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HIV Among African Americans

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Title: HIV Among African Americans


1
HIV Among African Americans
  • Nina T. Harawa, MPH, PhD
  • Assistant 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

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HIV/AIDS Data
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7 times
20 times
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Gender distribution by Race/ethnicity new
HIV/AIDS Diagnoses in 2007
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NHANES Survey
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Summary National Data for African Americans
  • Make up 1 in 2 new cases but just 12 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

19
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

20
The Problem
  • Black people experience higher HIV/AIDS rates
    across gender, age, and behavioral risk groups.

21
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.

22
Percentage of Persons Aged 22--44 Years at
Increased Risk for Human Immunodeficiency Virus
(HIV) Infection, by Race/Ethnicity and Education
--- National Survey of Family Growth, United
States, 2002
23
Solving 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

24
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.

25
Chlamydia network from Qikiqtarjuaq,
NunavutCanada, 2003
Data courtesy of Andrea Cuschieri
26
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
27
Aspects of Sexual Networks
  • Core groups
  • Mixing patterns
  • Concurrency
  • Size
  • Connectedness
  • Rates of partner change

28
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)

29
Chlamydia network from Qikiqtarjuaq,
NunavutCanada, 2003
Data courtesy of Andrea Cuschieri
30
Core Transmitters
31
Chlamydia network from Qikiqtarjuaq,
NunavutCanada, 2003
Data courtesy of Andrea Cuschieri
32
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

33
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.

34
Examples of factors encouraging disassortative
mixing
  • Gender norms
  • Public sex venues
  • Sex-ratio imbalances
  • Secrecy/lack of dialogue regarding sexual
    histories

35
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.

36
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)

37
Centrality/Connectedness
  • The degree to which an individual is near all
    other individuals in a network (directly or
    indirectly).
  • How central an HIV person is to a network deeply
    influences transmission rates in a community.
  • In Colorado Springs, CO, network analysts found
    that HIV persons had high levels of risk
    behavior but were located in peripheral areas of
    risk networks.(Rothenburg et al. 98). This
    network configuration may have explained the
    relatively low HIV transmission levels.
  • HIV persons in New York City, NY occupied
    central positions within their needle-sharing and
    sexual risk networks, which helped explain the
    high observed levels of infection.(Friedman et
    al. 97)

38
Network Density
Two Examples 5 actors 10 possible ties
39
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.

40
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

41
CONTEXT-NETWORK PATHWAYS P O V E R T
Y/SEGREGATION Pool of
Relationship marriageable
men Instability CONCURRENCY SEX RATIO
42
Male-to-female sex ratios
  • Higher numbers of men than women across age
    groups.
  • Caused by differential
  • Mortality
  • Incarceration
  • Military service
  • Compounded by differential
  • Rates of interracial relationships
  • Unemployment

43
Current Marital Status
  • Black women are less likely to marry, marry
    later, and more frequently divorce than white
    women.Tucker and Mitchell-Kernan, 1995.
  • Black women ages 15, are nearly half as likely
    as white women to be married and living with
    their spouse (29 vs. 54) Table A1. Marital
    Status of People 15 Years and Over, by Age, Sex,
    Personal Earnings, Race, and Hispanic Origin,
    2003 - US Census

44
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.

45
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.

46
Dual Epidemics
47
Impact of incarceration
  • Imbalanced gender ratios
  • Disrupted relationships - correctional
    concurrency
  • Spread of STIs within prison
  • Normalization of incarceration and effects on
    normative community values of sex, violence and
    drug use
  • Diversion of human/economic resources

N.T. Harawa and A. Adimora. Incarceration,
African Americans, and HIV advancing a research
agenda. J Natl Med Assoc 100 (2008) 57-62.
48
Gender and cultural norms
  • Economic/historical circumstances have altered
    some gender norms but strengthened others.
  • Women historically have been employed.
  • Women often play crucial decision-making roles
    within institutions.
  • Masculine roles within families strongly
    upheld/defended given threats/assaults in other
    areas.

