The Full Value of Vaccine Assessments (FVVA): a framework for assessing and communicating the value of vaccines for investment and introduction decision-making.

BACKGROUND: Several economic obstacles can deter the development and use of vaccines. This can lead to limited product options for some diseases, delays in new product development, and inequitable access to vaccines. Although seemingly distinct, these obstacles are actually interrelated and therefore need to be addressed through a single over-arching strategy encompassing all stakeholders. METHODS: To help overcome these obstacles, we propose a new approach, the Full Value of Vaccines Assessments (FVVA) framework, to guide the assessment and communication of the value of a vaccine. The FVVA framework is designed to facilitate alignment across key stakeholders and to enhance decision-making around investment in vaccine development, policy-making, procurement, and introduction, particularly for vaccines intended for use in low- and middle-income countries. RESULTS: The FVVA framework has three key elements. First, to enhance assessment, existing value-assessment methods and tools are adapted to include broader benefits of vaccines as well as opportunity costs borne by stakeholders. Second, to improve decision-making, a deliberative process is required to recognize the agency of stakeholders and to ensure country ownership of decision-making and priority setting. Third, the FVVA framework provides a consistent and evidence-based approach that facilitates communication about the full value of vaccines, helping to enhance alignment and coordination across diverse stakeholders. CONCLUSIONS: The FVVA framework provides guidance for stakeholders organizing global-level efforts to promote investment in vaccines that are priorities for LMICs. By providing a more holistic view of the benefits of vaccines, its application also has the potential to encourage greater take-up by countries, thereby leading to more sustainable and equitable impacts of vaccines and immunization programmes.

The Macroeconomic Impact of Increasing Investments in Malaria Control in 26 High Malaria Burden Countries: An Application of the Updated EPIC Model.

BACKGROUND: Malaria remains a major public health problem. While globally malaria mortality affects predominantly young children, clinical malaria affects all age groups throughout life. Malaria not only threatens health but also child education and adult productivity while burdening government budgets and economic development. Increased investments in malaria control can contribute to reduce this burden but have an opportunity cost for the economy. Quantifying the net economic value of investing in malaria can encourage political and financial commitment. METHODS: We adapted an existing macroeconomic model to simulate the effects of reducing malaria on the gross domestic product (GDP) of 26 high burden countries while accounting for the opportunity costs of increased investments in malaria. We compared two scenarios differing in their level of malaria investment and associated burden reduction: sustaining malaria control at 2015 intervention coverage levels, time at which coverage levels reached their historic peak and scaling-up coverage to reach the 2030 global burden reduction targets. We incorporated the effects that reduced malaria in children and young adolescents may have on the productivity of working adults and on the future size of the labour force augmented by educational returns, skills, and experience. We calibrated the model using estimates from linked epidemiologic and costing models on these same scenarios and from published country-specific macroeconomic data. RESULTS: Scaling-up malaria control could produce a dividend of US$ 152 billion in the modelled countries, equivalent to 0.17% of total GDP projected over the study period across the 26 countries. Assuming a larger share of malaria investments is paid out from domestic savings, the dividend would be smaller but still significant, ranging between 0.10% and 0.14% of total projected GDP. Annual GDP gains were estimated to increase over time. Lower income and higher burden countries would experience higher gains. CONCLUSION: Intensified malaria control can produce a multiplied return despite the opportunity cost of greater investments.

Methods for the Economic Evaluation of Health Care Interventions for Priority Setting in the Health System: An Update From WHO CHOICE.

The World Health Organization's (WHO's) Choosing Interventions that are Cost-Effective (CHOICE) programme has been a global leader in the field of economic evaluation, specifically cost-effectiveness analysis for almost 20 years. WHO-CHOICE takes a "generalized" approach to cost-effectiveness analysis that can be seen as a quantitative assessment of current and future efficiency within a health system. This supports priority setting processes, ensuring that health stewards know how to spend resources in order to achieve the highest health gain as one consideration in strategic planning. This approach is unique in the global health landscape. This paper provides an overview of the methodological approach, updates to analytic framework over the past 10 years, and the added value of the WHO-CHOICE approach in supporting decision makers as they aim to use limited health resources to achieve the Sustainable Development Goals (SDGs) by 2030.

Progressive Realisation of Universal Health Coverage in Low- and Middle-Income Countries: Beyond the "Best Buys".

