Investigating Voluntary Medical Male Circumcision Program Efficiency Gains through Subpopulation Prioritization: Insights from Application to Zambia

BACKGROUND:

Countries in sub-Saharan Africa are scaling-up voluntary male medical circumcision (VMMC) as an HIV intervention. Emerging challenges in these programs call for increased focus on program efficiency (optimizing program impact while minimizing cost). A novel analytic approach was developed to determine how subpopulation prioritization can increase program efficiency using an illustrative application for Zambia.

METHODS AND FINDINGS:

A population-level mathematical model was constructed describing the heterosexual HIV epidemic and impact of VMMC programs (age-structured mathematical (ASM) model). The model stratified the population according to sex, circumcision status, age group, sexual-risk behavior, HIV status, and stage of infection. A three-level conceptual framework was also developed to determine maximum epidemic impact and program efficiency through subpopulation prioritization, based on age, geography, and risk profile. In the baseline scenario, achieving 80% VMMC coverage by 2017 among males 15-49 year old, 12 VMMCs were needed per HIV infection averted (effectiveness). The cost per infection averted (cost-effectiveness) was USD $1,089 and 306,000 infections were averted. Through age-group prioritization, effectiveness ranged from 11 (20-24 age-group) to 36 (45-49 age-group); cost-effectiveness ranged from $888 (20-24 age-group) to $3,300 (45-49 age-group). Circumcising 10-14, 15-19, or 20-24 year old achieved the largest incidence rate reduction; prioritizing 15-24, 15-29, or 15-34 year old achieved the greatest program efficiency. Through geographic prioritization, effectiveness ranged from 9-12. Prioritizing Lusaka achieved the highest effectiveness. Through risk-group prioritization, prioritizing the highest risk group achieved the highest effectiveness, with only one VMMC needed per infection averted; the lowest risk group required 80 times more VMMCs.

CONCLUSION:

Epidemic impact and efficiency of VMMC programs can be improved by prioritizing young males (sexually active or just before sexual debut), geographic areas with higher HIV prevalence than the national, and high sexual-risk groups.

Below:  Program efficiency and policy domains of age-group prioritization in the voluntary medical male circumcision (VMMC) program.

A) Expansion path curve showing the incremental increase in total cost of the VMMC program relative to total number of HIV infections averted (magnitude of impact) for each age-group targeted intervention. The blue line describes the expansion of the program with minimal diminishing of returns and the red line describes the expansion of the program with considerable diminishing of returns. B)Frontier-policy plot classifying the different policy domains based on the theme of maximizing program efficiency (maximizing gain while minimizing cost). Circle size represents the magnitude of the impact.C) Frontier-policy plot delineating the different policy domains based on the theme of maximizing the total impact of the VMMC program. Circle size here represents the total number of VMMCs needed relative to the baseline VMMC intervention scenario. In both B and C, the orange circles represent the age brackets that fall within the optimal policy domain and the blue circle represents the baseline VMMC intervention scenario.

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By:   Awad SF¹, Sgaier SK^2,3, Tambatamba BC⁴, Mohamoud YA¹, Lau FK², Reed JB⁵, Njeuhmeli E⁶, Abu-Raddad LJ^1,7,8.

¹Infectious Disease Epidemiology Group, Weill Cornell Medical College in Qatar, Cornell University, Qatar Foundation, Education City, Doha, Qatar.

²Integrated Delivery, Global Development Program, Bill & Melinda Gates Foundation, Seattle, Washington, United States of America.

³Department of Global Health, University of Washington, Seattle, Washington, United States of America.

⁴Ministry of Community Development and Mother and Child Health, Lusaka, Zambia.

⁵Office of the U.S. Global AIDS Coordinator, Washington, District of Columbia, United States of America.

⁶United States Agency for International Development, Washington, District of Columbia, United States of America.

⁷Department of Healthcare Policy and Research, Weill Cornell Medical College, Cornell University, New York, New York, United States of America.

⁸College of Public Health, Hamad bin Khalifa University, Qatar Foundation, Education City, Doha, Qatar.

PLoS One. 2015 Dec 30;10(12):e0145729. doi: 10.1371/journal.pone.0145729.

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