An Examination of Diagnosis Strategies to Maximize the Preventive Potential of Post-Diagnosis Behavior Change: Insights from Southern California

Aditya Khanna, University of Washington
Steven M. Goodreau, University of Washington
Daniel Wohlfeiler, California Department of Public Health
Pamina Gorbach, University of California, Los Angeles
Eric Daar, University of California, Los Angeles
Susan Little, University of California, San Diego

We use network models to compare diagnosis strategies to reduce HIV incidence among men who have sex with men (MSM). We extend prior models, parameterized from the behavioral sub-study of the Southern California Acute Infection and Early Disease Program (and other published biological and demographic data), that demonstrated the population-level effects of post-diagnosis behavior change (presented at PAA 2013). The diagnosis strategies we model here involve tests with shorter detection windows, more frequent testing, and other individualized testing regimens. We simulate these strategies over a 10 year period and our primary outcome is the number of new infections. We find that individualized testing (IT) strategies (i.e. testing every 3 partners or 3 months, or every 6 partners or 6 months) are significantly more effective than realistic models of other diagnosis strategies. This work highlights the potential importance of individualized strategies for new public health policies in HIV prevention.