9780471986348

Disease Mapping and Risk Assessment for Public Health

by ; ; ; ; ; ;
  • ISBN13:

    9780471986348

  • ISBN10:

    0471986348

  • Format: Hardcover
  • Copyright: 1999-07-09
  • Publisher: WILEY
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Summary

Representative of the most pertinent issues within disease surveillance and mapping, this book will provide an accessible overview for statisticians and epidemiologists.

Table of Contents

Editors' Preface xiii
List of Contributors
xv
PART I: DISEASE MAPPING
Disease Mapping and Its Uses
3(12)
Introduction
3(1)
Simple statistical representation
4(4)
Model-based approaches
8(3)
Spatio-temporal modelling
11(2)
Conclusions
13(2)
Bayesian and Empirical Bayes Approaches to Disease Mapping
15(16)
Introduction
15(1)
Maximum likelihood estimation of relative risks of mortality
16(3)
Hierarchical Bayesian model of relative risks
19(5)
Empirical Bayes estimation of relative risks
24(1)
Fully Bayesian estimation of the relative risks
25(4)
Conclusion
29(2)
Addressing Multiple Goals Evaluating Region-Specific Risk Using Bayesian Methods
31(18)
Introduction
31(1)
Models
32(3)
Goals and inferences
35(3)
Using Monte-Carlo output
38(1)
Scottish lip cancer data analysis
38(7)
Conclusion
45(4)
Disease Mapping with Hidden Structures Using Mixture Models
49(14)
Introduction
49(2)
The empirical Bayes approach
51(4)
The validity of the mixture model approach for map construction
55(1)
Extensions of the mixture model approach
56(2)
Discussion and conclusions
58(1)
Appendix: Details about the program DismapWin
59(4)
PART II: CLUSTERING OF DISEASE
Inference for Extremes in Disease Mapping
63(22)
Introduction
63(1)
Spatial models for disease incidence or mortality
64(3)
Bayesian inference via simulation
67(8)
Bayes and constrained Bayes estimates
75(3)
Loss functions for extreme values
78(2)
Results for the Scotland lip-cancer data
80(5)
Edge Effects in Disease Mapping
85(14)
Introduction
85(1)
Edge effect problems
86(1)
Edge effect compensation methods
87(2)
A hierarchical Bayesian model for disease mapping of tract count data
89(3)
The Tuscany example
92(5)
Conclusions
97(2)
A Review of Cluster Detection Methods
99(12)
Introduction
99(3)
Reasons for studying disease clustering
102(2)
Definition of clusters and clustering
104(3)
Modelling issues
107(1)
Hypothesis tests for clustering
108(3)
Comparison of General Tests for Spatial Clustering
111(8)
Introduction
111(1)
Inappropriate tests
111(2)
Available tests
113(3)
Discussion
116(3)
Markov Chain Monte Carlo Methods for Putative Sources of Hazard and General Clustering
119(24)
Introduction
119(1)
Definitions
120(1)
The analysis of health risk related to pollution sources
121(1)
The analysis of non-focused disease clustering
122(1)
A general model formulation for specific clustering
123(1)
Markov chain Monte Carlo methods
124(1)
Putative hazard example
125(7)
Non-focused clustering example
132(9)
Conclusions
141(2)
Statistical Evaluation of Disease Cluster Alarms
143(8)
Introduction
143(1)
Focused cluster tests applied at other similar locations
144(1)
Post-alarm monitoring
145(1)
The spatial scan statistic
146(1)
A proactive approach
147(1)
Discussion
148(3)
Disease Clustering for Uncertain Locations
151(18)
Introduction
151(1)
Classical statistics and randomisation tests
152(1)
Cluster statistics as randomisation tests
153(1)
Sample-based randomisation tests are epidemiologically unreasonable
154(1)
Statistical inference
155(2)
Location models
157(4)
Location model applications
161(1)
Spatial randomisation
162(2)
Statistical inference for uncertain locations
164(1)
An application
164(1)
Discussion
165(4)
Empirical Studies of Cluster Detection---Different Cluster Tests in Application to German Cancer Maps
169(12)
Introduction
169(1)
Methods
170(2)
Results of application to German cancer mortality data
172(4)
Discussion
176(5)
PART III: ECOLOGICAL ANALYSIS
Introduction to Spatial Models in Ecological Analysis
181(12)
Introduction
181(1)
Ecological fallacy in spatial data
182(3)
Statistical models
185(6)
Example
191(1)
Conclusions
191(2)
Bayesian Ecological Modelling
193(10)
Introduction
193(1)
Statistical issues
194(2)
Data issues
196(3)
Problems with the interpretation of ecological regression studies
