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1Spatial Analysis of HIV and STD Disease BurdenMike Janson, MPHChief, Research & Evaluation DivisionOffice of AIDS Programs and Policy2HIV Prevention Strategy Where should we focus our prevention efforts to make the largest impact with resources we have?Assessing effective interventions tell us which strategies will make the most impact3Spatial Analysis BackgroundServices historically prioritized by Service Planning Area (SPA)Disease burden geographical differences are not explained by SPA boundariesThe use of GIS allows for small-area analysis and spatial epidemiological techniquesRecent agreements to share HIV and STD case data have allowed for a more accurate picture of overall HIV/STD disease burden4Spatial Analysis BackgroundOpportunity to examine disease burden without regard to arbitrary boundariesAnalysis conducted without preconceived ideas about where clusters would occur related to SPAs

Service Planning Areas (SPAs)5

HIV Positivity Rates by Service Planning Area (SPA), 2007Source: HIRS, Calendar Year 2007

6This is an optional map slide. This map shows New Positivity HIV Rates by Service Planning Area for Calendar Year 2007.7SPA Planning ModelAssumes that burden of disease is fairly equal across the area of a given SPA

HIV Case Density, 2009, SPA 8

Very Low DensityVery High DensitySource: 2009 New HIV Cases, HIV Epidemiology Program89Syndemic Planning ModelFocuses on connections among cofactors of diseaseConsiders those connections when developing health policiesAligns with other avenues of social change to assure the conditions in which all people can be healthy. Two or more afflictions, interacting synergistically, contributing to excess burden of disease in a populationLinked epidemics, interacting epidemics, connected epidemics, co-occurring epidemics, co-morbidities, and clusters of health-related crises910Syndemic Spatial AnalysisAnalyze spatial relationships between multiple co-occurring epidemicsHIVSyphilisGonorrheaHepatitisTwo or more afflictions, interacting synergistically, contributing to excess burden of disease in a populationLinked epidemics, interacting epidemics, connected epidemics, co-occurring epidemics, co-morbidities, and clusters of health-related crises1011Data SourcesTwo or more afflictions, interacting synergistically, contributing to excess burden of disease in a populationLinked epidemics, interacting epidemics, connected epidemics, co-occurring epidemics, co-morbidities, and clusters of health-related crises11122009 New HIV Cases2,036 HIV cases1,858 (91.2%) provided some type of residence address1,731 (93.2% match rate) could be geocoded to exact location127 (6.8%) could be geocoded to the zip code centroid (included homeless and those who gave a PO Box)Exact location cases were included in the cluster analysisCentroid cases were not included in the preliminary analysis

132009 STD CasesSyphilis2,641 cases geocoded by residence address1,042 (39.5%) reported HIV co-infection (self-report)1,597 (60.5%) reported no HIV2 cases had missing HIV resultsGonorrhea7,918 geocoded by residence addressNo HIV results available for this analysis

14Cluster Analysis MethodologyAssess spatial distributions of HIV and STD casesAverage Nearest Neighbor (ANN) statisticCalculates actual mean distance between cases and compares that mean to a hypothetical random distributionStatistic used to describe the variation in spatial data

Are cases clustered or dispersed???15

HIV Case Distribution,200916

Syphilis CaseDistribution17

Gonorrhea Spatial Distribution18Cluster Analysis MethodologyConclude that HIV and STD cases are clustered and that the clusters can not be explained by chanceSpatial characteristics are a factor in HIV and STD cases

Identify and locate clusters19Cluster Analysis MethodologyNearest Neighbor Hierarchical Clustering (Nnh)Used when geographical characteristics are believed to be relevant to the health outcome (Smith, Goodchild, Longley, 2011) Cases are considered a cluster if they fall within the expected mean distance +/- a confidence interval obtained from the standard error (Mictchell, 2005)Can be single or multi-level

20Nnh ClusteringSingle-levelIdentifies the largest clusters at the County levelMulti-levelIdentifies multiple levels of clusters (County, city area, neighborhood)Cluster Count CriteriaMinimum 1% of cases

21Preliminary Results

Nnh Cluster Analysis: 2009 New HIV Cases

Source: 2009 New HIV Cases, HIV Epidemiology Program

68.2% of HIV Cases

22This is an optional map slide. This map was developed from the HIV Epidemiology Programs Semi Annual Surveillance Report and shows AIDS cases identified in CY2007 by Health District.