BACKGROUND: World Health Organization Choosing Interventions that are Cost-Effective (WHO CHOICE) has been a programme of the WHO for 20 years. In this latest update, we present for the first time a cross-programme analysis of the comparative cost-effectiveness of 479 intervention scenarios across 20 disease programmes and risk factors. METHODS: This analysis follows the standard WHO CHOICE approach to generalized cost-effectiveness analysis applied to two regions, Eastern sub-Saharan Africa and Southeast Asia. The scope of the analysis is all interventions included in programme specific WHO CHOICE analyses, using WHO treatment guidelines for major disease areas as the foundation. Costs are measured in 2010 international dollars, and benefits modelled beginning in 2010, or the nearest year for which validated data was available, both for a period of 100 years. RESULTS: Across both regions included in the analysis, interventions span multiple orders of magnitude in terms of cost-effectiveness ratios. A health benefit package optimized through a value for money lens incorporates interventions responding to all of the main drivers of disease burden. Interventions delivered through first level clinical and non-clinical services represent the majority of the high impact cost-effective interventions. CONCLUSION: Cost-effectiveness is one important criterion when selecting health interventions for benefit packages to progress towards universal health coverage (UHC), but it is not the only criterion and all calculations should be adapted to the local context. To support country decision-makers, WHO CHOICE has developed a downloadable tool to support the development of data for this criterion.

Priority Setting in HIV, Tuberculosis, and Malaria - New Cost-Effectiveness Results From WHO-CHOICE.

BACKGROUND: This paper forms part of an update of the World Health Organization Choosing Interventions that are Cost-Effective (WHO-CHOICE) programmes. It provides an assessment of global health system performance during the first decade of the 21st century (2000-2010) with respect to allocative efficiency in HIV, tuberculosis (TB) and malaria control, thereby shining a spotlight on programme development and scale up in these Millennium Development Goal (MDG) priority areas; and examining the cost-effectiveness of selected best-practice interventions and intervention packages commonly in use during that period. METHODS: Generalized cost-effectiveness analysis (GCEA) was used to determine the cost-effectiveness of the selected interventions. Impact modelling was performed using the OpenMalaria platform for malaria and using the Goals and TIME (TB Impact Model and Estimates) models in Spectrum for HIV and TB. All health system costs, regardless of payer, were included and reported in international dollars. Health outcomes are estimated and reported as the gain in healthy life years (HLYs) due to the specific intervention or combination. Analysis was restricted to eastern sub-Saharan Africa and Southeast Asia. RESULTS: At the reference year of 2010, commonly used interventions for HIV, TB and malaria were cost-effective, with cost-effectiveness ratios less than I$ 100/HLY saved for virtually all interventions included. HIV, TB and malaria prevention and treatment interventions are highly cost-effective and can be implemented through a phased approach to full coverage to achieve maximum health benefits and contribute to the progressive elimination of these diseases. CONCLUSION: During the first decade of the 21st century (2000-2010), the global community has done well overall for HIV, TB, and malaria programmes as regards both economic efficiency and programmatic selection criteria. The role of international assistance, financial and technical, arguably was critical to these successes. As the global community now tackles the challenge of universal health coverage, this analysis can reinforce commitment to Sustainable Development Goal targets but also the importance of continued focus on these critical programme areas.

Cost-Effectiveness of Testing and Treatment for Hepatitis B Virus and Hepatitis C Virus Infections: An Analysis by Scenarios, Regions, and Income.

OBJECTIVES: Testing and treatment for hepatitis B virus (HBV) and hepatitis C virus (HCV) infection are highly effective, high-impact interventions. This article aims to estimate the cost-effectiveness of scaling up these interventions by scenarios, regions, and income groups. METHODS: We modeled costs and impacts of hepatitis elimination in 67 low- and middle-income countries from 2016 to 2030. Costs included testing and treatment commodities, healthcare consultations, and future savings from cirrhosis and hepatocellular carcinomas averted. We modeled disease progression to estimate disability-adjusted life-years (DALYs) averted. We estimated incremental cost-effectiveness ratios (ICERs) by regions and World Bank income groups, according to 3 scenarios: flatline (status quo), progress (testing/treatment according to World Health Organization guidelines), and ambitious (elimination). RESULTS: Compared with no action, current levels of testing and treatment had an ICER of $807/DALY for HBV and -$62/DALY (cost-saving) for HCV. Scaling up to progress scenario, both interventions had ICERs less than the average gross domestic product/capita of countries (HBV: $532/DALY; HCV: $613/DALY). Scaling up from flatline to elimination led to higher ICERs across countries (HBV: $927/DALY; HCV: $2528/DALY, respectively) that remained lower than the average gross domestic product/capita. Sensitivity analysis indicated discount rates and commodity costs were main factors driving results. CONCLUSIONS: Scaling up testing and treatment for HBV and HCV infection as per World Health Organization guidelines is a cost-effective intervention. Elimination leads to a much larger impact though ICERs are higher. Price reduction strategies are needed to achieve elimination given the substantial budget impact at current commodity prices.

Analysis of Mammography Screening Schedules under Varying Resource Constraints for Planning Breast Cancer Control Programs in Low- and Middle-Income Countries: A Mathematical Study.

