Journal of Urban Health

, Volume 88, Issue 1, pp 129–141 | Cite as

Spatial Clustering of HIV Prevalence in Atlanta, Georgia and Population Characteristics Associated with Case Concentrations

  • Brooke A. Hixson
  • Saad B. Omer
  • Carlos del Rio
  • Paula M. FrewEmail author


We assessed prevalent HIV cases in Atlanta to examine case distribution trends and population characteristics at the census tract level that may be associated with clustering effects. We calculated cluster characteristics (area and internal HIV prevalence) via Kuldorff's spatial scan method. Subsequent logistic regression analyses were performed to analyze sociodemographics associated with inclusion in a cluster. Organizations offering voluntary HIV testing and counseling services were identified and we assessed average travel time to access these services. One large cluster centralized in downtown Atlanta was identified that contains 60% of prevalent HIV cases. The prevalence rate within the cluster was 1.34% compared to 0.32% outside the cluster. Clustered tracts were associated with higher levels of poverty (OR = 1.19), lower density of multi-racial residents (OR = 1.85), injection drug use (OR = 1.99), men having sex with men (OR = 3.01), and men having sex with men and IV drug use (OR = 1.6). Forty-two percent (N = 11) of identified HIV service providers in Atlanta are located in the cluster with an average travel time of 13 minutes via car to access these services (SD = 9.24). The HIV epidemic in Atlanta is concentrated in one large cluster characterized by poverty, men who have sex with men (MSM), and IV drug usage. Prevention efforts targeted to the population living in this area as well as efforts to address the specific needs of these populations may be most beneficial in curtailing the epidemic within the identified cluster.


HIV/AIDS HIV prevalence Spatial cluster detection Geographic mapping 



We thank Jennifer Taussig, Richard Dunville, and the HIV Epidemiology Unit at the Georgia Department of Community Health for assistance with data preparation. We also thank Emily McCollum for her valuable assistance reviewing the manuscript. Special thanks to our partner agencies for their support of this study including AID Atlanta, National AIDS Education and Services for Minorities (NAESM), SisterLove, Someone Cares, and Stand, Inc.

Sources of Support

This study was supported by the Emory Center for AIDS Research (P30 AI050409), Global Health Institute, the Emory Vaccine Center (U19 AI057266), and the Emory HIV/AIDS Clinical Trials Unit (U01 AI069418).


