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AbstractIntroductionGiven the importance of voluntary medical male circumcision (VMMC) in reducing HIV incidence, access to and use of quality data for programme planning and management are essential. Unfortunately, such data are currently not standardized for reliable and consistent programme use in priority countries. To redress this, the UNAIDS Reference Group (RG) on Estimates, Modelling, and Projection worked with partner Avenir Health to use the Decision Makers Program Planning Toolkit (DMPPT) 2 Online to provide estimates of VMMC coverage and to support countries to set age‐ and geographic‐specific targets. This article describes the methods and tools used for assembling, reviewing and validating VMMC programme data as part of the 2021 Estimates process.DiscussionThe approach outlined for integrating VMMC data using the DMPPT2 Online required significant country engagement as well as upgrades to the DMPPT2 Online. The process brought together local‐level VMMC stakeholders, for example Ministries of Health, the Joint United Nations Programme on HIV/AIDS (UNAIDS), the US President's Emergency Plan for AIDS Relief, the World Health Organization (WHO), VMMC implementers and so on, to review, amend and agree on historical and more recent VMMC data. The DMPPT2 Online was upgraded to align with the Spectrum and Naomi models used in the Annual HIV Estimates process. In addition, new and revised inputs were incorporated to enhance accuracy of modelled outputs. The process was successful in mobilizing stakeholders behind efforts to integrate VMMC into the annual HIV Estimates process and generating comprehensive, country‐owned and validated VMMC data that will enhance programme monitoring and planning.ConclusionsVMMC programme data from most of the priority countries were successfully reviewed, updated, validated and incorporated into the annual HIV Estimates process in 2020. It is important to ensure that these data continue to be used for programme planning and management. Current and future data issues will need to be addressed, and countries will need ongoing support to do so. The integration of the DMPPT2 Online into the annual HIV Estimates process is a positive step forward in terms of streamlining country‐owned planning and analytical practices for the HIV response.

AbstractIntroductionOral pre‐exposure prophylaxis (PrEP) provision is a priority intervention for high HIV prevalence settings and populations at substantial risk of HIV acquisition. This mathematical modelling analysis estimated the impact, cost and cost‐effectiveness of scaling up oral PrEP in 13 countries.MethodsWe projected the impact and cost‐effectiveness of oral PrEP between 2018 and 2030 using a combination of the Incidence Patterns Model and the Goals model. We created four PrEP rollout scenarios involving three priority populations—female sex workers (FSWs), serodiscordant couples (SDCs) and adolescent girls and young women (AGYW)—both with and without geographic prioritization. We applied the model to 13 countries (Eswatini, Ethiopia, Haiti, Kenya, Lesotho, Mozambique, Namibia, Nigeria, Tanzania, Uganda, Zambia and Zimbabwe). The base case assumed achievement of the Joint United Nations Programme on HIV/AIDS 90‐90‐90 antiretroviral therapy targets, 90% male circumcision coverage by 2020 and 90% efficacy and adherence levels for oral PrEP.ResultsIn the scenarios we examined, oral PrEP averted 3% to 8% of HIV infections across the 13 countries between 2018 and 2030. For all but three countries, more than 50% of the HIV infections averted by oral PrEP in the scenarios we examined could be obtained by rollout to FSWs and SDCs alone. For several countries, expanding oral PrEP to include medium‐risk AGYW in all regions greatly increased the impact. The efficiency and impact benefits of geographic prioritization of rollout to AGYW varied across countries. Variations in cost‐effectiveness across countries reflected differences in HIV incidence and expected variations in unit cost. For most countries, rolling out oral PrEP to FSWs, SDCs and geographically prioritized AGYW was not projected to have a substantial impact on the supply chain for antiretroviral drugs.ConclusionsThese modelling results can inform prioritization, target‐setting and other decisions related to oral PrEP scale‐up within combination prevention programmes. We caution against extensive use given limitations in cost data and implementation approaches. This analysis highlights some of the immediate challenges facing countries—for example, trade‐offs between overall impact and cost‐effectiveness—and emphasizes the need to improve data availability and risk assessment tools to help countries make informed decisions.

Although oral PrEP is highly effective at preventing HIV acquisition, optimizing continuation among beneficiaries is challenging in many settings. We estimated the costs of delivering oral PrEP to populations at risk of HIV in seven clinics in Zimbabwe. Full annual economic costs of oral PrEP initiations and continuation visits were estimated from the providers' perspective for a six-clinic NGO network and one government SGBV clinic in Zimbabwe (January–December 2018). Disaggregating costs of full initiation and incremental follow-up visits enabled modeling of the impact of duration of continuation on the cost per person-year ($pPY) on PrEP. 4677 people initiated oral PrEP, averaging 2.7 follow-up visits per person. Average cost per person initiated was $238 ($183–$302 across the NGO clinics; $86 in the government facility). The full cost per initiation visit, including central and direct costs, was $178, and the incremental cost per follow-up visit, capturing only additional resources used directly in the follow up visits, was $22. The average duration of continuation was 3.0 months, generating an average $pPY of $943, ranging from $839 among adolescent girls and young women to $1219 in men. Oral PrEP delivery costs varied substantially by scale of initiations and by duration of continuation and type of clinic. Extending the average oral PrEP continuation from 2.7 to 5 visits (about 6 months) would greatly improve service efficiency, cutting the $pPY by more than half.

