breast cancer in the Surveillance Epidemiology and End Results (SEER) cancer registries, linked to a nationally representative 5% reference sample of Medicare-eligible women located in 11 states that span all census regions and are heterogeneous in racial and ethnic mix. Combining women with and without cancer in the sample allows assessment of previous cancer diagnosis on propensity to use mammography. Our conceptual model recognizes the interplay between individual, social, cultural, and physical environments along the pathways to health care utilization, while delineating local and more distant levels of influence among contextual variables. In regression modeling, we assess individual-level effects, direct effects of contextual factors, and interaction effects between individual and contextual factors. Results: Pooling all women across states leads to quite different conclusions than state-specific models. Commuter intensity, community acculturation, and community elderly impoverishment have significant direct impacts on mammography use which vary across states. Minorities living in isolated enclaves with others of the same race/ethnicity may be either advantaged or disadvantaged, depending upon the place studied. Conclusion: Careful analysis of place-specific context is essential for understanding differences across communities stemming from different causal factors. Optimal policy interventions to change behavior (improve screening rates) will be as heterogeneous as local community characteristics, so no "one size fits all" policy can improve population health. Probability modeling with correction for clustering of individuals within multilevel contexts can reveal important differences from place to place and identify key factors to inform targeting of specific communities for further study. http://www.ij-healthgeographics.com/content/7/1/32 Lee R Mobley, Tzy-Mey (May) Kuo, David Driscoll, Laurel Clayton and Luc Anselin International Journal of Health Geographics 2008, 7:32 2008-06-30 doi:10.1186/1476-072X-7-32 International Journal of Health Geographics 1476-072X 7 32 2008-06-30 Background: The seasonality of cholera is described in various study areas throughout the world. However, no study examines how temporal cycles of the disease vary around the world or reviews its hypothesized causes. This paper reviews the literature on the seasonality of cholera and describes its temporal cycles by compiling and analyzing 32 years of global cholera data. This paper also provides a detailed literature review on regional patterns and environmental and climatic drivers of cholera patterns.Data, Methods, and ResultsCholera data are compiled from 1974 to 2005 from the World Health Organization Weekly Epidemiological Reports, a database that includes all reported cholera cases in 140 countries. The data are analyzed to measure whether season, latitude, and their interaction are significantly associated with the country-level number of outbreaks in each of the 12 preceding months using separate negative binomial regression models for northern, southern, and combined hemispheres. Likelihood ratios tests are used to determine the model of best fit. The results suggest that cholera outbreaks demonstrate seasonal patterns in higher absolute latitudes, but closer to the equator, cholera outbreaks do not follow a clear seasonal pattern. Conclusion: The findings suggest that environmental and climatic factors partially control the temporal variability of cholera. These results also indirectly contribute to the growing debate about the effects of climate change and global warming. As climate change threatens to increase global temperature, resulting rises in sea levels and temperatures may influence the temporal fluctuations of cholera, potentially increasing the frequency and duration of cholera outbreaks. http://www.ij-healthgeographics.com/content/7/1/31 Michael Emch, Caryl Feldacker, M Sirajul Islam and Mohammad Ali International Journal of Health Geographics 2008, 7:31 2008-06-20 doi:10.1186/1476-072X-7-31 International Journal of Health Geographics 1476-072X 7 31 2008-06-20 Background: A community health assessment (CHA) is used to identify and address health issues in a given population. Effective CHA requires timely and comprehensive information from a wide variety of sources, such as: socio-economic data, disease surveillance, healthcare utilization, environmental data, and health resource allocation. Indonesia is a developing country with 235 million inhabitants over 13,000 islands. There are significant barriers to conducting CHA in developing countries like Indonesia, such as the high cost of computing resources and the lack of computing skills necessary to support such an assessment. At the University of Pittsburgh, we have developed the Spatial OLAP (On-Line Analytical Processing) Visualization and Analysis Tool (SOVAT) for performing CHA. SOVAT combines Geographic Information System (GIS) technology along with an advanced multidimensional data warehouse structure to facilitate analysis of large, disparate health, environmental, population, and spatial data. The objective of this paper is to demonstrate the potential of SOVAT for facilitating CHA among developing countries by using health, population, healthcare resources, and spatial data from Indonesia for use in two CHA cases studies. Results: Bureau of Statistics administered data sets from the Indonesian Census, and the Indonesian village statistics, were used in the case studies. The data consisted of: healthcare resources (number of healthcare professionals and facilities), population (census), morbidity and mortality, and spatial (GIS-formatted) information. The data was formatted, combined, and populated into SOVAT for CHA use. Case study 1 involves the distribution of healthcare professionals in Indonesia, while case study 2 involves malaria mortality. Screen shots are shown for both cases. The results for the CHA were retrieved in seconds and presented through the geospatial and numerical SOVAT interface. Conclusions: The case studies show the potential of spatial and multidimensional analysis using SOVAT for community health assessment in developing countries. Financial challenges as well as limited technological skills are barriers in conducting CHA in these environments. Since SOVAT is based primarily on open-source components and can be deployed using small personal computers, it is cost-effective for developing countries. Also, combining the strength in analysis and the ease of use makes tools like SOVAT ideal for healthcare professionals without extensive computer skills. http://www.ij-healthgeographics.com/content/7/1/30 Bambang Parmanto, Maria Paramita, Wayan Sugiantara, Gede Pramana, Matthew Scotch and Donald S Burke International Journal of Health Geographics 2008, 7:30 2008-06-11 doi:10.1186/1476-072X-7-30 International Journal of Health Geographics 1476-072X 7 30 2008-06-11