Combinations of interventions to achieve a national HIV incidence reduction goal: insights from an agent-based model

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Abstract

Objective:

Analyzing HIV care service targets for achieving a national goal of a 25% reduction in annual HIV incidence and evaluating the use of annual HIV diagnoses to measure progress in incidence reduction.

Design:

Because there are considerable interactions among HIV care services, we model the dynamics of ‘combinations’ of increases in HIV care continuum targets to identify those that would achieve 25% reductions in annual incidence and diagnoses.

Methods:

We used Progression and Transmission of HIV/AIDS 2.0, an agent-based dynamic stochastic simulation of HIV in the United States.

Results:

A 25% reduction in annual incidence could be achieved by multiple alternative combinations of percentages of persons with diagnosed infection and persons with viral suppression including 85 and 68%, respectively, and 90 and 59%, respectively. The first combination corresponded to an 18% reduction in annual diagnoses, and infections being diagnosed at a median CD4+ cell count of 372 cells/μl or approximately 3.8 years from time of infection. The corresponding values on the second combination are 4%, 462 cells/μl, and 2.0 years, respectively.

Conclusion:

Our analysis provides policy makers with specific targets and alternative choices to achieve the goal of a 25% reduction in HIV incidence. Reducing annual diagnoses does not equate to reducing annual incidence. Instead, progress toward reducing incidence can be measured by monitoring HIV surveillance data trends in CD4+ cell count at diagnosis along with the proportion who have achieved viral suppression to determine where to focus local programmatic efforts.

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