Suchergebnisse

Indonesia is the third largest contributor to the global tuberculosis (TB) burden and among the top twenty countries in the world for TB-HIV (human immunodeficiency virus) coinfection, and multidrug-resistant TB (MDR-TB). In addition to the significant toll of TB to health and human capital, the economic burden of TB is substantial. Controlling TB in Indonesia will require not only that the Government of Indonesia (GOI) spend more on TB but that it spend it better. This means that decisions on which interventions or programs to prioritize and how best to implement them will be critical to maximizing health outcomes. Projections indicate that TB incidence will remain relatively stagnant under status quo spending and that there is limited scope for improving allocative efficiency. Following a request for technical assistance from the Government of Indonesia (GOI) on how to make available TB resources go further, especially in a context of shrinking external funding, consultations were held with program managers and experts in the National TB Program, the Ministry of Health, and the Ministry of Finance. Optima TB is a mathematical optimization model that informs policy makers and program managers on how to allocate the available resources across TB programs to maximize impact. This report covers the findings from an Optima TB analysis conducted in Indonesia as of September 2020.

Objective::Prices of antiretroviral (ARV) drugs in lower income countries have decreased substantially over the past two decades, helping to facilitate greatly expanded access to antiretroviral therapy (ART). However, ART coverage in many parts of the world remains low. We investigate the extent of epidemiological benefits that might be expected if ARV drug prices decline further.Design:A modeling study using data from seven countries in West and Central Africa (Cameroon, Democratic Republic of the Congo, Côte d'Ivoire, Niger, Nigeria, Senegal, and Togo).Methods:We investigated how the timing of ARV cost reductions could affect the impact and compared three different possible investment strategies: reinvesting in ART, reinvesting in the HIV response according to historical allocations, and reinvesting with the aim of minimizing HIV incidence and mortality.Results:If ARV drug prices fell by 37% relative to 2018 levels (i.e. following continued trend declines), we calculate ART unit costs could decrease by ∼20% (holding other cost components constant). If this could be achieved by 2020 and the savings were reinvested into ART, we estimate that an additional 8% of HIV infections and 11% of HIV-related deaths could be averted over 2020-2030 across the seven countries. Slightly greater gains could be attained if funds were reinvested in ART in combination with primary prevention. Delays in the year of introduction of ARV price reductions would reduce the impact by about 1% per year.Conclusion:ARV price reductions could free up funds that - if strategically invested - would help countries move closer toward the elimination of HIV.

AbstractIntroductionWith limited funds available, meeting global health targets requires countries to both mobilize and prioritize their health spending. Within this context, countries have recognized the importance of allocating funds for HIV as efficiently as possible to maximize impact. Over the past six years, the governments of 23 countries in Africa, Asia, Eastern Europe and Latin America have used the Optima HIV tool to estimate the optimal allocation of HIV resources.MethodsEach study commenced with a request by the national government for technical assistance in conducting an HIV allocative efficiency study using Optima HIV. Each study team validated the required data, calibrated the Optima HIV epidemic model to produce HIV epidemic projections, agreed on cost functions for interventions, and used the model to calculate the optimal allocation of available funds to best address national strategic plan targets. From a review and analysis of these 23 country studies, we extract common themes around the optimal allocation of HIV funding in different epidemiological contexts.Results and discussionThe optimal distribution of HIV resources depends on the amount of funding available and the characteristics of each country's epidemic, response and targets. Universally, the modelling results indicated that scaling up treatment coverage is an efficient use of resources. There is scope for efficiency gains by targeting the HIV response towards the populations and geographical regions where HIV incidence is highest. Across a range of countries, the model results indicate that a more efficient allocation of HIV resources could reduce cumulative new HIV infections by an average of 18% over the years to 2020 and 25% over the years to 2030, along with an approximately 25% reduction in deaths for both timelines. However, in most countries this would still not be sufficient to meet the targets of the national strategic plan, with modelling results indicating that budget increases of up to 185% would be required.ConclusionsGreater epidemiological impact would be possible through better targeting of existing resources, but additional resources would still be required to meet targets. Allocative efficiency models have proven valuable in improving the HIV planning and budgeting process.

With limited funds available, meeting global health targets requires countries to both mobilize and prioritize their health spending. Within this context, countries have recognized the importance of allocating funds for HIV as efficiently as possible to maximize impact. Over the past six years, the governments of 23 countries in Africa, Asia, Eastern Europe and Latin America have used the Optima HIV tool to estimate the optimal allocation of HIV resources.

