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Über dieses Buch

This book focuses on a range of geospatial applications for environmental health research, including environmental justice issues, environmental health disparities, air and water contamination, and infectious diseases. Environmental health research is at an exciting point in its use of geotechnologies, and many researchers are working on innovative approaches. This book is a timely scholarly contribution in updating the key concepts and applications of using GIS and other geospatial methods for environmental health research. Each chapter contains original research which utilizes a geotechnical tool (Geographic Information Systems (GIS), remote sensing, GPS, etc.) to address an environmental health problem. The book is divided into three sections organized around the following themes: issues in GIS and environmental health research; using GIS to assess environmental health impacts; and geospatial methods for environmental health. Representing diverse case studies and geospatial methods, the book is likely to be of interest to researchers, practitioners and students across the geographic and environmental health sciences. The authors are leading researchers and practitioners in the field of GIS and environmental health.

Inhaltsverzeichnis

Frontmatter

General Considerations in Geospatial Analysis of Environmental Health

Frontmatter

Chapter 1. Environmental Health and Geospatial Analysis: An Overview

Abstract
This chapter provides a brief overview of the use of geographic information science (GISc) in environmental health research and reviews the main themes and concepts highlighted in each chapter. We summarize applications of GISc in environmental hazard surveillance, exposure assessment and health outcomes surveillance. Challenges of using geospatial tools and methods are discussed. The final sections briefly review the contributions of each chapter and the connections among chapters.
Juliana A. Maantay, Sara McLafferty

Chapter 2. Using Geovisualization and Geospatial Analysis to Explore Respiratory Disease and Environmental Health Justice in New York City

Abstract
The goal of this chapter is to illustrate how complex issues in environmental health justice analysis can benefit from geovisualization and exploration within a Geographic Information Science (GISc) framework. Individual health outcome variables, such as hospitalizations due to respiratory disease, can be very difficult to interpret without a geographic context; and interactions amongst variables such as disease, socio-demographic characteristics, or environmental exposures, further complicate an accurate interpretation of the data. Data exploration and visualization through mapping and spatial analysis often provides a more robust understanding of the data, as well as improved clarity in viewing the phenomena under study, which will lead to better design of further analyses and additional hypothesis generation, in an iterative fashion. In the first part of this chapter, we use a hypothetical data set to illustrate some of the data exploration, geovisualization, statistical methods, and geospatial analyses. In the second part of the chapter, we use a worked example of respiratory disease and socio-demographic variables in New York City to assess potential environmental justice impacts, in order to further demonstrate the importance of geovisualization and geospatial analysis in achieving a better understanding of environmental health issues.
Andrew Maroko, Juliana A. Maantay, Kristen Grady

Chapter 3. Outdoor Air Pollution and Health – A Review of the Contributions of Geotechnologies to Exposure Assessment

Abstract
An individual’s exposure to air pollution is affected by the variability of pollution concentrations at different locations and times. The most accurate measures of exposure incorporate personal monitoring, but as the number of people included in a study increases, the feasibility of conducting individual-level monitoring quickly decreases, thus requiring the development of more practical approaches, sometimes at the cost of capturing these key sources of variability. In this chapter, we focus on how geotechnologies contribute to characterizing variable air pollution levels and individual geographic mobility with respect to exposure assessment for epidemiological and exposure determinants studies. Rather than an exhaustive literature review, we provide a general discussion of geotechnology uses, include representative examples from epidemiological or exposure determinants studies, and identify limitations and future potential applications. Approaches discussed include simple proximity-to-source or monitor methods, dispersion models, spatial interpolation techniques, and the potential for using satellite-derived air pollution estimates and global positioning systems. The use of time-activity patterns and travel surveys is also included. Finally, an annotated list of recommended review articles is provided for readers interested in more in-depth treatment of many of the topics presented in this chapter.
Eleanor M. Setton, Ryan Allen, Perry Hystad, C. Peter Keller

