Spatial Analysis of Attrition Along the HIV Care Continuum in the Atlanta Metropolitan Area Open Access
Huylebroeck, Brian (2015)
Context Proper HIV management and prevention requires adherence to the HIV Care Continuum steps, which consist of diagnosis, linkage to care, retention in care, initiation of antiretroviral therapy, and achievement of viral suppression. Using spatial analysis to detect geographic hot spots of attrition from these steps may serve to identify how best to control the HIV epidemic.
Objective: To identify and describe geographic areas associated with poor engagement in HIV care in the metro-Atlanta area.
Design, Setting, and Participants: Surveillance data was extracted from Georgia Enhanced HIV/AIDS Reporting System for a retrospective cohort of persons diagnosed with HIV in 2010 and 2011 in Fulton, DeKalb, Gwinnett, Clayton, Douglas, and Cobb counties in Georgia, with follow-up to 2013 (n=2339). Spatial patterns of outcomes due to attrition along the HIV Care Continuum were analyzed using Hot Spot Analysis (Getis-Ord Gi*) in ArcGIS to identify geographic areas of significant, non-random clustering, known as hot spots. Logistic regression models were used to evaluate associations among hot spots, demographic factors, and each outcome.
Outcome Measurements: Outcomes of interest were: not linked to care, not linked to care within 90 days, not retained in care, and not virally suppressed.
Results: Of the 2339 persons in the sample, 2067 persons (88.4%) linked to care; 1295 persons (62.6%) linked to care within 90 days among those linked; 663 persons (32.1%) were retained in care among those linked; 326 persons (49.2%) were virally suppressed among those retained. Persons currently residing in geographic hot spots had higher odds to not link to care [adjusted odds ratio (AOR): 1.51 (95% confidence interval (CI) 1.04-2.21)], not link to care within 90 days [2.73 (1.28-5.83)], not retain in care [2.47 (1.43-4.26)], and not achieve viral suppression [2.72 (1.56-4.76)] than persons residing outside of hot spots in the follow-up period.
Conclusion: Spatial patterns associated with clustering of poor outcomes were found to be strong independent predictors of linkage to care, retention in care, and viral suppression in a 6-county section of the metro-Atlanta area. The findings provide further evidence for the use of spatial analyses as a tool for characterizing the HIV Care Continuum.
Table of Contents
I. Background. 1
II. Manuscript Abstract. 9
Table 1. Characteristics of Persons Diagnosed With HIV Infection in Metropolitan Atlanta by Inclusion in the Analysis Sample, 2010-2011.
Table 2. Engagement at Each Step of the HIV Care Continuum among a Sample of Persons Diagnosed with HIV Infection in Metropolitan Atlanta by Select Characteristics, 2010-2011.
Table 3. Multivariable Logistic Models of Engagement at Each Step of the HIV Care Continuum for a Sample of Persons Diagnosed with HIV Infection in Metropolitan Atlanta, 2010-2011.
Figure 1. Reference map of the Atlanta metropolitan area.
Figure 2. Kernel Density of Persons Diagnosed with HIV in Metro-Atlanta, 2010-2011.
Figure 3. Geographic Distribution of Major HIV/AIDS Medical Care Providers in Metro-Atlanta.
Figure 4. Geographic Hot Spots Associated with Not Linking to Care in Metro-Atlanta, 2010-2011.
Figure 5. Geographic Hot Spots Associated with Not Linking to Care within 90 Days in Metro-Atlanta, 2010-2011.
Figure 6. Geographic Hot Spots Associated with Not Retaining in Care in Metro-Atlanta, 2010-2011.
Figure 7. Geographic Hot Spots Associated with Not Achieving Viral Suppression in Metro-Atlanta, 2010-2011.
III. Summary, Public Health Implications, Possible Future Directions. 41
Appendix A. SAS Code for Sample Selection, Variable Creation, and Data Extraction.
Appendix B. SAS Code for Multivariable Logistic Regression Models.
About this Master's Thesis
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