Purpose: In this article, we examine the effectiveness of a variety of HIV diagnosis interventions in recently HIV-diagnosed men who have sex with men (MSM). These interventions use the preventive potential of postdiagnosis behavior change (PDBC), as measured by the reduction in the number of new infections. Empirical evidence for PDBC was presented in the behavioral substudy of the Southern California Acute Infection and Early Disease Research Program. In previous modeling work, we demonstrated the existing preventive effects of PDBC. However, a large proportion of new infections among MSM are either undiagnosed or diagnosed late, and the preventive potential of PDBC is not fully utilized.
Methods: We derive empirical, stochastic, network-based models to examine the effectiveness of several diagnosis interventions that account for PDBC among MSM over a 10-year period. These interventions involve tests with shorter detection windows, more frequent testing, and individualized testing regimens.
Results: We find that individualized testing interventions (i.e., testing individuals every three partners or 3 months, whichever is first, or every six partners or 6 months, whichever is first) result in significantly fewer new HIV infections than the generalized interventions we consider.
Conclusions: This work highlights the potential of individualized interventions for new public health policies in HIV prevention.
Keywords: Diagnosis strategies; Exponential random graph models (ERGMs); Men who have sex with men (MSM); Network models; Testing as prevention.
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