Chapter 4. The Use of Residential History in Environmental Health Studies

Abstract
Residential histories – listings of the places and dates where people have lived over their lives – are useful for assessing lifetime proximity to environmental hazards. When past residences are ignored, as is the norm, results are biased against finding an association between exposure and disease. I conducted a comprehensive review of 26 published environmental epidemiological studies using residential histories to assess current practice. Most often, studies collect all of a person’s exact lifetime addresses resided in for at least 1 year, and exclude missing data – reasonable, though not necessarily optimal, choices. Residential histories are complex and time-consuming to collect, and must be researcher-initiated, as they are not an element of any population-based disease surveillance systems in the United States. Indeed, surveillance systems often have difficulty collecting even basic demographic items. As such, residential histories are best suited for focused research studies involving direct contact with subjects through interviews or questionnaires.
Francis P. Boscoe

Chapter 5. Proximity Analysis for Exposure Assessment in Environmental Health Justice Research

Abstract
This chapter provides a historical overview and constructive critique of analytical approaches and methods that have been used to measure proximity to environmental health hazards and potential exposure to their adverse effects in the environmental justice (EJ) research literature. After providing an introduction to environmental health justice research and key findings, we examine how quantitative EJ analysis has emerged from comparing the prevalence of minority or low-income populations in spatial units hosting environmental hazards and circular buffer zones to more advanced techniques that utilize GIS, pollution plume models, and estimates of health risk from ambient exposure to multiple pollutants and emission sources. We also review spatial analytical approaches used in previous studies to determine the demographic and socioeconomic characteristics of people residing in areas potentially exposed to environmental hazards, as well as newly emerging geostatistical techniques that are more appropriate for spatial analysis of EJ than conventional statistical methods used in prior research. The concluding section focuses on highlighting the key limitations and identifying future research needs associated with assessment of environmental health justice.
Jayajit Chakraborty, Juliana A. Maantay

Chapter 6. Their Data, Our Cause: An Exploration of the Form, Function, and Deployment of Mapping Technologies among Community Environmental Justice Organizations

Abstract
The field of environmental justice offers many examples of the utility of maps and GIS for illustrating the disproportionate levels of environmental risk being endured by disadvantaged or marginalized racial, ethnic or income groups. However, these have predominantly focused on the distribution of environmental risk rather than focusing on the map-making parties themselves. This research directs attention towards the use of maps and GIS by “local” environmental justice organizations in their calls for environmental justice. I focus on activist engagement with maps and mapping technologies like GIS. Through a survey of community-based environmental organizations, I examine whether these organizations use maps and if so, how maps are produced including the sources of mapping knowledge used in the map-making process. By examining how and why such organizations map environmental hazards and use GIS, this chapter provides insights into the notion of GIS mapping as an empowering practice. I assess the types of maps produced and the data sources used in order to see more clearly potential restrictions on the power and ability of organizations to counter dominant narratives of their communities. This research reveals that while these organizations recognize the importance of maps to their efforts, there are significant differences in the resources and abilities of environmental justice organizations.
Trevor Fuller

Impacts on Environmental Health (Topical Case Studies)

Frontmatter

Chapter 7. Geospatial Analysis of West Nile Virus (WNV) Incidences in a Heterogeneous Urban Environment: A Case Study in the Twin Cities Metropolitan Area of Minnesota

Abstract
West Nile virus (WNV) infected dead bird sites and human cases are frequently located in the densely populated, urban areas primarily because they are reported by people. However, the spatial pattern (i.e. morphology) of the urban landscape features could also contribute to the location of WNV incidences. This study has two objectives: (1) analyzing the association of urban environmental features that facilitated the viral activities of WNV infection in the TCMA from 2002 to 2007 and (2) comparing the spatial association between WNV infected mosquito pools and human cases with heterogeneous urban characteristics. It also addresses the question of how urban morphology affects human health. Using a combination of factorial ecology, geospatial techniques, and hierarchical cluster analysis, urban landscape classes are derived from the environmental and built environment risk-factors hypothesized to be associated with WNV transmission. The infection rate among, birds, mosquitoes, and human cases are then compared to these urban classes. Results indicate that the WNV infection rate is considerably higher in the urban class located just outside the cities of Minneapolis and Saint Paul. The dominant features of this class are close proximity to bogs and swamps, parks, sewerage system, waste water discharge sites, trails, high density of catch basins, moderate density of single family houses, and medium vegetation cover with stagnant waters. In general, the rate of infection decreases with increasing distance from the urban core. This is critical, in terms of vector control policies, because two out of four WNV carrying vectors, Culex restuans and Culex pipiens are predominantly urban mosquitoes.
Debarchana Ghosh

