1. The document discusses different types of spatial analysis that can be used to analyze health data, including exploring relationships between data points, identifying clusters, and predictive modeling. 2. Specific examples are provided of spatial analyses conducted in Virginia to identify disparities in conditions like infant mortality, prostate cancer rates, and breast cancer rates across census tracts and counties. 3. Identifying clusters of high rates and disparities can help public health officials develop targeted interventions and policies to improve health equity.

1. The Spatial Analysis of Health Data Health Disparities and the Development of High Priority Target Areas September 10, 2009 Virginia Health Equity Conference Virginia Department of Health Office of Minority Health and Public Health Policy Ken Studer, PhD Rexford Anson-Dwamena, MPH

3. Surrounded by Clusters! 'Tobler's first law of geography' "everything is related to everything else, but near things are more related than distant things"

4. Double Jeopardy describes children (under 18 years old) that live in poor families and in poor neighborhoods. Poor neighborhoods are defined as census tracts (CTs) with greater than 20.0% poverty. The racial categories include persons of Hispanic and non-Hispanic origin; 'Other' includes American Indian, Alaska Native, Native Hawaiian and other Pacific Islander, some other race alone, and two or more races. **Total number of children living below the federal poverty level reflects the sum of the four racial categories since Hispanic ethnicity could not be determined for each race. Source: Census 2000, SF3, P159. Where is the Map?

5. Abraham Verghese: Urbs in Rure Verghese, A., S. Berk, and F. Sarubbi. 1989. Urbs in Rure: HIV infections in rural Tennessee. Journal of Infectious Diseases 160(6): 1051-1055.

6. Spatial Analysis of Prostate Cancer Incidence in Virginia* * Oliver, MN, E Smith, M Siadaty, FR Hauck, LW Pickle, Spatial Analysis of Prostate Cancer Incidence and Race in Virginia, 1990–1999. Am J Prev Med 2006;30(2S):S67–S76. Census Tract Level Analysis County Level Analysis

7. Source: United States Department of Agriculture: Economic Research Service, 2004 County Typologies; Census 2000, SF3-PCT25. County/Census Tract Low Education in Virginia Census Tract Level County Level

8. County/Census Tract SMR

9. Mortality Ratio by Census Tract

10. Things Change but…. …systems remain highly sensitive to initial conditions

11. Persistence of Poverty

12. 31

14. 50% Infant Mortality in Richmond Block Groups: 1990-2005

15. Percentage (yellow) of Richmond Homicides by Census Tract, 2007 Richmond, Virginia Infant Deaths by Census Block Group, 1990-2005 Thematic Map (Choropleth Map)

16. Infant Mortality Clustering

17. NOVA Infant Deaths per Census Block Group Source: VDH Vital Statistics, 1990-2005.

18. Predictive Kriging Analysis Infant Deaths by Block Group Source: VDH Vital Statistics, 1990-2005. Kernel Density Analysis Low Birth-weight Infants based on Census Tract Data with Optimum Locations for Clinics Source: VDH Vital Statistics, 1996-2005.

20. Health Disparity

21. Kernel Density Smoothed Surface

22. SaTScan Cluster Analysis

23. Cluster #1 Filter Decomposition

24. Rural Cluster #2

25. Breast Cancer Residual Analysis

26. Combined Kernel Density and Kriging Analysis—State Standard

27. Combined Kernel Density and Kriging Analysis—NOVA Standard

28. Combined Kernel Density and Kriging Analysis— Potentially Underreported Incidence

29. GeoDa Cluster Analysis

30. White Breast Cancer Rates

31. Black Breast Cancer Rates

32. Black/White Breast Cancer Disparities

33. Black/White Breast Cancer Disparities

35. Contact Information: Ken Studer, PhD [email_address] Rexford Anson-Dwamena, MPH rexford.dwamena @vdh.virginia.gov