Use of space time models to investigate the stability of patterns of disease

Environmental Health Perspectives

Volumn 116, Issue 8, 2008, Pages 1111-1119

  Abellan, Juan Jose ^a,b   Richardson, Sylvia ^a   Best, Nicky ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b CIBER EPIDEMIOLOGÍA Y SALUD PÚBLICA CIBERESP   (Spain)

Author keywords

Bayesian hierarchical models; Congenital anomalies; Disease mapping; Mixture models; Space time interactions; Stable disease patterns

Indexed keywords

ARTICLE; BAYES THEOREM; CASE STUDY; CONGENITAL MALFORMATION; DISEASE SURVEILLANCE; ENVIRONMENTAL FACTOR; EPIDEMIOLOGICAL DATA; INTERNATIONAL CLASSIFICATION OF DISEASES; MATHEMATICAL MODEL; PRIORITY JOURNAL; RISK ASSESSMENT; SENSITIVITY AND SPECIFICITY; SIMULATION; SOCIOECONOMICS; STATISTICAL DISTRIBUTION; UNITED KINGDOM; CLUSTER ANALYSIS; COMPUTER SIMULATION; CONGENITAL DISORDER; GEOGRAPHIC INFORMATION SYSTEM; HUMAN; METHODOLOGY;

BAYES THEOREM; COMPUTER SIMULATION; CONGENITAL ABNORMALITIES; ENGLAND; GEOGRAPHIC INFORMATION SYSTEMS; HUMANS; RISK ASSESSMENT; SOCIOECONOMIC FACTORS; SPACE-TIME CLUSTERING;

EID: 51249093740     PISSN: 00916765     EISSN: 15529924     Source Type: Journal    
DOI: 10.1289/ehp.10814     Document Type: Article

References (28)

1. Banerjee S, Carlin BP, Gelfand AE. 2004. Hierarchical Modeling and Analysis for Spatial Data. Boca Raton, FL:Chapman & Hall/CRC.
2. Bernardinelli L, Clayton D, Pascutto C, Montomoli C, Ghislandi M, Songini M. 1995. Bayesian analysis of space-time variation in disease risk. Stat Med 14:2433-2443.
3. Besag J, York J, Mollié A. 1991. A Bayesian image restoration with two applications in spatial statistics. Ann Inst Statist Math 43:1-59.
4. Best NG, Richardson S, Thomson A. 2005. A comparison of Bayesian spatial models for disease mapping. Stat Methods Med Res 14:35-59.
5. Boyd PA, Armstrong B, Dolk H, Botting B, Pattenden S, Abramsky L. 2005. Congenital anomaly surveillance in England - ascertainment deficiencies in the national system. BMJ 330:27-31.
6. Carstairs V, Morris R. 1989. Deprivation: explaining differences in mortality between Scotland and England and Wales. BMJ 299:886-889.
7. Elliott P, Briggs D, Morris S, de Hoogh C, Hurt C, Jensen TK, et al. 2001. Risk of adverse birth outcomes in populations living near landfill sites. BMJ 323:363-368.
8. Ferrándiz J, Abellán JJ, López A, Sanmartin P, Vanaclocha H, Zurriaga O, et al. 2002. Geographical distribution of the cardiovascular mortality in Comunidad Valenciana (Spain). In: GIS for Emergency Preparedness and Health Risk Reduction (Briggs D, Forer P, Jarup L, Stern R, eds). Dordrecht:Kluwer Academic Publishers, 267-282.
9. Gilks WR, Richardson S, Spiegelhalter D, eds. 1996. Markov Chain Monte Carlo in Practice. London:Chapman and Hall.
10. Heywood I, Cornelius S, Carver S. 1998. Introduction to Geographical Information Systems. Harlow:Addison Wesley Longman.
11. Jarup L, Best N, Toledano MB, Wakefield JC, Elliott P. 2002. Geographical epidemiology of prostate cancer in Great Britain. Int J Cancer 97:695-699.
12. Knorr-Held L. 2000. Bayesian modelling of inseparable space-time variation in disease risk. Stat Med 19:2555-2567.
13. Knorr-Held L, Besag J. 1998. Modelling risk from a disease in time and space. Stat Med 17:2045-2060.
14. Mardia K, Kent J, Bibby J. 1979. Multivariate Analysis. London:Academic Press.
15. Office for Population Censuses and Surveys. 1995. The OPCS Monitoring Scheme for Congenital Malformations: A Review by a Working Group of the Registrar General's Medical Advisory Group. Occasional Paper, 43. London, UK:Office for Population Censuses and Surveys, 5.
16. Pascutto C, Wakefield JC, Best NG, Richardson S, Bernardinelli L, Staines A, et al. 2000. Statistial issues in the analysis of disease mapping data. Stat Med 19:2493-2519.
17. Ramis-Prieto R, García-Pérez J, Pollán M, Aragonés N, Pérez-Gómez B, López-Abente G. 2007. Modelling of municipal mortality due to haematological neoplasias in Spain. J Epidemiol Community Health 61:165-171.
18. Richardson S. 2003. Spatial models in epidemiological applications. In: Highly Structured Stochastic Systems (Green PJ, Hjort NL, Richardson S, eds). New York:Oxford University Press, 237-259.
19. Richardson S, Abellan J, Best N. 2006. Bayesian spatio-temporal analysis of joint patterns of male and female lung cancer risks in Yorkshire (UK). Stat Methods Med Res 15:385-407.
20. Richardson S, Best NG, Thomson A, Elliott P. 2004. Interpreting posterior relative risk estimates in disease-mapping studies. Environ Health Perspect 112:1016-1025.
21. Richardson S, Green P. 1997. On Bayesian analysis of mixtures with an unknown number of components. J R Stat Soc Ser B 59:731-792.
22. Roberts G. 1996. Markov chain concepts related to sampling algorithms. In: Markov Chain Monte Carlo in Practice (Gilks WR, Richardson S, Spiegelhalter D, eds). London:Chapman & Hall, 49.
23. Spiegelhalter D, Thomas A, Best NG, Lunn DJ. 2003. WinBUGS Version 1.4 User's Manual. Available: http://www.mrc-bsu.cam.ac.uk/bugs/winbugs/ manual14.pdf [accessed 15 February 2008].
24. U.K. Small Area Health Statistics Unit. 2008. Home Page. Available: http://www.sahsu.org [accessed 15 February 2008].
25. Wakefield JC, Best NG, Waller L. 2000. Bayesian approaches to disease mapping. In: Spatial Epidemiology (Elliott P, Wakefield JC, Best NG, Briggs DJ, eds). Oxford:Oxford University Press, 104-127.
26. Waller LA, Carlin BP, Xia H, Gelfand AE. 1997. Hierarchical spatio-temporal mapping of disease rates. J Am Stat Assoc 92:607-617.
27. World Health Organization. 1975. International Classification of Diseases, 9th Revision. Geneva:World Health Organization.
28. World Health Organization. 1993. International Classification of Diseases, 10th Revision. Geneva:World Health Organization.