Chapter 8. The Health Impacts of Brownfields in Charlotte, NC: A Spatial Approach

Abstract
Brownfield redevelopment in Charlotte, North Carolina has been a success in terms of leveraging private investment, increasing tax bases, and creating job opportunities. Little is known, however, about the potential health impacts of these brownfield sites in the city. This research intends to fill this gap by examining the effect of brownfield sites on neighborhood Low Birth Weight (LBW) rate. The health impact is measured as a function of proximity to brownfield sites, inactive hazardous site density, population’s economic status, and the community’s socio-economic attributes. The analyses show that being close to brownfield sites is not significantly related to having a higher rate of Low Birth Weight, but the density of brownfields in the census block group is related to a higher LBW rate. The Geographically Weighted Regression (GWR) model reveals that there is a considerable spatial variation in the strength of the health impacts. The local health department has indicated lack of capacity to examine the variation in community health status. The findings of this study can serve as the starting point for local health professionals to identify communities that are impacted by brownfields the most, and therefore more actively participate in brownfield redevelopment.
Junfeng Wang

Chapter 9. Regional Environmental Patterns of Diarrheal Disease in Bangladesh: A Spatial Analytical and Multilevel Approach

Abstract
This study investigates diarrheal disease distributions in Bangladesh using nationally representative household-level survey data integrated with land type maps that characterize flood inundation levels. The spatial distribution of childhood diarrhea is mapped throughout the country and diarrhea rates are stratified by individual, household, and regional-level variables. This study describes national-level trends by integrating spatially-referenced household characteristics and regional-level information on water and sanitation. The world saw dramatic improvements in water availability during the 1980s, designated “International Water Supply and Sanitation Decade” by the UN. Nevertheless, reductions in diarrheal morbidity in much of the developing world have been modest, possibly because of a lack of sufficient parallel improvements in sanitation and hygiene (Levine et al., Lancet 2(7976):86–89, 1976; Esrey et al., Bull World Health Organ 63:757–772, 1985; Hoque et al., Bull World Health Organ 74:431–437, 1996). In a recent meta-analysis of 64 studies, Fewtrell and Colford (Health, Nutrition, Population Discussion Paper, World Bank, Washington DC, http://​www1.​worldbank.​org/​hnp/​Pubs_​Discussion/​Fewtrell&​ColfordJuly2004.​pdf, 2004) found that water supply, water quality, hygiene, and sanitation programs all reduce diarrheal disease mortality and morbidity. However, multiple interventions did not reduce diarrheal disease any more than approaches that involved only one intervention. This suggests that a better fundamental understanding of the relationship between water, sanitation, household characteristics and diarrheal disease is needed to optimize future interventions. This study begins to investigate these relationships using data at different collected at multiple scales.
Elisabeth D. Root, Michael Emch

Chapter 10. Developing a Supermarket Need Index

Abstract
The New York City Department of City Planning with assistance from the New York City Department of Health and Mental Hygiene developed a supermarket need index to determine the areas in the city with the highest levels of diet-related diseases and largest populations with limited opportunities to purchase fresh foods. The index was created using Geographic Information Systems to measure the need for supermarkets based on high population density, low access to a car at the household level, low household incomes, high rates of diabetes, high rates of obesity, low consumption of fresh fruits and vegetables, low share of fresh food retail, and capacity for new stores. The resulting index identified areas of acute need for additional full-line grocery stores, encompassing portions of the city where approximately three million New Yorkers reside.
Laura Smith, Chris Goranson, Jodi Bryon, Bonnie Kerker, Cathy Nonas

