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UNAIDS and a broad range of partners have collaborated to establish a new set of HIV prevention targets to be achieved by 2025 as an intermediate step towards the sustainable development target for 2030. The number of new HIV infections in the world continues to decline, in part due to the extraordinary expansion of effective HIV treatment. However, the decline is geographically heterogeneous, with some regions reporting a rise in incidence. The incidence target that was agreed for 2020 has been missed. A range of exciting new HIV prevention technologies have become available or are in the pipeline but will only have an impact if they are accessible and affordable and delivered within systems that take full account of the social and political context in which most infections occur. Most new infections occur in populations that are marginalised or discriminated against due to structural, legal, and cultural barriers. The new targets imply a new approach to HIV prevention that emphasises appropriate, person-centred, prioritised, effective, combination HIV prevention within a framework that reduces existing barriers to services and acknowledges heterogeneity, autonomy, and choice. These targets have consequences for people working in HIV programmes both for delivery and for monitoring and evaluation, for health planners setting local and national priorities, and for funders both domestic and global. Most importantly, they have consequences for people who are at risk of HIV exposure and infection. Achieving these targets will have a huge impact on the future of the HIV epidemic and put us back on track towards ending AIDS as a public health threat by 2030., Author(s): Peter Godfrey-Faussett 1,2,*, Luisa Frescura 1, Quarraisha Abdool Karim 3, Michaela Clayton 4, Peter D. Ghys 1,(on behalf of the 2025 prevention targets working group) Introduction Course correction needed [...]

Introduction: Due to the nature of funding, national planners and international donors typically balance budgets over short time periods when designing HIV programmes (~5-year funding cycles). We aim to explicitly quantify the cost of short-term funding arrangements on the success of future HIV prevention programmes. Methods: Using mathematical models of HIV transmission in Kenya, we compare the impact of optimized combination prevention strategies under different constraints on investment over time. Each scenario has the same total budget for the 30-year intervention period but the pattern of spending over time is allowed to vary. We look at the impact of programmes with decreasing, increasing or constant spending across 5-year funding cycles for a 30-year period. Interventions are optimized within each funding cycle such that strategies take a short-term view of the epidemic. We compare these with two strategies with no spending pattern constraints: one with static intervention choices and another flexible strategy with interventions changed in year ten. Results and Discussion: For the same total 30-year budget, greatest impact is achieved if larger initial prevention spending is offset by later treatment savings which leads to accumulating benefits in reduced infections. The impact under funding cycle constraints is determined by the extent to which greater initial spending is permitted. Short-term funding constraints and funds held back to later years may reduce impact by up to 18% relative to the flexible long-term strategy. Conclusions: Ensuring that funding arrangements are in place to support long-term prevention strategies will make spending most impactful. Greater prevention spending now will bring considerable returns through reductions in new infections, greater population health and reductions in the burden on health services in the future. Keywords: HIV Prevention; healthcare financing; health policy; mathematical modelling; programme planning, 1 | INTRODUCTION Renewed prevention efforts will be critical to future success in the control of the HIV epidemic. Despite substantial progress since the peak of the epidemic in 1997 [...]

Background UNAIDS has established new program targets for 2025 to achieve the goal of eliminating AIDS as a public health threat by 2030. This study reports on efforts to use mathematical models to estimate the impact of achieving those targets. Methods and findings We simulated the impact of achieving the targets at country level using the Goals model, a mathematical simulation model of HIV epidemic dynamics that includes the impact of prevention and treatment interventions. For 77 high-burden countries, we fit the model to surveillance and survey data for 1970 to 2020 and then projected the impact of achieving the targets for the period 2019 to 2030. Results from these 77 countries were extrapolated to produce estimates for 96 others. Goals model results were checked by comparing against projections done with the Optima HIV model and the AIDS Epidemic Model (AEM) for selected countries. We included estimates of the impact of societal enablers (access to justice and law reform, stigma and discrimination elimination, and gender equality) and the impact of Coronavirus Disease 2019 (COVID-19). Results show that achieving the 2025 targets would reduce new annual infections by 83% (71% to 86% across regions) and AIDS-related deaths by 78% (67% to 81% across regions) by 2025 compared to 2010. Lack of progress on societal enablers could endanger these achievements and result in as many as 2.6 million (44%) cumulative additional new HIV infections and 440,000 (54%) more AIDS-related deaths between 2020 and 2030 compared to full achievement of all targets. COVID-19-related disruptions could increase new HIV infections and AIDS-related deaths by 10% in the next 2 years, but targets could still be achieved by 2025. Study limitations include the reliance on self-reports for most data on behaviors, the use of intervention effect sizes from published studies that may overstate intervention impacts outside of controlled study settings, and the use of proxy countries to estimate the impact in countries with fewer than 4,000 annual HIV infections. Conclusions The new targets for 2025 build on the progress made since 2010 and represent ambitious short-term goals. Achieving these targets would bring us close to the goals of reducing new HIV infections and AIDS-related deaths by 90% between 2010 and 2030. By 2025, global new infections and AIDS deaths would drop to 4.4 and 3.9 per 100,000 population, and the number of people living with HIV (PLHIV) would be declining. There would be 32 million people on treatment, and they would need continuing support for their lifetime. Incidence for the total global population would be below 0.15% everywhere. The number of PLHIV would start declining by 2023., Author(s): John Stover 1,*, Robert Glaubius 1, Yu Teng 1, Sherrie Kelly 2, Tim Brown 3, Timothy B. Hallett 4, Paul Revill 5, Till Bärnighausen 6, Andrew N. Phillips 7, [...]

