Monday, October 21, 2013: 2:45 PM
Key Ballroom 3-4 (Hilton Baltimore)
Quantitative Methods and Theoretical Developments (MET)
Eric Lloyd Ross, AB1, Pamela P. Pei, PhD1, Rochelle P. Walensky, MD, MPH1, Elena Losina, PhD2, Milton C. Weinstein, PhD3 and Kenneth A. Freedberg, MD, MSc1, (1)Massachusetts General Hospital, Boston, MA, (2)Massachusetts General Hospital and Brigham and Women's Hospitals, Boston, MA, (3)Harvard School of Public Health, Boston, MA
Purpose: Many compartmental
models have projected substantial reductions in HIV prevalence with expanded
use of antiretroviral therapy (ART). Often these models simulate HIV disease as
progression through 3-5 “health states,” culminating in death; ART slows, but
does not reverse, this progression. Our objectives were to develop a dynamic
HIV transmission model that could incorporate a more detailed simulation of HIV
treatment, and to examine the implications of this framework for long-term
epidemic projections.
Method: We combine two
models to project HIV transmission. A stochastic, closed-cohort microsimulation
(CEPAC-International) projects CD4 count, HIV viral load, and survival
trajectories of an HIV-infected cohort. These trajectories are incorporated as
inputs to an open-cohort Susceptible-Infected (SI) model of HIV transmission,
in which infectivity depends on viral load. The microsimulation differs from
simpler models in that ART increases patients' CD4 counts, rather than merely
slowing disease progression. This produces improved health status by the time
of ART failure and/or loss-to-follow-up, resulting in longer survival with uncontrolled
viremia and relatively high infectivity.
To
assess the implications of this modeling approach, we simulate a policy of
immediate ART at diagnosis for HIV-infected patients in Kwa-Zulu Natal, South
Africa. Literature-based, base-case inputs include: HIV diagnosis rate of
40/100PY, 80% virologic suppression at 6m on ART, 4% loss-to-follow-up at 12m,
and 98% reduced infectivity with suppressed viral load; biannual viral load
monitoring guides switch to 2nd-line ART. For comparison, we
approximate simpler models by specifying immediate decline to pre-ART CD4 count
upon ART failure/loss-to-follow-up; this effectively erases the health gains
derived from ART, though it does not fully capture the continued progression while
on ART in simpler models.
Result: In the base case,
HIV incidence declines rapidly from 2.24/100PY to 1.35/100PY, and prevalence
declines from 24% to 22% over 20 years. Eliminating the health gains from ART
reduces average life-years with uncontrolled viremia from 7.7 to 6.0y; incidence
declines to 1.20/100PY, and 20-year prevalence decreases to 19% (Figure).
Conclusion: Using an HIV
microsimulation linked to an SI transmission model, we estimate that immediate ART
in South Africa will modestly reduce HIV prevalence. Eliminating the health
gains derived from ART – akin to simpler models – likely overestimates this
reduction. These results highlight
the importance of a detailed accounting of ART's health
benefits in models of HIV transmission.