Chapter 11. Asthma, Air Quality and Environmental Justice in Louisville, Kentucky

Abstract
Many analyses have demonstrated that environmental hazards tend to be concentrated in areas with higher numbers of low-income populations and people of color. We used geographic information science (GISc) and statistical analyses to examine issues of air quality and asthma occurrence among urban children in Louisville, Kentucky. The results of our analyses indicate that there is a well-defined spatial cluster of high rates of childhood asthma hospitalizations in western Louisville, an area of the city that is notorious for its poor air quality and the poor economic and physical health of its residents. Analyses also confirmed a strong seasonal pattern to asthma, with a fall peak. The multi-factorial etiology of asthma makes it difficult to pinpoint specific triggers for acute asthma episodes. Analyses of EPA criteria pollutants and volatile organic compounds from local air monitoring sites showed very little correlation with hospital admissions, although acetone, acrylonitrile and chloroform manifested similar seasonal patterns. In order to address the environmental justice concerns of disproportionate siting vs. minority move-in, we used GISc to examine patterns of residential mobility in western Louisville over a 60-year period. The polluting industries in western Louisville’s “Rubbertown” preceded the local in-migration of African-Americans, the majority of which took place from 1960 to 1970. While the increasing African-American presence in the community has resulted in a community with greater social cohesion over time and successful community-based initiatives to reduce air toxics emissions have been implemented, significant health disparities in western Louisville must continue to be addressed.
Carol Hanchette, Jong-Hyung Lee, Tim E. Aldrich

Chapter 12. The Impact of Changes in Municipal Solid Waste Disposal Laws on Proximity to Environmental Hazards: A Case Study of Connecticut

Abstract
Environmental policies affect proximity to environmental hazards. In the late 1980s, the State of Connecticut implemented mandatory recycling laws to improve management of municipal solid waste. At that time, more than 80% of the State’s 169 towns disposed of trash within their own borders. The regulatory change redirected flows of waste to transfer stations and trash-to-energy plants. To assess changes in the proximity to hazards associated with this shift, the origins and destinations of solid waste shipment flows are modeled using data for 2008. Ton-weighted distances to disposal are estimated for 2008 and compared to the distances if solid waste had continued to be disposed of within towns. Changes in municipal solid waste management in Connecticut have differentially impacted local communities. Residents of the Town of Hartford, particularly low-income minority residents in the North End, have been affected by the operation of municipal solid waste management facilities in Hartford, which receive waste from almost half the towns in the state. The implementation of environmental policies intended to improve municipal solid waste disposal at the state level adversely affected proximity to environmental hazards in selected communities and the abilities of local communities to improve environmental quality in their own jurisdictions.
Ellen K. Cromley

Chapter 13. Global Geographies of Environmental Injustice and Health: A Case Study of Illegal Hazardous Waste Dumping in Côte d’Ivoire

Abstract
Global environmental injustice, the unfair distribution of hazardous activities and materials in disadvantaged communities, is increasingly evident in the African continent through transboundary pollution and illegal disposal of hazardous wastes. Studies are needed to uncover the underlying factors that account for these trends and the detrimental health effects in the host communities. This chapter examines a recent incident involving the disposal of hazardous wastes in Abidjan, Cote d’Ivoire. Specifically, in August 2006, hazardous wastes consisting of mercaptans, hydrogen sulfide, phenols, and hydrocarbons were dumped illegally in seventeen locations resulting in approximately fifteen deaths and thousands of injuries. The chapter examines the circumstances under which the incident occurred and the communities that were most affected by the incident. Atmospheric dispersion models are used to delineate the plume footprints of the hazardous releases in Abidjan. The generalized risk zones are then integrated into a Geographic Information Systems (GIS) to assess the environmental impacts of exposure and the demographic profile of residents within these high risk zones.
Florence M. Margai, Fatoumata B. Barry