INTRODUCTION: With limited funds available, meeting global health targets requires countries to both mobilize and prioritize their health spending. Within this context, countries have recognized the importance of allocating funds for HIV as efficiently as possible to maximize impact. Over the past six years, the governments of 23 countries in Africa, Asia, Eastern Europe and Latin America have used the Optima HIV tool to estimate the optimal allocation of HIV resources. METHODS: Each study commenced with a request by the national government for technical assistance in conducting an HIV allocative efficiency study using Optima HIV. Each study team validated the required data, calibrated the Optima HIV epidemic model to produce HIV epidemic projections, agreed on cost functions for interventions, and used the model to calculate the optimal allocation of available funds to best address national strategic plan targets. From a review and analysis of these 23 country studies, we extract common themes around the optimal allocation of HIV funding in different epidemiological contexts. RESULTS AND DISCUSSION: The optimal distribution of HIV resources depends on the amount of funding available and the characteristics of each country's epidemic, response and targets. Universally, the modelling results indicated that scaling up treatment coverage is an efficient use of resources. There is scope for efficiency gains by targeting the HIV response towards the populations and geographical regions where HIV incidence is highest. Across a range of countries, the model results indicate that a more efficient allocation of HIV resources could reduce cumulative new HIV infections by an average of 18% over the years to 2020 and 25% over the years to 2030, along with an approximately 25% reduction in deaths for both timelines. However, in most countries this would still not be sufficient to meet the targets of the national strategic plan, with modelling results indicating that budget increases of up to 185% would be required. CONCLUSIONS: Greater epidemiological impact would be possible through better targeting of existing resources, but additional resources would still be required to meet targets. Allocative efficiency models have proven valuable in improving the HIV planning and budgeting process.

INTRODUCTION With limited funds available, meeting global health targets requires countries to both mobilize and prioritize their health spending. Within this context, countries have recognized the importance of allocating funds for HIV as efficiently as possible to maximize impact. Over the past six years, the governments of 23 countries in Africa, Asia, Eastern Europe and Latin America have used the Optima HIV tool to estimate the optimal allocation of HIV resources. METHODS Each study commenced with a request by the national government for technical assistance in conducting an HIV allocative efficiency study using Optima HIV. Each study team validated the required data, calibrated the Optima HIV epidemic model to produce HIV epidemic projections, agreed on cost functions for interventions, and used the model to calculate the optimal allocation of available funds to best address national strategic plan targets. From a review and analysis of these 23 country studies, we extract common themes around the optimal allocation of HIV funding in different epidemiological contexts. RESULTS AND DISCUSSION The optimal distribution of HIV resources depends on the amount of funding available and the characteristics of each country's epidemic, response and targets. Universally, the modelling results indicated that scaling up treatment coverage is an efficient use of resources. There is scope for efficiency gains by targeting the HIV response towards the populations and geographical regions where HIV incidence is highest. Across a range of countries, the model results indicate that a more efficient allocation of HIV resources could reduce cumulative new HIV infections by an average of 18% over the years to 2020 and 25% over the years to 2030, along with an approximately 25% reduction in deaths for both timelines. However, in most countries this would still not be sufficient to meet the targets of the national strategic plan, with modelling results indicating that budget increases of up to 185% would be required. CONCLUSIONS Greater epidemiological impact would be possible through better targeting of existing resources, but additional resources would still be required to meet targets. Allocative efficiency models have proven valuable in improving the HIV planning and budgeting process.

INTRODUCTION: With limited funds available, meeting global health targets requires countries to both mobilize and prioritize their health spending. Within this context, countries have recognized the importance of allocating funds for HIV as efficiently as possible to maximize impact. Over the past six years, the governments of 23 countries in Africa, Asia, Eastern Europe and Latin America have used the Optima HIV tool to estimate the optimal allocation of HIV resources. METHODS: Each study commenced with a request by the national government for technical assistance in conducting an HIV allocative efficiency study using Optima HIV. Each study team validated the required data, calibrated the Optima HIV epidemic model to produce HIV epidemic projections, agreed on cost functions for interventions, and used the model to calculate the optimal allocation of available funds to best address national strategic plan targets. From a review and analysis of these 23 country studies, we extract common themes around the optimal allocation of HIV funding in different epidemiological contexts. RESULTS AND DISCUSSION: The optimal distribution of HIV resources depends on the amount of funding available and the characteristics of each country's epidemic, response and targets. Universally, the modelling results indicated that scaling up treatment coverage is an efficient use of resources. There is scope for efficiency gains by targeting the HIV response towards the populations and geographical regions where HIV incidence is highest. Across a range of countries, the model results indicate that a more efficient allocation of HIV resources could reduce cumulative new HIV infections by an average of 18% over the years to 2020 and 25% over the years to 2030, along with an approximately 25% reduction in deaths for both timelines. However, in most countries this would still not be sufficient to meet the targets of the national strategic plan, with modelling results indicating that budget increases of up to 185% would be required. CONCLUSIONS: Greater epidemiological impact would be possible through better targeting of existing resources, but additional resources would still be required to meet targets. Allocative efficiency models have proven valuable in improving the HIV planning and budgeting process.

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.