  1. 1.
    Centers for Disease Control and Prevention. New HIV Incidence Estimates: CDC Responds. CDC HIV/AIDS Facts. 2008.
  2. 2.
    Bautista CT, Sateren WB, Sanchez JL, Singer DE, Scott P. Geographic mapping of HIV infection among civilian applicants for United States military service. Health Place. 2008; 14(3): 608–615.CrossRefPubMedGoogle Scholar
  3. 3.
    Southern States AIDS Directors Work Group. Southern States Manifesto: Update 2008. HIV/AIDS and Sexually Transmitted Diseases in the South. Accessed February 16, 2010.
  4. 4.
    Reif S, Geonnotti K, Whetten K. HIV infection and AIDS in the Deep South. Am J Public Health. 2006; 96(6): 970–973.CrossRefPubMedGoogle Scholar
  5. 5.
    Georgia Department of Human Resources. 2007 Georgia HIV/AIDS Surveillance Summary. Accessed on November 29, 2009.
  6. 6.
    Kaiser State Health Facts. Georgia: HIV Infection Cases Reported among States with Confidential Name-Based Reporting. 2007.
  7. 7.
    Georgia Community Planning Group and Georgia Division of Health. Comprehensive HIV Prevention Plan 2009–2013, 2008.
  8. 8.
    Priddy FH, Pilcher CD, Moore RH, et al. Detection of acute HIV infections in an urban HIV counseling and testing population in the United States. J Acquir Immune Defic Syndr. 2007; 44(2): 196–202.CrossRefPubMedGoogle Scholar
  9. 9.
    State of Georgia Department of Human Resources. The Georgia HIV/AIDS Epidemic. Atlanta, GA; 2008.Google Scholar
  10. 10.
    US Census Bureau—Population Division. Annual Estimates of the Population of Metropolitan and Micropolitan Statistical Areas: April 1, 2000 to July 1, 2008 (CBSA-EST2008-01). Published in 2009. Accessed on July 25, 2010.
  11. 11.
    US Census Bureau. Atlanta city, Georgia: ACS Demographic and Housing Estimates: 2006–2008. Published in 2009. Accessed on July 25, 2010.
  12. 12.
    US Census Bureau. Atlanta city, Georgia: Selected Economic Characteristics: 2006-2008. Published in 2009. Accessed on July 25, 2010.
  13. 13.
    US Census Bureau. Atlanta city, Georgia: Selected Social Characteristics in the United States: 2006-2008. Published in 2009. Accessed on July 25, 2010.
  14. 14.
    Vermund SH, Hodder SL, Justman JE, et al. Addressing research priorities for prevention of HIV infection in the United States. Clin Infect Dis. 2010; 50(Suppl 3): S149–S155.CrossRefPubMedGoogle Scholar
  15. 15.
    Geanuracos CG, Cunningham SD, Weiss G, Forte D, Reid LM, Ellen JM. Use of geographic information systems for planning HIV prevention interventions for high-risk youths. Am J Public Health. 2007; 97(11): 1974–1981.CrossRefPubMedGoogle Scholar
  16. 16.
    Chutuape KS, Ziff M, Auerswald C, Castillo M, McFadden A, Ellen J. Examining differences in types and location of recruitment venues for young males and females from urban neighborhoods: findings from a multi-site HIV prevention study. J Urban Health. 2009; 86(1): 31–42.CrossRefPubMedGoogle Scholar
  17. 17.
    Weir SS, Pailman C, Mahlalela X, Coetzee N, Meidany F, Boerma JT. From people to places: focusing AIDS prevention efforts where it matters most. AIDS. 2003; 17(6): 895–903.CrossRefPubMedGoogle Scholar
  18. 18.
    Wohl DA, Khan MR, Tisdale C, et al. Locating the places people meet new sexual partners in a southern US City to inform HIV/STI prevention and testing efforts. [published online ahead of print July 8, 2010]. AIDS Behav. Jul 8 2010. doi: 10.1007/s10461-010-9746-4.
  19. 19.
    Haan M, Kaplan GA, Camacho T. Poverty and health. Prospective evidence from the Alameda County Study. Am J Epidemiol. 1987; 125(6): 989–998.PubMedGoogle Scholar
  20. 20.
    Waitzman NJ, Smith KR. Phantom of the area: poverty-area residence and mortality in the United States. Am J Public Health. 1998; 88(6): 973–976.CrossRefPubMedGoogle Scholar
  21. 21.
    Forna FM, Fitzpatrick L, Adimora AA, et al. A case-control study of factors associated with HIV infection among black women. J Natl Med Assoc. 2006; 98(11): 1798–1804.PubMedGoogle Scholar
  22. 22.
    Denning P, DiNenno, E. Communities in crisis: is there a generalized HIV epidemic in improverished urban areas of the United States? Paper presented at: International AIDS Conference; 21 July 2010; Vienna.Google Scholar
  23. 23.
    US Census Bureau. USA State and County QuickFacts. Accessed on April 21, 2010.
  24. 24.
    US Census Bureau. Glossary of basic geographic and related terms—census 2000. Washington, DC: US Census Bureau; 2001.Google Scholar
  25. 25.
    Coulton CJ, Korbin J, Chan T, Su M. Mapping residents’ perceptions of neighborhood boundaries: a methodological note. Am J Community Psychol. 2001; 29(2): 371–383.CrossRefPubMedGoogle Scholar
  26. 26.