Chapter 14. Environment and Health Inequalities of Women in Different Neighbourhoods of Metropolitan Lagos, Nigeria

Abstract
Despite all the policies evolved by the various governments in Nigeria to maintain a healthy environment, inequalities in health persist among women in Lagos. This study examines the nature of the relationship between environmental health factors and health status of women in different neighbourhoods of metropolitan Lagos. All the 17 local government areas (LGAs) were selected to achieve 100% representation. Questionnaires (no = 1,150) were administered to randomly selected women aged 18 years and above. A total of 9 Focus Group Discussions (FGDs) were held with women of same age from different neighbourhoods. Data analysis was by descriptive statistics, chi-square tests, one-way ANOVA and logistic regression. GIS was employed to show the spatial variation of health status of women across neighbourhoods. Results show that the mean of environmental diseases experienced by women varied among income neighbourhoods but while the difference in means between the low and medium income groups was highly significant at p < 0–5, that of the medium and high income groups was not. GIS highlighted the high income neighbourhood as having women in the highest health status. The more the access to pipe borne water, the lower the incidence of diarrhea (Wald = 19.125, p < 0.05) Also, diarrhea increased with age, irrespective of neighbourhood location. The FGDs identified stress as a major cause of ill health among women across neighbourhood groups. The study identified various neighbourhood environmental factors that affect the health of women. Improved environmental conditions are germane to improving the health status of women in metropolitan Lagos while emphasis is placed on attending to the stressors that affect women’s health.
Immaculata I.C. Nwokoro, Tunde S. Agbola

Chapter 15. Housing Quality and Racial Disparities in Low Birth Weight: A GIS Assessment

Abstract
Geospatial technologies such as geographic information systems (GIS) and spatial statistics allow researchers to analyze conceptually meaningful spatial datasets on environmental health topics to target interventions and generate new hypotheses for future research. This environmental health study focuses on the relationship between racial residential segregation, housing quality and value and low birth weight in the city of Flint, Michigan. A GIS was constructed with aerial imagery as the base; and maps of racial residential segregation and tax parcels -i.e., building footprints overlaid to examine the effect of maternal exposure to housing quality and value on low birth weight in these neighborhoods. Geographically weighted regression (GWR) was used to analyze these spatial datasets. The findings from this research showed that substandard and well-maintained housing were dispersed throughout the city of Flint, with a higher density of substandard housing in areas of segregation and concentrated poverty. Pregnant mothers living in well-maintained housing in racially mixed neighborhoods received some protection compared to similar mothers living in housing with minor disrepairs. This protection was not observed for mothers living in well-maintained housing in highly segregated neighborhoods, controlling for the same risk factors. GIS and spatial statistics were essential tools in this environmental health study.
Sue C. Grady

Geospatial Methods in Investigating Environmental Health

Frontmatter

Chapter 16. Participatory Mapping as a Component of Operational Malaria Vector Control in Tanzania

Abstract
Global efforts to tackle malaria have gained unprecedented momentum. However, in order to move towards the ambitious goal of eliminating and eventually eradicating malaria, existing tools must be improved and new tools developed. The City of Dar es Salaam, Tanzania, is home to the first operational community-based larviciding programme targeting malaria vectors in modern Africa. In an attempt to optimize the accuracy of the application of larvicides, a participatory mapping and monitoring approach was introduced that includes (1) community-based development of sketch maps of the target areas, and (2) verification of the sketch maps using laminated aerial photographs in the field which are later digitized and analyzed using Geographical Information Systems (GIS). The participatory mapping approach developed enables gap-free coverage of targeted areas with mosquito larval habitat control, and more equal distribution of the workload of field staff. The procedure has been tested, validated and successfully applied in 56 km2 of the city area. Currently, the approach is being scaled up to an area of about eight times that size, thus covering most of the urban area of Dar es Salaam. The procedure is simple, straightforward, replicable and at relatively low cost. It requires only minimal technical skills and equipment. In the case of Dar es Salaam, the resulting database provides a spatial resolution of administrative boundaries that is almost 50 times higher than that of previously available data. This level of detail can be very useful for a wide range of other purposes rather than merely malaria control, for example implementation of council programmes in a variety of sectors and spatially-explicit analyses for research and evaluation purposes.
Stefan Dongus, Victoria Mwakalinga, Khadija Kannady, Marcel Tanner, Gerry Killeen

