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Endemic Cofactors of HIV

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					Endemic Cofactors of HIV

Why    th    till    l t d?
Wh are they still neglected?
         Eileen Stillwaggon
International Society for Infectious Diseases
    Neglected Tropical Diseases Meeting
          Boston, July 8—10, 2011
                Outline
• The HIV/AIDS policy paradigm

• Obstacles to addressing interactions
  between HIV and NTDs

• The role of NTDs in AIDS epidemics

• New avenues for modeling AIDS
  epidemics and NTD interactions
               Adult Prevalence of HIV
ivory = <0.1%                       tan = 0.1% to <0.5%
yellow = 0.5% to <1%                orange = 1% to <5%
   d      to 15%
 red = 5% t <15%                  dark d          t
                                  d k red = 15% to 26%
           Why are

        f d l i S       il d
  26 % of adults in Swaziland
              and
         f d lt in Zambia
   15 % of adults i Z bi

        HIV-infected

       and fewer than 1 %
in the USA and Western Europe?
     Behavior and individual risk
•   Early initiation of sex
•   Premarital sex
•   Multiple partners
•   Unprotected sex
    U           d
•   Alcohol use and sex
•   Concurrent sexual relationships
    At a national level, risky sexual behaviors
      do           l      ih            l
      d not correlate with HIV prevalence
                       t                it l
                   - extra- or pre-marital sex
                     -early initiation of sex
        -multiple partners in previous year or lifetime
                  -having any sexual partner
•                     (eds ) 1995
  Cleland and Ferry (eds.). 1995. Sexual Behaviour and AIDS in the
  Developing World. WHO.
• UNAIDS. 1999. “Fact Sheet on Differences in HIV Spread in African
  Cities ” unaids org
  Cities. unaids.org.
• Stillwaggon. 2006. AIDS and the Ecology of Poverty.
• Wellings et al. 2006. “Sexual behaviour in context: a global perspective”
               1706—1728.
  Lancet 368: 1706 1728
             Concurrent sexual partnerships:
     the latest attempt to find a behavioral anomaly

                                               pp g
The current conventional wisdom: Overlapping sexual
partnerships are especially common in sub-Saharan Africa and
explain the region’s high prevalence of HIV.


For the Concurrency Hypothesis to be valid, both of the
f ll i must be true:
following    tb t
    – long-term overlapping partnerships are far more
             common in Africa
    – long-term overlapping partnerships spread HIV much
             more rapidly than other sexual behaviors
      Quantitative Evidence does not show that concurrency is
                          more common
                    in eastern/southern Africa
               Halperin, Epstein, and Mah cite 33 studies reporting on
                            43 surveys or other research.

 None of the surveys they cite clearly supports the assertion that
   concurrency is unusually high in eastern/southern Africa.




Sawers, L. and E. Stillwaggon, Concurrent Sexual Partnerships Do Not Explain HIV Epidemics
in Africa: A Systematic Review of the Evidence, Journal of the International AIDS Society
13(34), 2010.
The Model
The concurrency hypothesis relies on a stochastic simulation model that purports to
show that concurrency spreads HIV more rapidly than other sexual behaviors.

To show that, the model requires four critical assumptions:

•   Frequency of sexual activity: Every person has sex with every partner, every day

•   Per-act transmission rate = 0.05

• Higher prevalence of concurrency than exists in sub-Saharan Africa and higher
even than the modelers’ own data

•   Gender symmetry

Without those four assumptions, the model shows that

concurrency leads to only a trivial difference in HIV infections

compared to serial monogamy.
    Modeling Sexual Networks and HIV

                Eaton, Hallett, Garnett
                   Behavior,
         AIDS and Behavior September 2010
“with staged transmission and up to 8% of individuals
                   partnerships,             spread
 having concurrent partnerships HIV fails to spread”
             Modeling Sexual Networks and HIV



                                               .




                      Sawers, Isaac, and Stillwaggon
             Journal of the International AIDS Society, in press
We use realistic values for frequency of sex and find that epidemics quickly drop to extinction
if only sexual behavior is included.
Why does the behavioral paradigm still
    drive AIDS policy in Africa?

