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Spatial clusters of people living with HIV/AIDS by risk of transmission in Texas Sonia Arbona PhD Praveen R. Pannala, MD, MPH Sharon K. Melville, MD, MPH May 26, 2009

Spatial clusters hiv texas

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Page 1: Spatial clusters hiv texas

Spatial clusters of people living with HIV/AIDS by risk

of transmission in Texas

Sonia Arbona PhDPraveen R. Pannala, MD, MPHSharon K. Melville, MD, MPH

May 26, 2009

Page 2: Spatial clusters hiv texas

Background

The areas of higher concentrations of people living with HIV/AIDS in Texas are the major metropolitan areas and the cities in their periphery (Texas DSHS, 2010)

Beyond this general pattern there is a need to identify clusters that can be targeted for public health interventions

Page 3: Spatial clusters hiv texas

Study Purpose

The analysis aims to identify spatial clusters within the known general distribution of HIV/AIDS cases in Texas

Spatial clusters characterized by:

Page 4: Spatial clusters hiv texas

Methods Statistics

The SaTScan software implemented the Spatial Scan Statistics (Kulldorff 1997, Kulldorff et al. 2009):

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Methods Statistics (Cont’d)

Statistics for each cluster are based on a Monte Carlo simulation:

• likelihood ratio, which indicates the probability of a cluster being real, and its corresponding p value

• relative risk estimate (RR = incidence proportioninside the cluster/incidence proportion outside the cluster)

Cases aggregated by zip codes are the units of observation

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Methods Sample

The analysis included 46,301 people living with HIV/AIDS in Texas as of December 31, 2008 by HIV transmission risk:

The 46,301 persons excluded institutionalized individuals and those without a residential zip code at time of report

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Results Number and location of clusters

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Nineteen clusters identified

18,173 (39.2%) of the cases included in the spatial clusters

Major metropolitan areas have more than one cluster

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Results Cluster Statistics

Table 1. Spatial clusters of HIV/AIDS in Texas by HIV mode of transmission in 2008 

Mode of Transmission

Cluster LocationObserved

casesExpected

casesRelative risk

estimateLog-likelihood

ratioP value

IDU

1 Houston 1196 358.4 3.98 674.95 0.0012 Fort Worth 108 8.15 13.49 180.09 0.0013 Dallas 182 39.31 4.75 138.1 0.0014 El Paso 30 4.4 6.84 32.02 0.0015 Dallas 29 5.54 5.26 24.61 0.0016 Waco 35 8.54 4.12 22.97 0.001

MSM

1 Dallas 4681 837.95 6.53 4501.07 0.0012 Houston 4514 1132.83 4.57 3086.00 0.0013 Austin 1585 711.75 2.30 410.11 0.0014 San Antonio 390 70.93 5.56 347.54 0.0015 El Paso 166 51.39 3.24 80.28 0.001

MSM/IDU

1 Houston 358 64.78 6.13 333.79 0.0012 Dallas 262 69.62 4.03 161.25 0.0013 Austin 198 53.40 3.90 118.44 0.0014 Fort Worth 57 15.33 3.77 33.46 0.001

HRT

1 Houston 3858 1173.57 4.68 2353.98 0.0012 Dallas 299 68.11 4.49 214.09 0.0013 Dallas 179 61.59 2.94 74.25 0.0014 Fort Worth 46 14.28 3.23 22.14 0.001

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Results Demographic Characteristics

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clustered

notclustered

38.9%

61.1%

Figure 2

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Results Spatial Clusters in Dallas – Fort Worth

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Results Spatial Clusters in Central Texas

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Results Spatial Clusters in Houston

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Comments and Future Directions

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Bibliography

Kulldorff M (1997) A spatial scan statistic. Communications in Statistics 26:1481-1496

Kulldorff M and Information Management Services, Inc. (2009) SaTScanTM v8.0: Software for the spatial and space-time scan statistics. http://www.satscan.org/

Texas Department of State Health Services (2010) 2008 HIV/STD Program Annual Report. Publication Number 13-10667