Conceptual and practical issues in the detection of local disease clusters: A study of mortality in Hamilton, Ontario

Canadian Geographer

Volumn 46, Issue 2, 2002, Pages 160-171

  Burra, Tara ^a   Jerrett, Michael ^a   Burnett, Richard T ^a   Anderson, Mark ^a  

^a MCMASTER UNIVERSITY   (Canada)

Author keywords

Cluster analysis; Geocoding; GIS; Hamilton; Local spatial statistics

Indexed keywords

CLUSTER ANALYSIS; MORTALITY; PUBLIC HEALTH; STATISTICAL ANALYSIS;

CANADA;

EID: 0036623421     PISSN: 00083658     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1541-0064.2002.tb00737.x     Document Type: Article

References (69)

1. Local indicators of spatial association-LISA
2. Exploratory spatial data analysis linking spaceStat and ArcView
3. The choice of test for detecting raised disease risk near a point source
4. Spatial analysis of the association between particulate air pollution and mortality in Hamilton, Canada
5. Guidelines for investigating clusters of health events
6. Geocoding and linking data from population-based surveillance and the US census to evaluate the impact of median household income on the epidemiology of invasive Streptococcus pneumoniae infections
7. On epidemiology and geographic information systems: A review and discussion of future directions
8. Locational uncertainty in geo-referencing public health datasets
9. A point process modelling approach to raised incidence of a rare phenomenon in the vicinity of a prespecified point
10. Evaluating cancer clusters
11. Exploratory spatial data analysis and GIS
12. Local forms of spatial analysis
13. The geography of parameter space: An investigation into spatial non-stationarity
14. GIS and spatial analytical problems
15. Spatial point pattern analysis and its application in geographical epidemiology
16. The uses of spatial analysis in medical geography: A review
17. Spatial statistics
18. The analysis of spatial association by distance statistics
19. Local spatial statistics: An overview
20. Spatial autocorrelation
21. Randomization, statistics, and causal inference
22. Geographical aspects of the emergence of infectious diseases
23. Exploratory spatial data analysis in a geographic information system environment
24. Dynamic graphics for exploring spatial data with applications to locating global and local anomalies
25. Childhood leukemia in Sweden: Using GIS and a spatial scan statistic for cluster detection
26. The analysis of disease clusters Part 1: State of the art
27. The analysis of disease clusters Part 2: Introduction to techniques
28. Air pollution, environmental equity and health: TSRI research program (Toxic substances Research Initiative 1999-2002)
29. A GIS-environmental justice analysis of particulate air pollution in Hamilton, Canada
30. Contingency, realism, and the expansion method
31. Detection of clusters
32. Spatial scan statistics: Models, calculations, and applications
33. Visualizing georeferenced data: Representing reliability of health statistics
34. A review of methods for the statistical analysis of spatial patterns of disease
35. Thalidomide and congenital abnormalities
36. Spatial analytical methods and geographic information systems: Use in health research and epidemiology
37. The modifiable areal unit problem
38. Using a geographical analysis machine to detect the presence of spatial clustering and the location of clusters in synthetic data
39. Local spatial autocorrelation statistics: Distributional issues and an application
40. A sobering start for the Cluster Busters' conference
41. Practical implications of models of statistical inference for causal effects and the critical role of the assignment mechanism
42. Improving the geographic basis of health surveillance using GIS
43. Monitoring for clusters of disease: Application to leukemia incidence in upstate New York
44. Exploring spatial data analysis with local statistics
45. Spatial pattern analyses to detect rare disease clusters
46. The analysis of regional patterns in health data: 1. Distributional considerations
47. Solving the cluster puzzle; clues to follow and pitfalls to avoid
48. Characterizing cluster studies: A review of the literature
49. Geocoding Issues when adding socioeconomic and spatial dimensions to health data, based on small-area geographic coding