• Racial stereotypes
    Stillwaggon, E.,
  – Stillwaggon E Racial Metaphors: Interpreting Sex and AIDS in
    Africa, Development and Change, 34(5):809 – 832, 2003.

         p
• Path dependence
  – Stillwaggon, E. AIDS and the Ecology of Poverty, Oxford
    University Press, 2006.

  Lots f
• L t of money
What else is going on

    besides sex?
Clinics and hospitals without medicines for curable STIs, and without
sterilizing equipment or disposable equipment (next slide).
       Why i    h
       Wh is each sex act

               or

            each birth

so much riskier in poor countries?
                         Transmission Efficiency


                     5                Risk of Transmission
               men




                             1/30-
               ml)




                                      Reflects Genital Viral Burden
 (Log10 copies/m




                             1/200
HIV RNA in Sem




                     4
                                                             1/100-
                                                             1/1000
        A
        c




                                     1/1000 -      1/500 -
                     3                             1/2000
                                     1/10,000
 (




                     2
Correlation Between Viral Load & HIV Transmission

                                                  30
                                          Years
                                                                                                                      Male-to-Female                                           Female-to-Male
                                                              All subjects
                                                                                                                       Transmission                                             Transmission
                                                  25
             smission rate per 100 Person-Y




                                                  20
                                 0




                                                  15

                                                  10
                      r




                                                  5

                                                  0
                                                                              9999




                                                                                                                                       9999




                                                                                                                                                                                                 9999
                                                                   499




                                                                                                                            499




                                                                                                                                                                                      499
                                                                                     10 000-49 999




                                                                                                                                              10 000-49 999




                                                                                                                                                                                                        10 000-49 999
                                                                                                     >50 000




                                                                                                                                                              >50 000




                                                                                                                                                                                                                        >50 000
                                                        400




                                                                                                                400




                                                                                                                                                                         400
                                                              400-34




                                                                                                                       400-34




                                                                                                                                                                                 400-34
         Trans




                                                                                               9




                                                                                                                                                        9




                                                                                                                                                                                                                  9
                                                                                                         0




                                                                                                                                                                  0




                                                                                                                                                                                                                            0
                                                       <4




                                                                                                               <4




                                                                                                                                                                        <4
                                                                         3500-9




                                                                                                                                  3500-9




                                                                                                                                                                                            3500-9
                                                        Viral load (HIV-1 RNA copies/ml) and HIV transmission

Quinn T, et al. N Engl J Med 2000; Fideli U, et al. AIDS Res Hum Retrovir 2001.
                0.3 log10   0.5 log10   1.0 log10
                increase    increase    increase
Increase in
likelihood of
heterosexual    18-20% 26-40%               100%
transmission
Increase in
risk of
progression     24-25%         44%          113%
to AIDS or
death
Cofactor Infections: Sexually Transmitted
Infections
   STIs promote HIV transmission
    – Making those without HIV more vulnerable
    – Making those with HIV more contagious

   Some STIs lead to genital ulceration
   Most STIs produce genital inflammation
   Most STIs promote viral shedding in the genital
    tract
                                          aa a
                                         Malaria
   causes chronic immune activation

   increases HIV replication 7                      to 10 times


   Increases mother-to-child transmission of HIV
   increases sexual transmission of HIV


HIV also increases malaria transmission.
Abu-Raddad, LJ, P Patnaik, and JG Kublin. 2006. Dual Infection with HIV and Malaria Fuels the Spread of
    Both Diseases in Sub-Saharan Africa, Science 314 (8 December): 1603–1606.
                         Transmission Efficiency


                     5                Risk of Transmission
               men




                             1/30-
               ml)




                                      Reflects Genital Viral Burden
 (Log10 copies/m




                             1/200
HIV RNA in Sem




                     4
                                                             1/100-
                                                             1/1000
        A
        c




                                     1/1000 -      1/500 -
                     3                             1/2000
                                     1/10,000
 (




                     2
Lymphatic filariasis is associated with higher risk of HIV infection and transmission.
Distribution of Lymphatic Filariasis
Distribution of helminths and
        HIV-1 in Africa
        HIV 1 i Af i




  Clinical Microbiology Reviews 2004, 17(4):1012—1030.
                Helminths (Worms)

   More than 80% of people in poor communities
    have at least one type of worm
   Virtually all children in urban slums, shanty towns,
    and rural villages have worms
       Helminths (Worms)