Author(s): Paul R. De Lay 1,*, Adèle Benzaken 2, Quarraisha Abdool Karim 3,4, Sani Aliyu 5, Carolyn Amole 6, George Ayala 7, Kalipso Chalkidou 8, Judy Chang 9, Michaela Clayton [...]

Introduction: A strategic approach to the application of HIV prevention interventions is a core component of the UNAIDS Fast Track strategy to end the HIV epidemic by 2030. Central to these plans is a focus on high-prevalence geographies, in a bid to target resources to those in greatest need and maximize the reduction in new infections. Whilst this idea of geographical prioritization has the potential to improve efficiency it is unclear how it should be implemented in practice. There are a range of prevention interventions which can be applied differentially across risk groups and locations, making allocation decisions complex. Here, we use mathematical modelling to compare the impact (infections averted) of a number of different approaches to the implementation of geographical prioritization of prevention interventions, similar to those emerging in policy and practice, across a range of prevention budgets.Methods: We use geographically specific mathematical models of the epidemic and response in 48 counties and major cities of Kenya to project the impact of the different geographical prioritization approaches. We compare the geographical allocation strategies with a nationally uniform approach under which the same interventions must be applied across all modelled locations.Results: We find that the most extreme geographical prioritization strategy, which focuses resources exclusively to high-prevaence locations, may substantially restrict impact (41% fewer infections averted) compared to a nationally uniform approach, as opportunities for highly effective interventions for high-risk populations in lower-prevalence areas are missed. Other geographical allocation approaches, which intensify efforts in higher-prevalence areas whilst maintaining a minimum package of cost-effective interventions everywhere, consistently improve impact at all budget levels. Such strategies balance the need for greater investment in locations with the largest epidemics whilst ensuring higher-risk groups in lower-priority locations are provided with cost-effective interventions.Conclusions: Our findings serve as a warning to not be too selective in the application of prevention strategies. Further research is needed to understand how decision-makers can find the right balance between the choice of interventions, focus on high-risk populations, and geographical targeting to ensure the greatest impact of HIV prevention.Keywords: geographical prioritization; epidemiology; mathematical modelling; health policy; HIV prevention; resource allocationTo access the supplementary material to this article please see Supplementary Files under Article Tools online., 1 | INTRODUCTIONGeographically specific intervention programming is commonly used in the control of a number of major infectious diseases, most notably those caused by vector-borne agents such as malaria or [...]

This paper reviews the data sources and methods used to estimate the number of people on, and coverage of, antiretroviral therapy (ART) programmes in low- and middle-income countries and to monitor the progress towards the "3 by 5" target set by WHO and UNAIDS. We include a review of the data sources used to estimate the coverage of ART programmes as well as the efforts made to avoid double counting and over-reporting. The methods used to estimate the number of people in need of ART are described and expanded with estimates of treatment needs for children, both for ART and for cotrimoxazole prophylaxis. An estimated 6.5 million people were in need of treatment in low- and middle-income countries by the end of 2004, including 660 000 children under age 15 years. The mid-2005 estimate of 970 000 people receiving ART in low- and middle-income countries (with an uncertainty range 840 000-1 100 000) corresponds to a coverage of 15% of people in need of treatment.