Nnh Cluster Analysis: 2009 Syphilis + HIV Cases*

Source: 2009 Syphilis Cases, STD Program*HIV self-reported among Syphilis cases

68.2% of Syphilis-HIV Co-Infection Cases

23This is an optional map slide. This map was developed from the HIV Epidemiology Programs Semi Annual Surveillance Report and shows AIDS cases identified in CY2007 by Health District.

Cluster Analysis: 2009 Syphilis w/o HIV Cases*

Source: 2009 Syphilis Cases, STD Program*HIV self-reported among Syphilis cases

68.2% of Syphilis w/o HIV Cases

24This is an optional map slide. This map was developed from the HIV Epidemiology Programs Semi Annual Surveillance Report and shows AIDS cases identified in CY2007 by Health District.

Source: 2009 new HIV cases, HIV Epidemiology Program; 2009 new STD cases, STD Programn=1,45283.9% of HIV Cases in LAC25This is an optional map slide. This map was developed from the HIV Epidemiology Programs Semi Annual Surveillance Report and shows AIDS cases identified in CY2007 by Health District.

HIV Demographic SummaryAfrican-American27.8% Men81.5% Women18.5%Latino44.4% Men90.7% Women9.3%White23.8% Men97.4% Women2.6%Central Cluster, 2009 HIV and Syphilis Burden Disease Burden Summaryn%HIV86146.3%Syphilis + HIV64258.5%Syphilis no HIV71244.6%Gonorrhea3,33042.1%26This is an optional map slide. This map was developed from the HIV Epidemiology Programs Semi Annual Surveillance Report and shows AIDS cases identified in CY2007 by Health District.

South Cluster, 2009 HIV and Syphilis Burden

HIV Demographic Summary%African-American24.5% Men83.3% Women16.7%Latino44.2% Men83.0% Women17.0%White26.7% Men91.8% Women8.2%

Disease Burden Summaryn%HIV31818.4%Syphilis + HIV949.0%Syphilis no HIV22213.9%Gonorrhea1,61320.4%27This is an optional map slide. This map was developed from the HIV Epidemiology Programs Semi Annual Surveillance Report and shows AIDS cases identified in CY2007 by Health District.

Northwest Cluster, 2009 HIV and Syphilis Burden Source: 2009 New HIV Cases, HIV Epidemiology Program; 2009 New Syphilis Cases, 2009 HIV Cases, STD Program

HIV Demographic SummaryAfrican-American17.2% Men64.3% Women35.7%Latino51.5% Men89.4% Women10.6%White16.6% Men84.4% Women15.6%Disease Burden Summaryn%HIV1599.2%Syphilis + HIV908.6%Syphilis no HIV19112.0%Gonorrhea6378.0%28This is an optional map slide. This map was developed from the HIV Epidemiology Programs Semi Annual Surveillance Report and shows AIDS cases identified in CY2007 by Health District.

Source: 2009 New HIV Cases, HIV Epidemiology Program; 2009 New Syphilis Cases, 2009 HIV Cases, STD Program

HIV Demographic SummaryAfrican-American11.5% Men41.7% Women58.3%Latino52.0% Men98.2% Women1.8%White26.9% Men92.9% Women7.1%

East Cluster, 2009 HIV and Syphilis Burden Disease Burden Summaryn%HIV1146.6%Syphilis + HIV615.8%Syphilis no HIV1187.4%Gonorrhea4395.5%29This is an optional map slide. This map was developed from the HIV Epidemiology Programs Semi Annual Surveillance Report and shows AIDS cases identified in CY2007 by Health District.

North Cluster, 2009 HIV and Syphilis Burden

Disease Burden Summaryn%HIV221.3%Syphilis + HIV