kessler, j. myers, j.e. ; nucifora, k.a. ; mensah, n. ; kowalski, a. ; sweeney, m. ; toohey, c. ;...
TRANSCRIPT
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.HNo disclosures or conflicts of interest to report
July 23, 2012IAS 2012
• 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
• 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
1
23
45
67
High risk sexual networks (HR)
IDU
MSM
Impact of different prioritization strategies of TLC-Plus over 20 years in NYC
% o
f H
IV i
nfe
ctio
ns
ave
rted
New
HIV
in
fect
ion
s
% of HIV infections averted
Number of new HIV infections
0%
5%
10%
15%
20%
25%
30%
0tan28a566028
0tan16a568716
0tan6a57156
0tan25a574225
0tan14a576914
0tan2a57972
0tan22a582422
0tan11a585111
1.000 10000000001.000 20000000001.0000%
5%
10%
15%
20%
25%
30%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$
% H
IV i
nfe
ctio
ns
ave
rted
Efficient frontier of prioritization strategies of TLC-Plus
All MSM
High risk sexual networks among MSM
All IDU
• 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