Chapter 17. Revisiting Tobler’s First Law of Geography: Spatial Regression Models for Assessing Environmental Justice and Health Risk Disparities

Abstract
Multivariate regression has been used extensively to determine if race/ethnicity or socioeconomic status is related to presence of pollution sources, quantity of pollutants emitted, toxicity of emissions, and other indicators of environmental health risk. Most previous studies assume observations and error terms to be spatially independent, thus violating one of the standard regression assumptions and ignoring spatial effects that potentially lead to incorrect inferences regarding explanatory variables. This chapter focuses on the problem of spatial autocorrelation in geospatial analysis of environmental justice and explores the application of simultaneous autoregressive (SAR) models to control for spatial dependence in the data. A case study uses both traditional and SAR models to examine the distribution of cancer risk from exposure to vehicular emissions of hazardous air pollutants in the Tampa Bay MSA, Florida. Several approaches are explored to augment the standard regression equation, identify the neighborhood structure of each tract, and specify the spatial weights matrix that accounts for variations in cancer risk not predicted by explanatory variables. Results indicate that conventional regression analysis could lead to erroneous conclusions regarding the role of race/ethnicity if spatial autocorrelation is ignored, and demonstrate the potential of SAR models to improve geospatial analysis of environmental justice and health disparities.
Jayajit Chakraborty

Chapter 18. A Spatially Explicit Environmental Health Surveillance Framework for Tick-Borne Diseases

Abstract
We demonstrate how applying a spatially explicit context to an existing environmental health surveillance framework is vital for more complete surveillance of disease, and for disease prevention and intervention strategies. To illustrate this framework, we present a case study that involves estimating the risk of human exposure to Lyme disease. The spatially explicit framework divides the surveillance process into three components: hazard surveillance, exposure surveillance, and outcome surveillance. The components are used both collectively and individually, to assess risk of exposure to infected ticks. By utilizing all surveillance components, we identify different areas of risk which would not have been identified otherwise. Hazard surveillance uses maximum entropy modeling and Geographically Weighted Regression analysis to create spatial models that predict the geographic distribution of ticks in Texas. Exposure surveillance uses GIS methods to estimate the risk of human exposures to infected ticks, resulting in a map that predicts the likelihood of human-tick interactions across Texas, using LandScan 2008™ population data. Lastly, outcome surveillance uses kernel density estimation-based methods to describe and analyze the spatial patterns of tick-borne diseases, which results in a continuous map that reflects disease rates based on population location. Data for this study was obtained from the Texas Department of Health Services and the University of North Texas Health Science Center. The data includes disease data on Lyme disease from 2004 to 2008, and the tick distribution estimates are based on field collections across Texas from 2004 to 2008.
Aldo Aviña, Chetan Tiwari, Phillip Williamson, Joseph Oppong, Sam Atkinson

Chapter 19. Using Distance Decay Techniques and Household-Level Data to Explore Regional Variation in Environmental Inequality

Abstract
This chapter links individual- and household-level data from the nationally representative Panel Study of Income Dynamics (PSID) with neighborhood-level environmental hazard data derived from the Environmental Protection Agency’s (EPA) Toxics Release Inventory (TRI) in order to determine whether regional differences in environmental inequality exist at the household level. The data cover nearly every metropolitan area in the contiguous US from 1990 to 2005, we divide the contiguous US into nine regions, and we use Geographic Information System (GIS) software to weight the potential impact of each TRI facility inversely according to geographic distance. Results indicate that the existence and magnitude of environmental racial inequality, as well as the role that race, income and other household characteristics play in shaping this inequality, vary in important ways across the nine regions of the country. This has important implications for environmental inequality and public health research.
Liam Downey, Kyle Crowder