Roundworm, hookworm, whipworm

• infect 25 to 35% of world population

• cause anemia

• cause Vitamin-A deficiency
        Helminths (Worms)

Roundworm, hookworm, whipworm

• increase susceptibility to HIV

• increase HIV viral load and
     HIV transmission

• accelerate progression to AIDS
                 Difference in CD4 counts
                            follow-up
                 at 12 week follow up visit




       JL         PA           M,              BA, Lohman-Payne B, al.
Walson JL, Otieno PA, Mbuchi M Richardson BA Lohman Payne B et al
Albendazole treatment among adults with HIV-1 and helminth co-infection: A
randomized, double blind, placebo-controlled trial. AIDS 2008, 22:1601—1609.
                       p
         Difference in plasma viral load
            at 12 week follow-up visit




       JL         PA           M,              BA, Lohman-Payne B, al.
Walson JL, Otieno PA, Mbuchi M Richardson BA Lohman Payne B et al
Albendazole treatment among adults with HIV-1 and helminth co-infection: A
randomized, double blind, placebo-controlled trial. AIDS 2008, 22:1601—1609.
                       health
             Restoring health, buying time

          22 5
    Of the 22.5 million people infected with
    HIV-1 in Africa, only 31% of those in need
    are currently on ARVs.

   ART is expensive relative to other health
    care interventions (between $300 and $400
                       year).
    per individual per year)

   Delaying immunosuppression may “buy
    time” til th d      l      t f        th
    ti ” until the development of AIDS or the
    need for ART and will allow critical
    infrastructure to be developed.

    UNAIDS, 2007; Judd Walson
           Schistosomiasis (bilharzia)

   S. hematobium (urinary schistosomiasis) infects
                   ,                    p p
    33% of Africans, almost 200 million people.


   Causes blood loss, malnutrition, anemia
           Schistosomiasis (bilharzia)

   S. hematobium (urinary schistosomiasis) infects
                   ,                    p p
    33% of Africans, almost 200 million people.


   Causes blood loss, malnutrition, anemia


   In endemic areas, 75% of women with urinary
    schistosomiasis also have genital infection.
            Schistosomiasis (bilharzia)

   Worms and ova of S. hematobium infect the vagina,
    uterus, vulva, and cervix.
   S. hematobium lesions are indistinguishable from STIs
    without biopsy.
            Schistosomiasis (bilharzia)
   Worms and ova of S. hematobium infect the vagina,
    uterus vulva, and cervix
    uterus, vulva     cervix.
   S. hematobium lesions are indistinguishable from STIs
            biopsy
    without biopsy.
   Lesions provide direct access to the blood stream for
    HIV
    HIV.
   Worms and ova produce inflammation, attracting CD 4+
       ll to the   i    d th     it in the      d ti
    cells t th cervix and other sites i th reproductive
    tract.
   Infection blocks bilit t tili      th
    I f ti bl k ability to utilize ARV therapy.
             Schistosomiasis (bilharzia)

      GENITAL LESIONS OF SCHISTOSOMIASIS
                           INCREASE
                   WOMEN’S RISK OF HIV
                             3 FOLD
                             3-FOLD



Kjetland, E, P Ndhlovu, et al. 2006. Association between genital
schistosomiasis and HIV in rural Zimbabwean women, AIDS 20(4):593–600.
       What are the obstacles?
• Technical or logistical?

• Methodological?

• Political?
       Cost of Treating 7 NTDs
    0 50
US$ 0.50 all inclusive for treating 7 NTDs
          4 DRUGS
            d li
          + delivery
          + equipment
            health d      i       i l
          + h l h education materials
          + training of personnel
          + monitoring and evaluation
          _________________________
          US$ 0.50 per person per year
            Weaknesses of
      cost-effectiveness analysis
                             y
• Single-input, single-output

  Short term
• Short-term

  Only     level f  l i i di id l
• O l one l l of analysis, individual or
  population
          Matrix of disease and treatment interactions

          malnu   worm   malaria   schist   STI       ART   HIV

malnu               ↑↓                                        ↑

worm        ↑               ↑↓                    ↑           ↑

malaria     ↑                                               ↑ 7-10

schist      ↑                                     ↑           ↑3

STI                                   ↑                       ↑

ART         ↓?      Х       Х         Х           ↓           ↓

HIV         ↑       ↑       ↑         ↑           ↑
          Weaknesses of
     CEA for disease prevention
                     p
• Intermediate inputs, NOT outcomes