The modes of transmission model has been widely used to help decision-makers target measures for preventing human immunodeficiency virus (HIV) infection. The model estimates the number of new HIV infections that will be acquired over the ensuing year by individuals in identified risk groups in a given population using data on the size of the groups, the aggregate risk behaviour in each group, the current prevalence of HIV infection among the sexual or injecting drug partners of individuals in each group, and the probability of HIV transmission associated with different risk behaviours. The strength of the model is its simplicity, which enables data from a variety of sources to be synthesized, resulting in better characterization of HIV epidemics in some settings. However, concerns have been raised about the assumptions underlying the model structure, about limitations in the data available for deriving input parameters and about interpretation and communication of the model results. The aim of this review was to improve the use of the model by reassessing its paradigm, structure and data requirements. We identified key questions to be asked when conducting an analysis and when interpreting the model results and make recommendations for strengthening the model's application in the future. Le modele de modes de transmission a ete largement utilise pour aider les decideurs a cibler les mesures empechant l'infection par le virus d'immunodeficience humaine (VIH). Le modete estime le nombre de nouvelles infections par leVIH au cours de l'annee suivante, contractees par des individus appartenant aux groupes a risque identifies d'une population donnee, en utilisant des donnees sur la taille des groupes, le comportement a risque global de chaque groupe, la prevalence actuelle de l'infection par le VIH entre partenaires sexuels ou d'injection de drogues de chaque groupe, et la probabilite de transmission du VIH associee aux divers comportements a risque. La force du modele reside dans sa simplicite, permettant de synthetiser des donnees provenant d'une variete de sources, ce qui donne une meilleure caracterisation de I'epidemie du VIH dans certains contextes. Toutefois, des problemes ont ete releves concernant les hypotheses qui sous-tendent la structure du modele, les limites des donnees disponibles pour obtenir les parametres d'entree, ainsi que l'interpretation et la communication des resultats du modele. L'objectif de la presente etude etait d'ameliorer l'utilisation du modele en reevaluant son paradigme, sa structure et ses exigences en termes de donnees. Nous avons identifie les principales questions a poser lors de l'analyse et de l'interpretation des resultats du modele, et nous faisons des recommandations visant a renforcer l'application du modele a l'avenir. El modelo de los modos de transmision se ha empteado de manera cjeneralizada para ayudar a los responsables de la toma de decisiones a dirigir las medidas para la prevencion de la infeccion por el virus de la inmunodehciencia humana (VIH). El modelo calcula el numero de infecciones porVIH nuevas adquiridas durante el ano subsiguiente por individuos en grupos de riesgo identificados en una poblacion dada empleando datos acerca del tamano de los grupos, el comportamiento de riescjo conjunto en cada grupo, la prevalencia actual de la infeccion por VIH entre las parejas sexuales o personas que comparten jeringuillas para el consumo de drogas de los individuos de cada grupo y la probabilidad de trasmitir elVIH asociada a los diferentes comportamientos de riesgo. El punto fuerte del modelo es su sencillez, que permite sintetizar datos de fuentes variadas, de lo que resulta una caracterizacion mas exacta de la epidemia del VIM en algunos entornos. No obstante, han surgido dudas acerca de las suposiciones que subyacen a la estructura del modelo, las limitaciones de los datos disponibles para derivar de ellos parametros de entrada y la interpretacion y comunicacion de los resultados dei modelo. El objeto de este examen fue el de mejorar el uso del modelo volviendo a examinar su paradigma, su estructura y los requisitos de los datos. Identificamos los puntos clave que deben cuestionarse durante la realizacion de un analisis y la interpretacion de los resultados dei modelo y formulamos recomendaciones para consolidar la aplicacion del modelo en el futuro., Introduction In the current global financial climate, it is more important than ever that effective resource allocation for the control of human immunodeficiency virus (HIV) infection is based on informed, [...]

In December 2020, UNAIDS released a new set of ambitious targets calling for 95% of all people living with HIV to know their HIV status, 95% of all people with diagnosed HIV infection to receive sustained antiretroviral therapy, and 95% of all people receiving antiretroviral therapy to have viral suppression by 2025. Adopted by United Nations Member states in June 2021 as part of the new Political Declaration on HIV and AIDS, these targets, combined with ambitious primary prevention targets and focused attention to supporting enablers, aim to bridge inequalities in treatment coverage and outcomes and accelerate HIV incidence reductions by focusing on progress in all sub-populations, age groups and geographic settings. Here we summarise the evidence and decisions underpinning the new global targets. [ABSTRACT FROM AUTHOR]

We assessed the impact of HIV-1 on malaria in the sub-Saharan African population. Relative risks for malaria in HIV-infected persons, derived from literature review, were applied to the HIV-infected population [...]