Chapter 20. Merging Satellite Measurement with Ground-Based Air Quality Monitoring Data to Assess Health Effects of Fine Particulate Matter Pollution

Abstract
Geospatial technologies have been widely used in environmental health research, including air pollution and human health. This chapter demonstrates the potential of integrating satellite air quality measurement with ground-based PM2.5 data to explore health effects of fine particulate air pollution. This study assesses the association of estimated PM2.5 concentration with chronic coronary heart disease (CCHD) mortality. Years 2003 and 2004 daily MODIS (Moderate Resolution Imaging Spectrometer) Level 2 AOD images were collated with US EPA PM2.5 data covering the conterminous USA. Pearson’s correlation analysis and geographically weighted regression (GWR) found that the relationship between PM2.5 and AOD is not spatially consistent across the conterminous states. GWR predicts well in the east and poorly in the west. The GWR model was used to derive a PM2.5 grid surface for the eastern US (RMSE = 1.67 μg/m3). A Bayesian hierarchical model found that areas with higher values of PM2.5 show high rates of CCHD mortality: \(\beta _{{\textrm{PM}}_{2.5} } \)= 0.802, posterior 95% Bayesian credible interval (CI) = (0.386, 1.225). Aerosol remote sensing and GIS spatial analyses and modelling could help fill pervasive data gaps in ground-based air quality monitoring that impede efforts to study air pollution and protect public health.
Zhiyong Hu, Johan Liebens, K. Ranga Rao

Chapter 21. Poverty Determinants of Acute Respiratory Infections in the Mapuche Population of Ninth Region of Araucanía, Chile (2000–2005): A Bayesian Approach with Time-Space Modeling

Abstract
This chapter highlights the relationship between poverty and disease among Mapuche indigenous peoples vis-à-vis the local population and ultimately, tests comparative differentials in mortality rates. First of all, we offer an overview of the destitute poverty in which Mapuche live and the consistency among all measurements including Census data, educational achievement scores and vulnerability index from school children. Although aggregate information gives a valuable and fair description of the problem, additional tests and GIS-based maps highlight the internal structures of inequalities among neighborhoods and the sharp territorial contrasts between Mapuche and non-Mapuche living conditions. GIS-based poverty maps display the territorial distributions of deprivation, whereas specific clusters of diseases are tested to verify whether such configurations are random or spatially dependent. Tobbler’s “first law of geography” is discussed and eventually tested in this section. Since the study data is longitudinal, test for autocorrelation is introduced with Bayesian time-space modelling. Conclusively, Mapuche people die at higher rates than non-Mapuches as well as show significantly higher rates of disease. Consistently, this ethnic group also represents the most impoverished and marginalized one of Chilean society, both at regional and national levels.
Flavio Rojas

Chapter 22. GIS and Atmospheric Diffusion Modeling for Assessment of Individual Exposure to Dioxins Emitted from a Municipal Solid Waste Incinerator

Abstract
The most potent dioxin congener (2,3,7,8-TCDD) is classified as a human carcinogen. Municipal solid waste incinerators (MSWI) are one of the major sources of dioxins and are therefore a cause of public concern. Blood dioxin levels are considered the best estimates of actual exposure, but they are costly and technically difficult to gather from individuals and to measure consistently. However, dioxins are good candidates for a combined GIS-modeling-based approach to simulate the ways in which they propagate in the environment, and the exposures that occur as a result. Dioxins are released into the air by a few known industrial point sources, and their environmental concentrations can therefore be estimated through plume modeling. Furthermore, they are known to be resistant to environmental and biological degradation, and accumulate in soils. We conducted a sequential epidemiologic investigation in the vicinity of a MSWI with high dioxin emission levels (Besançon, France). Contours of modeled ground-level air concentrations were used to assign a dioxin exposure category for any inhabitant of the town. Exposure accuracy was assessed through dioxin measurements from soil samples. In a mixed individual/ecological case-control study, a higher risk for non-Hodgkin lymphoma was found among individuals living in the area with the highest dioxin concentration (odds ratio 2.5, 95% confidence interval 1.4–4.5). The replication of these findings at the nationwide level added further evidence. GIS and exposure modeling can be considered innovative and appropriate for the assessment of dioxin exposure, moving from source identification to personal exposure estimates using environmental surrogates.
Jean-François Viel