49
Racial oppression
  • Diminishes opportunities for economic
    advancement, especially for Black men.
  • CONTEXT - NETWORK RELATIONSHIPS
  • residential segregation by race
  • concentration of adverse social and economic
    influences (poverty, drugs, violence)
  • selection of partners
  • from neighborhood

50
Proximal/Distal Determinants
  • A determinate is an element that identifies or
    determines the nature of something or that fixes
    or conditions an outcome
  • PROXIMAL DETERMINATES directly affect disease
    risk.
  • DISTAL DETERMINANTS help shape behavior and the
    risks associated with given behaviors.

51
Determinants of Heightened STD Risks in African
American Communities
  • MAJOR PROXIMAL DETERMINATES
  • ??High prevalence of STDs
  • ??Sexual network patterns concurrency and mixing
    among different subpopulations
  • ??Risk behaviors
  • DISTAL DETERMINANTS
  • ??Poverty, inequality, discrimination,
    segregation
  • ??Healthcare access and utilization

52
NHANES Survey
53
African American MSM
  • Higher HIV rates despite
  • Similar to lower risk behaviors
  • Number partners
  • Unprotected sex
  • Risky drug use
  • . . . Compared with other MSM

54
Associations of Race/Ethnicity with HIV
Prevalence and HIV-related Behaviors among Young
MSM in Seven US Urban Centers
  • Nina T. Harawa, MPH, PhD
  • Los Angeles County
  • HIV Epidemiology Program

55
Hypothesis
  • Young Black and Latino MSM are more likely to
    report factors that are associated with high-risk
    partners and behaviors.
  • These contribute to increased infection risk.

Risk level of Partner pool
Social and sexual networks
RACE
INFECTION RISK
56
Objectives
  • Use the Young Mens Survey (YMS) Phase One data
    to
  • examine racial/ethnic differences in SES, risk
    behaviors, and partnership types
  • examine associations of these factors with HIV
    infection and
  • evaluate whether differences in these factors
    explain racial/ethnic disparities in HIV
  • . . . among young MSM ages 15 22 years.

57
Methods Sample Frame
  • Study conducted in SF, LA, Seattle, Dallas, NYC,
    Baltimore, and Miami
  • Venues identified via formative research
  • Coffee house, clubs, events, parks, gyms, etc.
  • Sampling frame constructed
  • On-site enumeration (4-hr periods with yield 7
    men ages 15-22 years)
  • Each month, 12 venues randomly selected

58
Methods - Recruitment
  • During sampling events
  • Potentially eligible young men sequentially
    selected and recruited
  • Consent obtained, survey administered, and HIV
    CT performed in a mobile unit
  • Compensation 40-50
  • Eligibility
  • Ages 15-22 years
  • Current resident
  • Spoke Spanish or English

59
Results - associations with race/ethnicity and age
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Results - multivariate
  • Following factors associated with infection
  • Race/ethnicity
  • Increasing age
  • Lacking a parent who completed grad/professional
    ed.
  • Being out of school/work
  • Certain partner types (? with exchange, steady,
    IDU partners)
  • Sharing needles
  • Sex while high on crack (and poppers)
  • Having any anal sex in past 6 months

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Results - multivariate associations with
race/ethnicity
63
Discussion
  • Reason for higher levels of infection among
    blacks and Latinos still unclear
  • Findings provided little direct support for the
    hypothesis

Risk level of Partner pool
Social and sexual networks
RACE
INFECTION RISK
64
Other Key Issues
  • Enhanced HIV testing a critical component
  • 91 of HIV blacks unaware of infection in YMS
    (ages 15-24 years)
  • Outness and homophobia may play key roles, but
    not always in the expected directions.
  • A number of studies have shown higher levels of
    risky behavior among out and gay-identified men
    than other MSM

65
Out to health provider by race/ethnicity and
known HIV status

Source L.A. Mens Survey 2008, National HIV
Behavioral Surveillance
66
Potential alternative explanations for high HIV
rates in Black MSM
  • Other indicators of partner type may better
    indicate risk (e.g., age, race, SES, etc.)
  • Greater levels of concurrency
  • Differential misreporting of risk behaviors
  • Differences in frequency of anal sex
  • Missed and delayed diagnosis of HIV infection
    among MSM of color and their partners
  • Biological differences (e.g., CCR5 mutation and
    circumcision prevalence)

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