199(1)
Technical implementation
200(1)
Conclusions
200(3)
Spatial Regression Models in Epidemiological Studies
203(14)
Truncated auto-Poisson vs. random effects Poisson regression
205(3)
Model fitting using Monte Carlo Newton--Raphson
208(2)
Prostate cancer in Valencia, 1975--1980
210(4)
Discussion
214(3)
Multilevel Modelling of Area-Based Health Data
217(14)
Introduction
217(2)
Developing a Poisson spatial multilevel model
219(4)
Incidence of prostate cancer in Scottish local authority districts
223(4)
Discussion
227(4)
PART IV: RISK ASSESSMENT FOR PUTATIVE SOURCES OF HAZARD
A Review of Modelling Approaches in Health Risk Assessment around Putative Sources
231(16)
Introduction
231(2)
Problems of inference
233(1)
Exploratory techniques
234(1)
Models for point data
235(7)
Models for count data
242(2)
Modelling vs. hypothesis testing
244(1)
Conclusions
245(2)
Disease Mapping Using the Relative Risk Function Estimated from Areal Data
247(10)
Introduction
247(1)
Definition of the Relative Risk Function
248(1)
Estimation of the relative risk function
249(1)
Application to childhood cancer data
249(3)
General heterogeneity of risk
252(2)
Selecting the degree of smoothing
254(1)
Discussion
254(3)
The Power of Focused Score Tests Under Misspecified Cluster Models
257(14)
Introduction
257(1)
Models of clustering and score tests
258(3)
Homogeneous population results
261(5)
Post hoc power analysis: New York leukaemia data
266(2)
Discussion
268(3)
Case--Control Analysis of Risk around Putative Source
271(16)
Introduction
271(1)
General definitions
272(2)
Estimation
274(4)
Crude trend tests on distance from source
278(4)
Stratified analysis
282(1)
Logistic regression analysis
282(3)
Conclusions
285(2)
Lung Cancer Near Point Emission Sources
287(8)
Introduction
287(1)
Intustrial areas
288(1)
Urban areas
289(1)
Methodological implications
290(2)
Conclusions
292(3)
PART V: PUBLIC HEALTH APPLICATIONS AND CASE STUDIES
Environmental Epidemiology, Public Health Advocacy and Policy
295(6)
Introduction
295(1)
`Washing Whiter': A pitfall to avoid
296(2)
A societal context to take into account
298(1)
Conclusion
299(2)
The Character and the Public Health Implications of Ecological Analyses
301(10)
Introduction
301(1)
Some remarks on the assessment of ecological exposures
302(1)
Comment on study designs
303(1)
Credibility of ecological analyses
304(1)
Scientific aspects
305(2)
Societal attitudes
307(1)
Conclusions
308(3)
Computer Geographic Analysis: A Commentary on Its Use and Misuse in Public Health
311(10)
Introduction
311(1)
Hypothesis generation
312(4)
Ecological studies
316(1)
Descriptive/administrative uses of GIS and geographic analysis
317(1)
Hypothesis testing
318(1)
Conclusion
319(2)
Estimating the Presence and the Degree of Heterogeneity of Disease Rates
321(8)
Introduction
321(1)
The Poisson case
322(2)
Binomial case
324(2)
Discussion
326(3)
Ecological Regression with Errors in Covariates: An Application
329(20)
Introduction
329(2)
Background and data
331(2)
The statistical model
333(7)
The data
340(1)
Estimation
340(1)
Results
340(6)
Discussion
346(3)
Case Studies in Bayesian Disease Mapping for Health and Health Service Research in Ireland
349(16)
Introduction
349(1)
Background
350(2)
Low birth weight and area deprivation
352(6)
Avoidable mortality for asthma
358(5)
Conclusion
363(2)
An Analysis of Determinants of Regional Variation in Cancer Incidence: Ontario, Canada
365(18)
Introduction
365(1)
Background and objectives
366(1)
Methods
367(2)
Results
369(11)
Conclusions
380(3)
Congenital Anomalies Near Hazardous Waste Landfill Sites in Europe
383(12)
Introduction
383(1)
Methods
384(4)
Results
388(3)
Discussion
391(4)
An Analysis of the Geographical Distribution of Leukaemia Incidence in the Vicinity of a Suspected Point Source: A Case Study
395(16)
Introduction
395(1)
Materials and methods
396(5)
Results
401(5)
Discussion
406(2)
Conclusion
408(3)
Lung Cancer Mortality in Women in Germany 1995: A Case Study in Disease Mapping
411(42)
Introduction
411(1)
The data
412(1)
The methods
413(40)
Appendix: Disease Mapping and Risk Assessment for Public Health Decision Making: Report on a WHO/Biomed2 International Workshop 453(16)
Index 469

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