Chapter 23. Synthesizing Waterborne Infection Prevalence for Comparative Analysis of Cluster Detection Methods

Abstract
When water is an important direct or indirect facilitator in the transmission of disease it is reasonable to expect that clusters of disease may occur near or along these water sources. As such, searching for water-related disease clusters can be an important part of spatial analysis process, particularly when there may be unknown spatial heterogeneities in the relationship between proximity to water and illness. We illustrate the value of using a new class of disease cluster detection methods in the spatial analysis of diseases suspected to emerge in unusual and irregular spatial patterns. Our experiment uses synthetic Schistosoma mansoni prevalence data created from information on environmental factors known to influence risk of infection. Our simulations suggest that cluster detection methods that assume circular cluster shapes are less precise in the delineation of cluster areas, even when the difference between cluster and non-cluster areas is large. We conclude that methods able to find irregularly shaped disease clusters are particularly well suited to applications in which features of the physical environment are suspected to influence risk of illness or infection.
Niko Yiannakoulias

Chapter 24. Spatiotemporal Analysis of PM2.5 Exposure in Taipei (Taiwan) by Integrating PM10 and TSP Observations

Abstract
Many studies have shown a significant association between human exposure to Particulate Matter (PM) and population health effects (premature mortality, respiratory and cardiovascular diseases, emergency room visits, and systemic inflammation). Fine PM particles (PM2.5) are believed to be more dangerous than PM10 because fine particles are easier inhaled and accumulated deeply into human lungs. Taipei is the largest city in Taiwan, where a variety of industrial and traffic emissions are continuously generated across space and time. Thus, it is crucial for health agencies to improve their understanding of spatiotemporal PM2.5 exposure of people living in Taipei city. The Bayesian Maximum Entropy (BME) theory of spatiotemporal statistics and science-based mapping provides valuable information about population exposure to PM2.5 pollution in Taipei. PM-related data (PM10, PM2.5 and Total Suspended Particles, TSP) are collected by different central and local government institutes. BME analysis introduces concepts and techniques that have a number of important features (theoretical and computational): several kinds of site-specific data and core knowledge bases are integrated that are associated with different physical scales; a variety of uncertainty sources are taken into account; non-linear, in general, PM estimators are used at unobserved locations; non-Gaussian laws are automatically incorporated; and a complete characterization of the dynamic PM distribution is obtained in terms of the probability density function at each space-time point rather than a single PM value. These BME advantages have considerable consequences as far as health risk analysis is concerned. Detailed space-time PM2.5 maps account for (i) composite space-time dependence structure of PM values, (ii) hard and soft datasets available about PM2.5, PM10 and TSP, and (iii) empirical evidence about the \( \frac{\textrm{PM}_{2.5}}{\textrm{PM}_{10}}\) and \(\frac{\textrm{PM}_{10}}{\textrm{TSP}}\) ratios. PM measures are investigated, including the fraction of fine particles that vary considerably across space-time. BME analysis properly identifies and quantifies factors that influence the spatiotemporal patterns of these measures, such as weather conditions and land use (e.g., the PM distributions in highly-developed commercial or industrial areas generally have higher fine particle fractions). Information generated by rigorous BME analysis and mapping across space-time constitutes valuable input to health management and decision-making under conditions of uncertainty.
Hwa-Lung Yu, Chih-Hsin Wang, George Christakos, Yu-Zhang Wu

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