Planning HIV Prevention Interventions for High Risk Young Adults in LA County By Craig Pulsipher

Over 2,400 cases of HIV reported in Los Angeles County in % of new diagnoses among persons aged years. 41% of new diagnoses among Latinos, 27% among Whites, 25% among Blacks, 5% among Asian/Pacific Islander, and less than 1% among American Indian/Alaska Native. Estimated that 80% of 2008 HIV diagnoses were among men who have sex with men (MSM), 11% transmitted through heterosexual contact, 5% were heterosexual injection drug users, and 4% were MSM who also inject drugs. (LA County Department of Public Health, 2011)

Background Despite advances in HIV prevention, infection rates and numbers of new cases of HIV among adolescents continue to rise (Geanuracos et al., 2007) Areas of high prevalence and incidence of HIV are often characterized by high levels of racial/ethnic segregation and low socioeconomic status (Geanuracos et al., 2007)

How can geographic and neighborhood characteristics be used to plan HIV prevention interventions for high risk young adults in LA County?

++ += + Percent African American Households (20%) Percent Latino or Hispanic Households (20%) Percent Asian Households (20%) Percent of persons aged (20%) Household Median Income (20%) HIV Risk Index Hot Spot Analysis

Network Analysis

What if young adults don’t want to spend time traveling to an HIV testing location? How can information about popular venues that young adults frequent be used to plan HIV prevention interventions in LA County?

Healthy Young Men (HYM) Study (Kipke et al., 2007) Purpose: explore the individual, familial, interpersonal, and community factors that may influence drug use, HIV risk, and mental health 526 young men who have sex with men (YMSM) completed one survey every 6 months between February 2005 and January 2006 Data: demographic variables, sexual orientation, perceived health status, personal satisfaction, health behaviors, access to care, history of STIs and HIV, depression, suicidality, favorite “gay places”

Favorite “Gay Places” Many YMSM desire to receive HIV prevention information quickly and easily in social contexts that they are already attending with friends (Holloway, Cederbaum, Ajayi, & Shoptaw, 2012) Health and community service providers can engage YMSM for HIV education and prevention at popular venues (Reisner et al., 2009)

Spatial Analysis Euclidean Distance Kernel Density

Map Algebra Euclidean Distance + Kernel Density =

West Hollywood

Conclusion Geographic and neighborhood characteristics can be used to identify areas where young adults are at high risk for contracting HIV. Information about popular venues that young adults frequent can be used to identify ideal locations for HIV prevention interventions.

References AIDSVu ( Emory University, Rollins School of Public Health. [December 1, 2012.] Geanuracos, C., Cunningham, S., Weiss, G., Forte, L., Reid, H., Ellen, J. (2007). Use of geographic information systems for planning HIV prevention interventions for high-risk youths. American Journal of Public Health, 97(11): 1974–1981. HIV Epidemiology, Division of HIV and STD Programs, Los Angeles County Department of Public Health. (2011). Annual HIV Surveillance Report, February 2012: Holloway, I., Cederbaum, J., Ajayi, A., Shoptaw, S. (2012). Where are the young men in HIV prevention efforts? Comments on HIV prevention programs and research from young men who have sex with men in Los Angeles County. Journal of Primary Prevention, 33(5-6): Kipke, M. D., Kubicek, K., Weiss, G., Wong, C., Lopez, D., Iverson, E., & Ford, W. (2007). The health and health behaviors of young men who have sex with men. The Journal of Adolescent Health: Official Publication of the Society for Adolescent Medicine, 40(4): Reisner, S. L., Mimiaga, M. J., Skeer, M., Vanderwarker, R., Gaucher, M. J., O’Connor, C. A., … Safren, S. A. (2009). Differential HIV risk behavior among men who have sex with men seeking health-related mobile van services at diverse gay-specific venues. AIDS and Behavior, 13: 822–831.

Models

Skills 1.Modeling 2.Hot Spot Analysis 3.Network Analysis 4.Central Feature 5.Directional Distribution 6.Euclidean Distance 7.Kernel Density 8.Map Algebra 9.Original Data 10.Images