• Interaction terms are rare

  No l h         f disease causation
• N real theory of di            i
     What CEA needs to include for
       p
       prevention and treatment
• Endogeneity

  Non linearity, non-convexity
• Non-linearity non convexity

      lil l h           f disease causation
• A multi-level theory of di            i

•   Stillwaggon, E. Complexity, cofactors and the failure of AIDS policy in Africa,
    Journal of the International AIDS Society 12(12), 2009.
         Pre-HAART Package of Care
  • Suggested                           • Unclear
     – Septrin                             – Macronutrients
     – Micronutrients                      – Acyclovir
     – TB prophylaxis                      – Deworming  g
                                           – Bednets
                                           – Water filters
                      Annual Cost   Dosing schedule    Tolerability
      Septrin           $10.00           DAILY             **

     Acyclovir          $185.00          DAILY             ***

      Bednets            $5.00           DAILY            ****

        ART             $300.00          DAILY              *

   Deworming            $0.25       Every 4-6 months      ****
Source: Judd Walson
                     g
            Increasing Returns
• Economies of scale

• Economies of scope

  Positive t t  t ill         i t i di id l
• P iti treatment spillovers, intra-individual

• Population effects
   Biomedical research needs
• Insufficient research
                    Insufficient research
• Up to 2008, there had been
   – 3 Randomized, controlled trials
        Walson 2008 – S il t
      •W l                           itt d H l i th (K
                        Soil transmitted Helminths (Kenya))
      • Nielson 2007 – Lymphatic Filariasis (Tanzania)
      • Kallestrup 2005 – Schistosomiasis (Zimbabwe)
   – 4 Observational studies, comparator groups have been:
      • Helminth-uninfected individuals
      • Same individuals pre/post treatment
      • Individuals who clear infection vs. those who don’t
• ONLY one RCT and one observational study had been adequately
  powered to detect a 0.3 log10 difference in plasma HIV RNA.

Walson J and G John-Stewart, Treatment of Helminth Co-Infection in Individuals with HIV-1:
  A Systematic Review of the Literature PLoS NTDs 1(3), 2007.
      Biomedical research needs
• Insufficient research
• Conflicting results
  –              p
      Small samples
  –   No control group
  –   No discrimination of species
  –   Short follow-up or no follow-up
  Kayvon Modjarrad, Sten H Vermund, Effect of treating co-infections on HIV-1 viral
    load:          i     i   Lancet I f
    l d a systematic review, L                 D        10, 2010.
                                    Infectious Diseases 10 2010

• An attentive audience and FUNDING from
  the AIDS policy community
     The Spread of AIDS in Africa




Source: AVERT.ORG
  Multiple Regression Analysis of HIV prevalence
  with basic model and with cofactor infections
  R2 = .80




Sawers, L. and Stillwaggon, E. Understanding the Southern Africa ‘Anomaly’: Poverty, Endemic Disease,
and HIV, Development and Change 41(2):195 – 224, 2010.
  Explaining
 “Explaining” the southern Africa differential

                  explain
Regression can “explain” southern Africa
 differential by reducing the regression coefficient
 on southern Africa

   g
Regression without cofactor infections
“Explains” about 10% of the southern Africa
  differential

   g
Regression with cofactor infections
“Explains” about 70% of the southern Africa
  differential
Modeling Sexual Networks and HIV

                             .




            Sawers, Isaac, and Stillwaggon
                                     Society,
   Journal of the International AIDS Society in press


               g
What will adding cofactors do?
   Rapid growth of HIV/AIDS in
       sub-Saharan Africa




