Introduction The epidemiological and programmatic implications of inclusivity of HIV positive males in voluntary medical male circumcision (VMMC) programs are uncertain. We modelled these implications in Zambia as an illustrative example.
Methods We used the Age-Structured Mathematical (ASM) model to evaluate the effectiveness (number of VMMCs needed to avert one HIV infection) of VMMC scale-up scenarios with varying proportions of HIV positive males. The range of proportions across the scenarios was derived from empirical data and programmatic considerations.
Results The number of VMMCs needed to avert one HIV infection in Zambia was projected to increase from 12.2 VMMCs per HIV infection averted, in a program that circumcises only HIV negative males, to 14.0 in a program that includes HIV positive males, based on their prevalence in the population. However, if a program that only reaches out to negative males is associated with 20% lower uptake among higher-risk males, the effectiveness would be 13.2 VMMCs per infection averted. If improved inclusivity of positive males is associated with 20% higher uptake among higher-risk males, the effectiveness would be 12.4. As the assumed VMMC efficacy against male-to-female HIV transmission is increased from 0% to 20% and 46%, the effectiveness of circumcising regardless of HIV status improves from 14.0 to 11.5 and 9.1, respectively. HIV incidence rate reduction among females would increase accordingly from 24.7% to 34.8% and 50.4%, respectively.
Conclusion Improving inclusivity of males in VMMC programs regardless of HIV status increases VMMC effectiveness, if there is moderate increase in VMMC uptake among higher-risk males and/or if there is moderate efficacy for VMMC against male-to-female transmission. In these circumstances, VMMC programs can reduce HIV incidence rate in males by nearly as much as expected by some anti-retroviral therapy programs, and additionally, females can benefit from the intervention by nearly as much as males.
Disclosure of interest statement This publication is based on research funded by the Bill and Melinda Gates Foundation. Infrastructure support was provided by the Biostatistics, Epidemiology, and Biomathematics Research Core at the Weill Cornell Medical College in Qatar. The content of this manuscript is the sole responsibility of the authors. The information provided here is not official US Government information and does not necessarily represent the views or positions of United States Agency for International Development, the United States Government, or the Bill and Melinda Gates Foundation.
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