THE GEOGRAPHY OF DISEASE
Chapter 1 Methodological Context 1 11 A systemic approach to health 1 12 Risk and public health 5 13 Epidemiology 9 14 Health geography 10 15 Spatial analysis for epidemiology and health geography 11 16 Geographic information systems 16 17 Book structure 18 Chapter 2 Spatial Analysis of Health Phenomena: General Principles 21 21 Spatial analysis in epidemiology and health geography 21 211 Spatial distribution of a health phenomenon 21 212 Spatial analysis in epidemiology 23 213 Spatial and statistical dependence 28 214 Causal relationships, explanatory factors, confounding factors 29 215 Uncertainty in event localization 30 216 Health data are often aggregated into geographical units 30 22 Spatial analysis terminology and formalism 32 221 Objects, attributes, events 33 222 Localization and spatial domain 34 223 The formalism of descriptive analysis 36 224 The formalism of the explanatory analysis 39 23 General approach of spatial analysis in epidemiology 42 231 The approach of descriptive analysis 42 232 The approach of explanatory analysis 44 233 Spatial analysis methods 45 234 Spatial analysis and health geography 46 24 Required knowledge on epidemiology and statistics 47 241 Epidemiology 47 242 Statistical analysis 48 243 Methods for model adjustment 52 244 Several distributions and models 58 Chapter 3 Spatial Data in Health 63 31 Introduction 63 32 Health data 64 321 Various types of data for individuals 64 322 Individual and aggregated health data 65 323 Description of the healthcare system 66 33 Spatialization of epidemiological data 66 331 Localization in space 66 332 Localization in time 68 333 Localization in time and space 68 334 Data aggregated according to a spatial criterion 68 335 Ethics and localization 69 34 Sources of data 70 341 Epidemiological data 70 342 Geographical and environmental data 71 343 Access to geographical data 72 Chapter 4 Cartographic Representations and Synthesis Tools 75 41 Introduction 75 411 Why use mapping methods? 75 412 How to use mapping? 76 42 Cartographic representations 78 421 Mapping events or health status 78 422 Mapping rates: prevalence, incidence, risk and odds ratio 78 423 Mapping flows and spatial relationships 82 424 Mapping limitations 83 425 Mapping rate significance 89 426 Rate adjustment 90 43 Descriptive statistics and visual synthesis tools 93 431 Average points, median points 93 432 Standard deviational ellipses 95 44 Interpolations and trend surfaces 97 441 Interpolations and continuous representation 97 442 Directions and gradients 103 443 Anamorphoses 103 45 Spatio-temporal animations 104 451 What and how 104 452 Animated mapping 105 Chapter 5 Spatial Distribution Analysis 109 51 Introduction 109 511 “Direct” methods for spatial analysis 109 512 Continuous space, point pattern, subsets 113 52 Global spatial analyses 115 521 Geographical location, extent, orientation 115 522 Centrality 118 523 Spatial dependence of values 120 524 Bivariate spatial analysis 133 525 Global pattern of the phenomenon and search for a geometric model 138 53 Local spatial analyses 139 531 Local indicators of spatial association (LISA) 140 532 Spatial scan-based search for singularities 145 533 Analyses around a source point 151 54 Example: emergence and diffusion of avian influenza 153 541 Introduction 153 542 Mapping 155 543 Analysis of the spatial distribution of cases 157 544 Spatio-temporal analyses 165 545 Analyses of risk factors 172 Chapter 6 Spatial Analysis of Risk 177 61 Introduction 177 62 Aggregation-based spatial analyses 177 621 Spatial aggregation operation 179 622 Statistical analysis 183 623 Spatial analysis of aggregation 195 624 Spatial belonging 198 63 Statistical modeling of spatial data 198 631 Statistical correlations and spatial relationships 199 632 Statistical modeling 200 633 Spatial models 201 634 Spatial heterogeneity of parameters 204 64 An example: analysis of tuberculosis risk factors 207 641 Epidemiological and socio-economic data 208 642 Analysis of the statistical and spatial distribution of rates 209 643 Statistical modeling of SMR and incidence 213 Chapter 7 Space–time Analyses and Modeling 219 71 Time–distance relationships 219 72 Mobile mean points 220 73 Spatio-temporal autocorrelation and clusters 222 731 Global spatio-temporal autocorrelation 222 732 Local spatio-temporal autocorrelation 222 733 Spatio-temporal clusters 222 734 Statistical modeling: GTWR 223 74 Emergence, diffusion, pathway 224 75 Spatio-temporal modeling of health phenomena 226 751 Process modeling and simulation 226 752 The deterministic approach of SEIR models 229 753 SEIR models and localization 231 754 Non-deterministic approach of multi-agent models 232