Although oral PrEP is highly effective at preventing HIV acquisition, optimizing continuation among beneficiaries is challenging in many settings. We estimated the costs of delivering oral PrEP to populations at risk of HIV in seven clinics in Zimbabwe. Full annual economic costs of oral PrEP initiations and continuation visits were estimated from the providers' perspective for a six-clinic NGO network and one government SGBV clinic in Zimbabwe (January-December 2018). Disaggregating costs of full initiation and incremental follow-up visits enabled modeling of the impact of duration of continuation on the cost per person-year ($pPY) on PrEP. 4677 people initiated oral PrEP, averaging 2.7 follow-up visits per person. Average cost per person initiated was $238 ($183-$302 across the NGO clinics; $86 in the government facility). The full cost per initiation visit, including central and direct costs, was $178, and the incremental cost per follow-up visit, capturing only additional resources used directly in the follow up visits, was $22. The average duration of continuation was 3.0 months, generating an average $pPY of $943, ranging from $839 among adolescent girls and young women to $1219 in men. Oral PrEP delivery costs varied substantially by scale of initiations and by duration of continuation and type of clinic. Extending the average oral PrEP continuation from 2.7 to 5 visits (about 6 months) would greatly improve service efficiency, cutting the $pPY by more than half.

Although oral PrEP is highly effective at preventing HIV acquisition, optimizing continuation among beneficiaries is challenging in many settings. We estimated the costs of delivering oral PrEP to populations at risk of HIV in seven clinics in Zimbabwe. Full annual economic costs of oral PrEP initiations and continuation visits were estimated from the providers' perspective for a six-clinic NGO network and one government SGBV clinic in Zimbabwe (January–December 2018). Disaggregating costs of full initiation and incremental follow-up visits enabled modeling of the impact of duration of continuation on the cost per person-year ($pPY) on PrEP. 4677 people initiated oral PrEP, averaging 2.7 follow-up visits per person. Average cost per person initiated was $238 ($183–$302 across the NGO clinics; $86 in the government facility). The full cost per initiation visit, including central and direct costs, was $178, and the incremental cost per follow-up visit, capturing only additional resources used directly in the follow up visits, was $22. The average duration of continuation was 3.0 months, generating an average $pPY of $943, ranging from $839 among adolescent girls and young women to $1219 in men. Oral PrEP delivery costs varied substantially by scale of initiations and by duration of continuation and type of clinic. Extending the average oral PrEP continuation from 2.7 to 5 visits (about 6 months) would greatly improve service efficiency, cutting the $pPY by more than half. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10461-021-03367-w.

AbstractIntroductionSeveral low‐ and middle‐income countries (LMICs) are preparing to introduce long‐acting pre‐exposure prophylaxis (LAP). Amid multiple pre‐exposure prophylaxis (PrEP) options and constrained funding, decision‐makers could benefit from systematic implementation planning and aligned costs. We reviewed national costed implementation plans (CIPs) to describe relevant implementation inputs and activities (domains) for informing the costed rollout of LAP. We assessed how primary costing evidence aligned with those domains.MethodsWe conducted a rapid review of CIPs for oral PrEP and family planning (FP) to develop a consensus of implementation domains, and a scoping review across nine electronic databases for publications on PrEP costing in LMICs between January 2010 and June 2022. We extracted cost data and assessed alignment with the implementation domains and the Global Health Costing Consortium principles.ResultsWe identified 15 implementation domains from four national PrEP plans and FP‐CIP template; only six were in all sources. We included 66 full‐text manuscripts, 10 reported LAP, 13 (20%) were primary cost studies‐representing seven countries, and none of the 13 included LAP. The 13 primary cost studies included PrEP commodities (n = 12), human resources (n = 11), indirect costs (n = 11), other commodities (n = 10), demand creation (n = 9) and counselling (n = 9). Few studies costed integration into non‐HIV services (n = 5), above site costs (n = 3), supply chains and logistics (n = 3) or policy and planning (n = 2), and none included the costs of target setting, health information system adaptations or implementation research. Cost units and outcomes were variable (e.g. average per person‐year).DiscussionLAP planning will require updating HIV prevention policies, technical assistance for logistical and clinical support, expanding beyond HIV platforms, setting PrEP achievement targets overall and disaggregated by method, extensive supply chain and logistics planning and support, as well as updating health information systems to monitor multiple PrEP methods with different visit schedules. The 15 implementation domains were variable in reviewed studies. PrEP primary cost and budget data are necessary for new product introduction and should match implementation plans with financing.ConclusionsAs PrEP services expand to include LAP, decision‐makers need a framework, tools and a process to support countries in planning the systematic rollout and costing for LAP.

HIV modelling and economic analyses have had a prominent role in guiding programmatic responses to HIV in sub-Saharan Africa. We reflect critically how the HIV modelling field might develop in future. We argue for HIV modelling to be more routinely aligned with national government and ministry of health priorities, recognizing their legitimate mandates and stewardship responsibilities, for HIV and other wider health programmes. We also place importance on an environment existing in which collaboration between modellers, and joint approaches to addressing modelling questions, becomes the norm rather than exception. Such an environment can accelerate translation of modelling analyses into policy formulation because areas where models agree can be prioritized for action, whereas areas over which uncertainty prevails can be slated for additional study, data collection and analysis. We also argue the need for HIV modelling to increasingly be integrated with the modelling of health needs beyond HIV, particularly in allocative efficiency analyses, where focusing on one disease over another may lead to worse health overall. Such integration may also enhance partnership with national governments whose mandates extend beyond HIV and to all of health care. Finally, we see a need for there to be substantial and equitable investment in capacity strengthening within African countries, so that African researchers will increasingly be leading modelling exercises. Building a critical mass of expertise, strengthened through external collaboration and knowledge exchange, should be the ultimate goal.