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New Haven Needle Exchange Program

New Haven Needle Exchange Program. Was it effective in reducing HIV transmission? Was it cost-effective ?. US History of HIV. 1981 CDC MMWR reports unusual pneumonia in 5 gay men in LA 1982 CDC coins the name AIDS 1983 HIV virus discovered 1985 HIV test approved 1986 AZT approved

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New Haven Needle Exchange Program

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  1. New Haven Needle Exchange Program • Was it effective in reducing HIV transmission? • Was it cost-effective?

  2. US History of HIV • 1981 CDC MMWR reports unusual pneumonia in 5 gay men in LA • 1982 CDC coins the name AIDS • 1983 HIV virus discovered • 1985 HIV test approved • 1986 AZT approved • 1987 US bans HIV+ immigrants and visitors • 1991 More drugs approved • 1997 Combination therapy becomes standard

  3. Drug use and the spread of HIV • IDU = injection drug user • 1/3 of US AIDS cases can be traced to drug injection • 1/2 of new HIV infections can be traced to drug injection • Spread of HIV among IDUs in NYC • 1985: prevalence close to 0 • 1988: 40% of IDUs infected • Becomes clear by 1987 that IDUs are dominant mode of transmission in New Haven • Reducing spread among IDUs a priority!

  4. Reducing spread of HIV among IDUs • Drug abuse treatment(e.g., detox, rapid detaox, residential programs) • Maintenance treatment(e.g., methadone, buprenorphine) • Bleach/education programs • Needle exchange programs

  5. Politics around needle exchange • Proponents: • Reduce HIV spread • Doesn’t increase drug use • Helps vulnerable minority populations • Opponents: • No evidence they reduce HIV spread • Encourages drug use • Admits defeat in war on drugs

  6. History of Needle Exchange • 1984 Implemented in Amsterdam • 1988 First US program in Tacoma, Washington • 1988 Use of federal funds is banned • 1990 May Connecticut legislature allows New Haven needle sharing programNov. Program starts • 1991 March initial data reported • 1992 Syringe possession decriminalized in Connecticut • 1993 Paper wins Edelman Award • 1998 Dept of HHS report “NEPs: Part of a Comprehensive HIV Prevention Strategy” • Currently ~200 needle exchange programs in US

  7. Early needle exchange studies • Relied on self-reported behavior about reduction in risky behavior • Did not incorporate quantity of needles exchanged

  8. New Haven program • Used needles exchanged 1-1 (up to 5) for new ones • Program clients and needles had IDs • Date, location, client ID, and needle IDs recorded at distribution and return of needles • Samples of needles tested for HIV

  9. Initial data from random testing • % HIV infected 91.5% (44/48) needles from “shooting gallery” 67.5% (108/160) street needles at program start 50.3% (291/579) program needles (first 15mo) 40.5% (147/367) program needles (next 12mo) • But how does reduced needle prevalencetranslate into reduced HIV transmission?

  10. Circulation Approach • Needle exchange… • Keeps number of needles in circulation constant • Increases needle turnover, thus reducing the time a needle is in circulation • Shorter circulation time reduces the number of uses (and users) per needle • Thus, decrease in number of infected needles

  11. Notation and Parameter Estimates • = 0.674 shared drug injections / client / year  = 0.84 probability a needle is bleached before injection  = 0.1 removal rate / HIV-infected client / year  = 0.0066 Pr [ HIV transmission probability | infected needle]  = 20.5 needle exchanges / circulating needle / year • = 0.1675 # clients / #circulating needles (t) fraction of circulating needles infected with HIV (0)=0.675 (t) HIV prevalence among program clients (0)=0.636 C(T) new infections over time period T / IDU

  12. Model ´(t) = [1-(t)]  (1-) (t)  - (t)  ´(t) = [1-(t)]   (t) - (t)[+(1-(t))] C(T) = t=0..T[1-(t)]  (1-) (t)  dt • HIV spread: IDU -> needle -> IDU • Malaria spread: humans -> mosquitoes -> humans • Needle exchange and bleach~ replacing infected mosquitoes with uninfected ones

  13. Effectiveness • One year horizon • No needle exchange (=0) • C(1)=0.064 = 6.4 HIV infections / 100 IDUs / year • With needle exchange (=20.5) • C(1)=0.043 = 4.3 HIV infections / 100 IDUs / year • Incidence reduced by 33%.

  14. Other Outcomes • No evidence of increase in drug injection • 1/6 of IDUs in program enter treatment • Program attracts minority clients • Local drug treatment: 60% white • Program clients: 60% nonwhite.

  15. Cost Effectiveness • Program cost: ~ $150,000 / year • Lifetime hospital costs / infection ~ $50k-100k • 20 infections averted • Cost saving!

  16. (0) +(0)+1-(0)] I = Sensitivity • Assume (t) constant • Approximately, • I decreases as •  increases • decreases •  decreases • Results robust

  17. Estimating rate of shared injections  • Self-reported 2.14 injections / client / day • Sharing rate • Self-reported 8.4% • But 31.5% of program needles returned by different client than originally issued to • Assume 31.5% (conservative) • Thus, 

  18. Estimating probability of bleaching  • Bleach outreach program begun in 1987 • Self-reported 84% use of bleach • Thus, =0.84

  19. Estimating IDU departure rate  • Departures due to • Development of AIDS • Drug treatment (1/6 of clients) • Hospitalization, jail, relocation,… • Assume departures due only to AIDS (conservative) • Mean time to AIDS ~ 10 years • Thus, 

  20. Estimating initial conditions (0), (0) • From needle data (108 infected / 160 tested) • Thus,  • Other studies on HIV prevalence among IDUs,  • 13% seeking treatment • 36% at STD clinics • 67% of African American men entering treatment • Assume at equilibrium before program starts: • ´(0)=0, ´(0)=0, =0 • Thus, (0)= (1-)] = 0.636

  21.  (1-)(1-  = Estimating infectivity per injection  • Studies of accidental needle sticks • Chance of transmission ~ 0.003-0.005 • Drug injection has higher probability • Assume at equilibrium before program start: • ´(0)=0, ´(0)=0, =0 •  • Thus, = 0.066

  22. Estimating the needle exchange rate  • Random variable Tr = time until needle returned • Exponential dist with rate  •  = needle exchanges / needle / year • Random variable Tl= time until needle is lost • Exponential dist. with rate  •  = rate at which needles lost / year • Random variable L = 1 if needle is legible, else 0 • Bernoulli with probability l • l=0.86 fraction of needles whose code is legible

  23. Estimating the needle exchange rate  • xi = 1 if the ith needle has been returned, else 0 • ti = observed (censored) circulation time of ith needle • If xi=1, then ti=Tr<Tl and L=1 • Likelihood = exp[-()ti] · l • If xi=0, then Tl<TrLikelihood: /() or (Tr<Tl and L=0) Likelihood: /() · (1-l) or (ti<min{Tr,Tl} and Tr<Tl and L=1) Likelihood: /() · exp[-()ti] · l

  24. Estimating the needle exchange rate  max log L = ∑i I(xi=1) log [exp[-()ti]l] + I(xi=0)log[/( (1-l)/() + l[/()]exp[-()ti]] • Max likelihood estimates •  = 20.5 needle exchanges / needle / year •  = 23.1 lost needles / circulating needle / year

  25. Estimating #clients / #needles  • = D/N N = number of needles in circulation D = number of IDUs in the program • Assume number of needles constant, N = D  = 20.5 needle exchanges / needle / year  = 122.4 needles distributed / IDU / year • Thus, 20.5/122.4=0.1675

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