2016
DOI: 10.1371/journal.pone.0156776
|View full text |Cite|
|
Sign up to set email alerts
|

Voluntary Medical Male Circumcision for HIV Prevention in Swaziland: Modeling the Impact of Age Targeting

Abstract: BackgroundVoluntary medical male circumcision (VMMC) for HIV prevention has been a priority for Swaziland since 2009. Initially focusing on men ages 15–49, the Ministry of Health reduced the minimum age for VMMC from 15 to 10 years in 2012, given the existing demand among 10- to 15-year-olds. To understand the implications of focusing VMMC service delivery on specific age groups, the MOH undertook a modeling exercise to inform policy and implementation in 2013–2014.Methods and FindingsThe impact and cost of ci… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
26
0

Year Published

2016
2016
2020
2020

Publication Types

Select...
8

Relationship

3
5

Authors

Journals

citations
Cited by 23 publications
(26 citation statements)
references
References 13 publications
0
26
0
Order By: Relevance
“…To date, seven countries (Malawi, South Africa, Swaziland, Tanzania, Uganda, Zambia, and Zimbabwe) have completed detailed country DMPPT 2 model applications to reexamine their age-targeting strategies for VMMC [1317,21,22]. In most cases, these modeling exercises have led to revised age-specific targets in the countries’ VMMC operational plans.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…To date, seven countries (Malawi, South Africa, Swaziland, Tanzania, Uganda, Zambia, and Zimbabwe) have completed detailed country DMPPT 2 model applications to reexamine their age-targeting strategies for VMMC [1317,21,22]. In most cases, these modeling exercises have led to revised age-specific targets in the countries’ VMMC operational plans.…”
Section: Discussionmentioning
confidence: 99%
“…The five DMPPT 2.0 country application papers in this collection [1317] all compare hypothetical scenarios in which MC coverage is scaled up to 80% in various age groups. The overall conclusions of these papers, similar to the outcomes of modeling conducted previously for Zimbabwe [2,3], are that the greatest immediate impact (largest reduction of HIV incidence over five years) can be achieved by circumcising males ages 20–29 or 20–34, and that these age groups are important for efficiency (number of VMMCs per HIV infection averted) and cost-effectiveness (cost per HIV infection averted) of the program.…”
Section: Introductionmentioning
confidence: 99%
“…Based on the modeling undertaken for this journal supplement, priority age groups can vary by country and by indicator of interest, as Table 1 shows. Although many countries had initially aimed to achieve 80% male-circumcision prevalence in the age group 15–49 years [3], several countries that participated in the modeling exercises—including Malawi [18], Swaziland [19], Uganda [20], and Zambia [21]—have revised their strategies and/or operational plans to focus on achieving targets among younger age ranges (most frequently 10–34 years) to maximize a combination of impact, cost-effectiveness, and feasibility.…”
Section: Progress In Vmmc Scale-up and The Potential Of Prioritizationmentioning
confidence: 99%
“…The DMPPT 2.0 model’s results in Tanzania reinforced the VMMC strategy launched in 2010, giving the country new confidence in investing in circumcising adolescents [22]. Modeling helped Swaziland set age-specific targets, balancing cost, impact, and feasibility, that were harmonized with its national goal of 70% coverage by 2018 of men ages 10–49 years [19]. Application of DMPPT 2.0 in Uganda led policymakers to propose males ages 10–34 years as a priority group for VMMC in Uganda’s application to the Global Fund [20].…”
Section: New Mathematical Models For Strategic Demand Creation Priorimentioning
confidence: 99%
“…[27] Given the geographically heterogeneous nature of the HIV epidemic, the Joint United Nations Programme on HIV/AIDS (UNAIDS) has called for renewed research efforts into the use of spatial analysis in epidemiology and health services research to identify populations both at greatest risk of HIV infection and in greatest need of prevention services. [28] A number of modeling studies have investigated the potential impact of targeting VMMC at key age-groups [29] and geographic regions where MC prevalence is low. [30,31] Our study is among the first to document small-scale geographic gaps in VMMC coverage.…”
Section: Discussionmentioning
confidence: 99%