    Gehlke CE, Biel K. Certain effects of grouping upon the size of the correlation coefficient in census tract material. J Am Stat Assoc. 1934; 29(185A): 169–170.CrossRefGoogle Scholar
  27. 27.
    Omer SB, Enger KS, Moulton LH, Halsey NA, Stokley S, Salmon DA. Geographic clustering of nonmedical exemptions to school immunization requirements and associations with geographic clustering of pertussis. Am J Epidemiol. 2008; 168(12): 1389–1396.CrossRefPubMedGoogle Scholar
  28. 28.
    Kulldorff M, Nagarwalla N. Spatial disease clusters: detection and inference. Stat Med. 1995; 14(8): 799–810.CrossRefPubMedGoogle Scholar
  29. 29.
    Huang L, Pickle LW, Das B. Evaluating spatial methods for investigating global clustering and cluster detection of cancer cases. Stat Med. 2008; 27(25): 5111–5142.CrossRefPubMedGoogle Scholar
  30. 30.
    Chiu YW, Hsu CE, Wang MQ, Nkhoma ET. Examining geographic and temporal variations of AIDS mortality: evidence of racial disparities. J Natl Med Assoc. 2008; 100(7): 788–796.PubMedGoogle Scholar
  31. 31.
    Huang L, Stinchcomb DG, Pickle LW, Dill J, Berrigan D. Identifying clusters of active transportation using spatial scan statistics. Am J Prev Med. 2009; 37(2): 157–166.CrossRefPubMedGoogle Scholar
  32. 32.
    Kulldorff M, Feuer EJ, Miller BA, Freedman LS. Breast cancer clusters in the northeast United States: a geographic analysis. Am J Epidemiol. 1997; 146(2): 161–170.PubMedGoogle Scholar
  33. 33.
    Kulldorff M, Mostashari F, Duczmal L, Katherine Yih W, Kleinman K, Platt R. Multivariate scan statistics for disease surveillance. Stat Med. 2007; 26(8): 1824–1833.CrossRefPubMedGoogle Scholar
  34. 34.
    Mostashari F, Kulldorff M, Hartman JJ, Miller JR, Kulasekera V. Dead bird clusters as an early warning system for West Nile virus activity. Emerg Infect Dis. 2003; 9(6): 641–646.PubMedGoogle Scholar
  35. 35.
    Heffernan R, Mostashari F, Das D, Karpati A, Kulldorff M, Weiss D. Syndromic surveillance in public health practice, New York City. Emerg Infect Dis. 2004; 10(5): 858–864.PubMedGoogle Scholar
  36. 36.
    Kulldorff M. A spatial scan statistic. Commun Stat Theory Methods. 1997; 26(6): 1481–1496.CrossRefGoogle Scholar
  37. 37.
    Wallace RG. AIDS in the HAART era: New York’s heterogeneous geography. Soc Sci Med. 2003; 56(6): 1155–1171.CrossRefPubMedGoogle Scholar
  38. 38.
    Law DC, Serre ML, Christakos G, Leone PA, Miller WC. Spatial analysis and mapping of sexually transmitted diseases to optimise intervention and prevention strategies. Sex Transm Infect. 2004; 80(4): 294–299.CrossRefPubMedGoogle Scholar
  39. 39.
    Greenbaum SD, Greenbaum PE. The ecology of social networks in four urban neighborhoods. Soc Netw. 1985; 7(1): 47–76.CrossRefGoogle Scholar
  40. 40.
    Huckfeldt RR. Social contexts, social networks, and urban neighborhoods: environmental constraints on friendship choice. AJS. 1983; 89(3): 651–669.CrossRefGoogle Scholar
  41. 41.
    Friedman SR, Flom PL, Kottiri BJ, et al. Consistent condom use in the heterosexual relationships of young adults who live in a high-HIV-risk neighbourhood and do not use “hard drugs”. AIDS Care. 2001; 13(3): 285–296.CrossRefPubMedGoogle Scholar
  42. 42.
    Rhodes T, Singer M, Bourgois P, Friedman SR, Strathdee SA. The social structural production of HIV risk among injecting drug users. Soc Sci Med. 2005; 61(5): 1026–1044.CrossRefPubMedGoogle Scholar
  43. 43.
    World Health Organization and UNAIDS. Initiating Second Generation HIV Surveillance Systems: Practical Guidelines. (WHO/HIV/2002.17); 2002.Google Scholar
  44. 44.
    HIV/AIDS Epidemiology Annual Report: San Francisco Department of Public Health; 2008.Google Scholar
  45. 45.
    Geographic distribution of HIV/AIDS across King County. Seattle, WA: Public Health–Seattle & King County; 2008.Google Scholar
  46. 46.
    Kellerman SE, Lehman JS, Lansky A, et al. HIV testing within at-risk populations in the United States and the reasons for seeking or avoiding HIV testing. J Acquir Immune Defic Syndr. 2002; 31(2): 202–210.PubMedGoogle Scholar

Copyright information

© The New York Academy of Medicine 2011

Authors and Affiliations

  • Brooke A. Hixson
    • 1
    • 2
  • Saad B. Omer
    • 2
  • Carlos del Rio
    • 1
    • 2
    • 3
  • Paula M. Frew
    • 1
    • 2
    • 3
    Email author
  1. 1.The Hope Clinic of the Emory Vaccine CenterDecaturUSA
  2. 2.Departments of Global Health and Behavioral Sciences and Health Education, Rollins School of Public HealthEmory UniversityAtlantaUSA
  3. 3.Department of Medicine, Division of Infectious DiseasesEmory University School of MedicineAtlantaUSA

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