Source:
AVERT.ORG
              Determining cost-saving options




Stillwaggon E, CS Carrier, MP Sautter, R McLeod, 2011, Maternal Serologic Screening to
Prevent Congenital Toxoplasmosis: A Decision-Analytic Economic Model, forthcoming.
    Risky behaviors that explain HIV
      for b S h            l i
      f sub-Saharan populations
•   Early initiation of sex
•   Premarital sex
•   Multiple partners
•   Extramarital sex
•   Unprotected sex
•   Alcohol use and sex
•                                p
    Concurrent sexual relationships
Risky Behavior:
   Living with mosquitoes
Risky Behavior:
   Living with disease vectors
Risky Behavior:
   Living with soil-transmitted worms
Risky Behavior:
   Washing clothes in stream with
             schistosomiasis
    y
Risky Behavior:
   Fishing in lake with schistosomiasis
Risky Behavior:
   Living with poor sanitation
Risky Behavior:
   Attending clinics that have no medicine
      Nigeria's Triumph: Dracunculiasis
                  Eradicated
  Emmanuel S. Miri, Donald R. Hopkins*, Ernesto Ruiz-Tiben, Adamu S. Keana,
P. Craig Withers, Jr., Ifeoma N. Anagbogu, Lola K. Sadiq,Oladele O. Kale, Luke D.
       Edungbola, Eka I. Braide, Joshua O. Ologe, and Cephas Ityonzughul
            g     ,              ,             g ,       p      y     g


The Carter Center, Jos, Nigeria; The Carter Center, Atlanta, Georgia;
              World Health Organization/Nigeria and
             Federal Ministry of Health, Abuja, Nigeria

                                                    215 225
           Am. J. Trop. Med. Hyg., 83(2), 2010, pp. 215-225
Thanks for some slides from
                 Judd L. Walson, MD, MPH
                    Assistant Professor
 Departments of Global Health, Medicine (Infectious Diseases),
                Pediatrics and Epidemiology
                  University of Washington

                Sten H. Vermund, MD, PhD
            Vanderbilt Institute for Gl b l Health
            V d bilt I tit t f Global H lth
Additional slides

 On sexual behavior
 On HIV cofactors
                    Genital herpes simplex virus type 2 -
                          seroprevalence, by age,
                         (1976–80) and (1988–94)
Percent
P     t
 40

 32

 24

 16
                                                                          NHANES II
  8                                                                       NHANES III

  0
      12 19
      12-19          20-29
                     20 29          30-39
                                    30 39          40 49
                                                   40-49          50 59
                                                                  50-59    60-69
                                                                           60 69       70+
                                                                                       70
                                                Age Group



              Note: Bars indicate 95% confidence intervals.
              *National Health and Nutrition Examination Survey
        Median age at first intercourse
                g
                         (selected countries, by gender)




Derived from Singh S, et al. 2000. “Gender Differences in the Timing of First Intercourse:
Data from 14 Countries,” International Family Planning Perspectives 26(1):21–28, 43.
Source: John O. G. Billy, Koray Tanfer, William R. Grady, and Daniel H. Klepinger. 1993. “The
Sexual Behavior of Men in the United States,” Family Planning Perspectives 25(2):52–60.
Source: Kathryn Kost and Jacqueline Darroch Forrest. 1992. “American Women’s Sexual Behavior and
Exposure to Risk of Sexually Transmitted Diseases,” Family Planning Perspectives 24(6):244–254.
 Canada: first-year college students

   ith              sexual
  with more than 10 se al partners


                       Men: 21 %

                     Women: 9 %

Source: N. MacDonald, G. Wells, W. Fisher, et al. 1990. “High-Risk
STD/HIV Behavior among College Students,” Journal of the American
Medical Association 263(23):3155–3159.
 Canada: first-year college students

      ith           sexual
     with 5 or more se al partners


                       Men: 40 %

                    Women: 25 %

Source: N. MacDonald, G. Wells, W. Fisher, et al. 1990. “High-Risk
STD/HIV Behavior among College Students,” Journal of the American
Medical Association 263(23):3155–3159.
      Protein-energy malnutrition
      P t i            l t iti

                       reduces
• integrity of skin and mucous membranes

• T-cell production.
                         y
           Iron-deficiency anemia

              reduces production of

•       ll
    B cells
•   T cells
•   N       l Killer    ll
    Natural Kill (NK) cells.
                  Zinc deficiency

                           d
                         reduces
  Natural Kill cell activity
• N     l Killer ll i i

• T-cell production

• integrity of the skin as a barrier to infection.
             Vitamin-A deficiency
• reduces production of
   – NK cells
         ll
   – T cells
   – B cells

• reduces skin and mucosal integrity


• increases viral load.
Maternal malnutrition increases
     MTC transmission


  Anemia increases viral shedding in the
              birth canal

				
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