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Kessler, J. Myers, J.E. ; Nucifora, K.A. ; Mensah, N. ; Kowalski, A. ; Sweeney, M. ; Toohey, C. ; Shepard, C. ; Cutler, B. ; Braithwaite, R.S. Modeling.

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Presentation on theme: "Kessler, J. Myers, J.E. ; Nucifora, K.A. ; Mensah, N. ; Kowalski, A. ; Sweeney, M. ; Toohey, C. ; Shepard, C. ; Cutler, B. ; Braithwaite, R.S. Modeling."— Presentation transcript:

1 Kessler, J. Myers, J.E. ; Nucifora, K.A. ; Mensah, N. ; Kowalski, A. ; Sweeney, M. ; Toohey, C. ; Shepard, C. ; Cutler, B. ; Braithwaite, R.S. Modeling the impact of focused strategies on the cost and effectiveness of TLC-Plus (or "Test and Treat") in New York City Presented by Jason Kessler, M.D., M.P.H No disclosures or conflicts of interest to report July 23, 2012 IAS 2012

2 Background o HPTN 052 strengthened evidence base for HIV treatment as a prevention strategy o TLC-Plus: community level test and treat intervention being tested in HPTN 065 (Bronx, NY and Washington DC) Objectives o To evaluate the impact of prioritization of TLC-Plus strategies in New York City (NYC). o To identify optimal prioritization strategies for given budget scenarios (i.e. biggest bang for the buck) Background and Objectives

3 Integrated compartmental model (transmission) with microsimulation model (disease progression) Background Inputs: o HIV testing probability (per year) = 31% o Linkage to care probability (within 90 days) = 75% o Adherence probability= 63% Intervention effects: o Increases HIV testing probability by 33%, linkage to care by 30% and adherence by 20% in prioritized population o Secondary effects of increased condom usage, and more monogamous relationships Prioritization strategies compared: o General population (1) o All MSM (3) o All IDU (4) o High risk sexual networks (HR) all (2) among MSM (5) among IDU (6) among MSM/IDU (7) Methods High risk sexual networks (HR) IDU MSM

4 Impact of different prioritization strategies of TLC-Plus over 20 years in NYC % of HIV infections averted New HIV infections % of HIV infections averted Number of new HIV infections

5 General population All high risk sexual networks High risk sexual networks among IDUs High risk sexual networks among IDU/MSM Total cost over 20 years - US$ % HIV infections averted Efficient frontier of prioritization strategies of TLC-Plus All MSM High risk sexual networks among MSM All IDU

6 TLC-Plus can prevent thousands of new HIV infections in NYC With conservative assumptions we find more modest impact of TLC- Plus than other models of test and treat strategies Focusing implementation of TLC-Plus among certain subpopulations (or neighborhoods where key subpopulations may concentrate) can render this intervention more cost-effective o Increase in feasibility. Conclusions


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