HIV Among African Americans

1. HIV Among African Americans Nina T. Harawa, MPH, PhD Associate Professor Charles Drew University/UCLA

2. Objectives • To review the epidemiology of HIV among Black people in the US • Discuss the role of sexual networks in HIV epidemics • To discuss possible reasons for the disproportionate impact of HIV among African Americans

3. Epidemiology of HIV/AIDS among Black People in the US

4. AIDS Data All 50 States

9. HIV/AIDS Data National Surveillance

19. Estimated New Cases

20. HIV Prevalence & Behavioral Data

21. NHANES Survey

22. Nat’l Survey of Family Growth (NSFG)

23. NSFG - Treated for an STD in past 12 months

24. Condom Use at last sex

25. Summary – National Data for African Americans • Make up 1 in 2 new cases but just 13% or 1 in 8 of the US population. • Males are more affected than females • 2 out of every 3 new cases are male, 1 out of 3 is female • Greater racial disparities for females than males. • MSM are the largest portion of male cases. • Heterosexual risk is the largest portion of female cases. • High prevalence in Northeast and Southeast

26. Objectives • To understand why sexual networks may place a key role in the Af Am HIV epidemic • To understand key terms for aspects of sexual networks • To understand how contextual factors might influence the shape of Af Am sexual networks

27. The Problem • Black people experience higher HIV/AIDS rates across gender, age, and behavioral risk groups.

28. The Conundrum • Not all of these disparities explained by • higher risk behaviors • lower individual income/educational levels • key papers • Millett et al. 2006 and 2007, Malebranche 2008, Harawa, et al. 2004, Halfors, et al. 2007 • Although other minority groups experience disparities, this is not true across the board or across behavioral risk groups.

29. Helping to Solve the Conundrum • Looking beyond the individual level • Couple • Family • Network: social and sexual • Neighborhood, zip, city, county, state, etc. • Economic, STD prevalence, “broken windows”, criminal justice, drug, political, . . .environment

30. Sexual Networks • Groups of persons who are connected to one another sexually. The number of persons in a network, how central high-risk persons are within it, the percentage in monogamous relationships and the number of “links” each has to others all determine how quickly HIV/STDs can spread through a network. • Distinct from but often overlap with social networks. • Who has sex with whom. • How many and how tightly are members connected.

31. Data courtesy of Andrea Cuschieri

32. Transmission Dynamics Model R0= ß x c x D R0 = Case reproduction rate ß = Efficiency of transmission C = Mean rate of partner change D = Duration of infectiousness Higher the value of R0, greater spread of infection Pamina M. Gorbach, DrPH; Lecture: UCLA 5/10/01

33. Aspects of Sexual Networks • Core groups • Mixing patterns • Concurrency • Size • Connectedness • Rates of partner change

34. Core Groups • Critical to maintaining high transmission rates. • Core transmitters have high levels of risky behaviors, contribute a disproportionate share of HIV/STDs cases, and can fuel sustained transmission in a network. • Sex workers • Repeatedly infected with STDs • High numbers of sexual partners • From core neighborhoods/networks • Men who have sex with men • IDUs (?crack users)

35. Chlamydia network from Qikiqtarjuaq, NunavutCanada, 2003 Data courtesy of Andrea Cuschieri

36. Core Transmitters

37. Chlamydia network from Qikiqtarjuaq, NunavutCanada, 2003 Data courtesy of Andrea Cuschieri

38. Partner Mixing Patterns • Assortative • Tendency toward partnering with similar partners (e.g., “ISO”) • Similar race (especially Black women) • Disassortative • Tendency toward partnering with dissimilar partners. • Dissimilar risk groups (partnering between high- and low-risk partners). • Mixed

39. Disassortative Mixing • Random spread broadens transmission. An infection spreads quickest when partnering is random.(Laumann 1994) When partners select one another within groups such as age, ethnicity, class, religion or other characteristics, diseases may not spread to all subgroups. When partnering is anonymous or random, a disease can spread more quickly through all groups.

40. Examples of factors encouraging disassortative mixing • Gender norms • Public sex venues • Sex-ratio imbalances • Secrecy/lack of dialogue regarding sexual histories

41. Concurrency • Overlapping sexual partnerships • Sexual partnerships in which a new sexual partnership is initiated prior to the termination of another. • Bacterial STDs are known to travel faster in populations with greater concurrency, but with equal rates of new partnerships.

42. Concurrency • Increases the probability for transmission, because earlier partners can be infected by both earlier and later partners. Further, they can serve as “nodes”, connecting all persons in a dense cluster, creating highly connected networks that facilitate transmission. • Concurrent partners can connect each of their respective clusters and networks as well. • Concurrency alone can fuel an epidemic even if the average number of partners is relatively low.(Morris, 1997)

43. Summary – Sexual Networks • Networks integrate “core transmitters” into the larger population. • Dense networks help maintain STD endemicity. • Core transmitters are key to population-based STD control.

44. Sexual network structure of African American Communities • Factors which influence these patterns • Male-to-female sex ratios • Social and residential segregation • Incarceration • Gender and cultural norms • Racial oppression that diminishes opportunities for advancement, especially for Black men

45. CONTEXT-NETWORK PATHWAYS P O V E R T Y/SEGREGATION Pool of Relationship marriageable men Instability CONCURRENCY SEX RATIO

46. Male-to-female sex ratios • Higher numbers of women than men across age groups. • Caused by differential • Mortality • Incarceration • Military service • Compounded by differential • Rates of interracial relationships • Unemployment

47. Marital Status • Black women are less likely to marry, marry later, and more frequently divorce than white women. • Black women ages 15+ years, are nearly half as likely as white women to be married and living with their spouse [Table A1. Marital Status of People 15 Years and Over, by Age, Sex, Personal Earnings, Race, and Hispanic Origin, 2003 - US Census]

48. Social and residential segregation • Black people are the most racially segregated group in the US. • Black/white segregation indices are still quite high: 69%. • Blacks tend to be concentrated in metropolitan areas (58%). • Lower and middle-class African Ams more likely to live in low-income urban areas than poor and middle-class Whites.

49. Incarceration of Black Men • Nearly 5% of men are incarcerated at any given time. • Among men ages 20-29 years, nearly 1 in 3 are under criminal justice supervision. • Projection: Nearly 1 in 3 men will be imprisoned in lifetime. • Nearly 60% of low-income men who did not graduate HS will be imprisoned. • Bureau of Justice Statistics: http://bjs.ojp.usdoj.gov/

50. Dual Epidemics