Spatial Epidemiological Approaches in Disease Mapping and Analysis

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  • Edition: 1st
  • Format: Hardcover
  • Copyright: 2008-08-18
  • Publisher: CRC Press

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Captures the Complexity of GIS for the Non-Specialist in a Ready-To-Implement WayUse of GIS applications in the medical community is not a new concept by any means. But, the ability to apply GIS technology on a wide scale is often hampered by the sophistication and complexity of the methodology and the limited access to affordable software. Spatial Epidemiological Approaches in Disease Mapping and Analysis illustrates the utilities of freeware using real-world data and leads users down the logical decision-making path toward developing spatial-statistical relationships.Wide-Ranging Overview of GIS Applications to Contemporary Health ProblemsThis internationally reputable guide brings instructional clarity to its treatment of spatial-statistical techniques, subjecting epidemiological data to statistical rigor and advanced methodological testing. With the help of a vivid color insert, this book illustrates the applications of GIS inexamining non-contagious (asthma and dengue) and contagious (SARS) diseases, making it applicable to any public health condition on any scale.  This landmark work follows a truly interdisciplinary model, capturing the complexity of GIS for the non-specialist in a ready-to-implement way and spotlighting the global challenge of analyzing public health concerns in a geographical context.

Table of Contents

Forewordp. ix
Forewordp. xi
Prefacep. xiii
Acknowledgmentsp. xv
Authorsp. xvii
List of Acronymsp. xix
GIS Concepts and Operationsp. 1
What Is a GIS?p. 1
What a GIS Is Notp. 2
GIS Components and Functionalitiesp. 3
Datap. 5
Equipmentp. 6
Methodsp. 7
Peoplep. 7
Organizationp. 8
Basic GIS Operationsp. 9
Summaryp. 11
Referencesp. 12
GIS and Geographic Datap. 15
Characteristics of Geographic Datap. 15
Topological Relationsp. 17
GIS Models: Raster versus Vectorp. 19
Rasterp. 21
Vectorp. 22
Attributep. 22
Data for Spatial Epidemiological Studiesp. 23
Georeferencing Locational Informationp. 25
Geocoding Problemsp. 27
Choosing the Right Addressp. 29
Aggregating Geographic Datap. 29
Units of Aggregationp. 30
Data Aggregation Concernsp. 30
Summaryp. 33
Referencesp. 33
Spatial Analysis Software and Methodsp. 35
Introductionp. 35
Softwarep. 35
CrimeStatp. 36
GeoDap. 36
HealthMapperp. 37
Summaryp. 38
Data Setsp. 40
Spatial Analysisp. 41
Age-Sex Standardizationp. 43
Disease Mappingp. 44
Spatial Autocorrelationp. 47
Geostatistical Analysisp. 48
Summaryp. 49
Referencesp. 49
Point Pattern Methods of Disease Analysisp. 51
Examining Point Patternsp. 51
Elementary Analysis of Disease Data by Visualizationp. 53
Examining the SARS Data Filep. 53
Reading Point Data into GeoDap. 53
Adding a Base Map in GeoDap. 54
Linking Interactively the Map and Its Disease Attribute Tablep. 56
Displaying Disease Locations as Proportional Point Symbolsp. 56
Cluster Analysis: Nearest Neighbor Distancep. 58
Setting Up a Workspace in CrimeStatp. 58
Specifying Input Datap. 58
Specifying Measurement Parameters and Computing NNIp. 59
Examining Local Patternsp. 61
Contextual Analysisp. 63
Setting Up a Workspace in CrimeStatp. 63
Specifying Input Datap. 63
Specifying Measurement Parameters and Computing SDEp. 64
Displaying SDE Using the HealthMapperp. 64
Constraints and Limitationsp. 66
Summaryp. 69
Referencesp. 69
Areal Methods of Disease Analysisp. 71
Areal Pattern Analysisp. 71
Areal Mappingp. 72
Disease Ratesp. 72
Rate Smoothing Techniquesp. 74
The Empirical Bayes Smoothing Methodp. 74
The Spatial Empirical Bayes Smoothing Methodp. 74
Constraints and Limitations of Choropleth Mappingp. 79
Data Classification in Choropleth Mapsp. 79
Modifiable Areal Unit and Area Dependence Problemsp. 83
Spatial Dependencep. 84
Measures of Spatial Autocorrelationp. 85
Spatial Autocorrelation Analysis with GeoDap. 86
Examining the Dengue Data Filep. 86
Constructing Spatial Weightsp. 88
Examining Characteristics of Spatial Weightsp. 89
Constructing Spatially Lagged Variablesp. 89
Visualizing the Moran Scatterplotp. 90
Assessing Statistical Significance of Moran's Ip. 91
Compiling Univariate LISAp. 91
Summaryp. 92
Referencesp. 93
Interpolation and Associative Analysisp. 95
Spatial Sampling and Interpolationp. 95
Kernel Density Estimationp. 96
Kernel Density Estimation of Asthma Occurrences in Hong Kongp. 98
Setting Up a Workspace in CrimeStatp. 98
Specifying Input Datap. 98
Specifying Grid Referencep. 98
Kernel Density Estimationp. 100
Displaying Results of Kernel Density Estimationp. 100
Constraints and Limitations of the Kernel Density Methodp. 102
Spatial Interpolation Methodsp. 103
IDW and Its Constraintsp. 104
Spline and Its Constraintsp. 104
Kriging (Ordinary or Universal) and Its Constraintsp. 105
Spatial Interpolation of Air Pollution Index (API) of Hong Kongp. 106
Associate Analysisp. 108
Application of Interpolated Surface in Associate Analysis: The Risk of Asthma Relative to API of Hong Kongp. 109
Application of Socioeconomic Data in Associate Analysis: Risk of Asthma Relative to Monthly Household Income of the Population of Hong Kongp. 112
Summaryp. 116
Referencesp. 117
Initiating a GIS Project in Spatial Epidemiologyp. 121
Introductionp. 121
Setting Up a GIS Infrastructurep. 122
Conceptualizing a GIS Projectp. 124
Determining the Focus of a GIS Developmentp. 125
Conceptualizing a GIS Applicationp. 125
Signs of an Unfeasible Projectp. 133
Summaryp. 136
Referencesp. 136
Current GIS Research in Health Care and Disease Analysesp. 139
Geography of Healthp. 139
Health Outcomes and Epidemiological Studiesp. 140
Health Care Delivery Applicationsp. 141
Health Care Commissioning and Needs Assessmentp. 142
Contagious versus Noncontagious Disease Analysesp. 143
Short-Term versus Long-Term Surveillance and Disease Trackingp. 145
Summaryp. 147
Referencesp. 148
List of GIS Softwarep. 153
Data Descriptionp. 155
Data Preparation in Microsoft Excelp. 163
Useful Web Referencesp. 167
Overviews and Guides to GISp. 167
Web-Based Tools for Public Health and Data Analysisp. 167
Indexp. 169
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