Background. Low-and-middle-income countries (LMICs) have higher mortality-to-incidence ratio for breast cancer compared to high-income countries (HICs) because of late-stage diagnosis. Mammography screening is recommended for early diagnosis, however, the infrastructure capacity in LMICs are far below that needed for adopting current screening guidelines. Current guidelines are extrapolations from HICs, as limited data had restricted model development specific to LMICs, and thus, economic analysis of screening schedules specific to infrastructure capacities are unavailable. Methods. We applied a new Markov process method for developing cancer progression models and a Markov decision process model to identify optimal screening schedules under a varying number of lifetime screenings per person, a proxy for infrastructure capacity. We modeled Peru, a middle-income country, as a case study and the United States, an HIC, for validation. Results. Implementing 2, 5, 10, and 15 lifetime screens would require about 55, 135, 280, and 405 mammography machines, respectively, and would save 31, 62, 95, and 112 life-years per 1000 women, respectively. Current guidelines recommend 15 lifetime screens, but Peru has only 55 mammography machines nationally. With this capacity, the best strategy is 2 lifetime screenings at age 50 and 56 years. As infrastructure is scaled up to accommodate 5 and 10 lifetime screens, screening between the ages of 44-61 and 41-64 years, respectively, would have the best impact. Our results for the United States are consistent with other models and current guidelines. Limitations. The scope of our model is limited to analysis of national-level guidelines. We did not model heterogeneity across the country. Conclusions. Country-specific optimal screening schedules under varying infrastructure capacities can systematically guide development of cancer control programs and planning of health investments.

Adjusting for Inflation and Currency Changes Within Health Economic Studies.

OBJECTIVES: Within health economic studies, it is often necessary to adjust costs obtained from different time periods for inflation. Nevertheless, many studies do not report the methods used for this in sufficient detail. In this article, we outline the principal methods used to adjust for inflation, with a focus on studies relating to healthcare interventions in low- and middle-income countries. We also discuss issues relating to converting local currencies to international dollars and US$ and adjusting cost data collected from other countries or previous studies. METHODS: We outlined the 3 main methods used to adjust for inflation for studies in these settings: exchanging the local currency to US$ or international dollars and then inflating using US inflation rates (method 1); inflating the local currency using local inflation rates and then exchanging to US$ or international dollars (method 2); splitting the costs into tradable and nontradable resources and using method 1 on the tradable resources and method 2 on the nontradable resources (method 3). RESULTS: In a hypothetical example of adjusting a cost of US$100 incurred in Vietnam from 2006 to 2016 prices, the adjusted cost from the 3 methods were US$116.84, US$172.09, and US$161.04, respectively. CONCLUSIONS: The different methods for adjusting for inflation can yield substantially different results. We make recommendations regarding the most appropriate method for various scenarios. Moving forward, it is vital that studies report the methodology they use to adjust for inflation more transparently.

Additional resource needs for viral hepatitis elimination through universal health coverage: projections in 67 low-income and middle-income countries, 2016-30.

BACKGROUND: The World Health Assembly calls for elimination of viral hepatitis as a public health threat by 2030 (ie, -90% incidence and -65% mortality). However, WHO's 2017 cost projections to achieve health-related Sustainable Development Goals did not include the resources needed for hepatitis testing and treatment. We aimed to estimate the incremental commodity cost of adding scaled up interventions for testing and treatment of hepatitis to WHO's investment scenarios. METHODS: We added modelled costs for implementing WHO recommended hepatitis testing and treatment to the 2017 WHO cost projections. We quantified additional requirements for diagnostic tests, medicines, health workers' time, and programme support across 67 low-income and middle-income countries, from 2016-30. A progress scenario scaled up interventions and a more ambitious scenario was modelled to reach elimination by 2030. We used 2018 best available prices of diagnostics and generic medicines. We estimated total costs and the additional investment needed over the projection of the 2016 baseline cost. FINDINGS: The 67 countries considered included 230 million people living with hepatitis B virus (HBV) and 52 million people living with hepatitis C virus (HCV; 90% and 73% of the world's total, respectively). Under the progress scenario, 3250 million people (2400 million for HBV and 850 million for HCV) would be tested and 58·2 million people (24·1 million for HBV and 34·1 million for HCV) would be treated (total additional cost US$ 27·1 billion). Under the ambitious scenario, 11 631 million people (5502 million for HBV and 6129 million for HCV) would be tested and 93·8 million people (32·2 million for HBV and 61·6 million for HCV) would be treated (total additional cost $58·7 billion), averting 4·5 million premature deaths and leading to a gain of 51·5 million healthy life-years by 2030. However, if affordable HCV medicines remained inaccessible in 13 countries where medicine patents are protected, the additional cost of the ambitious scenario would increase to $118 billion. Hepatitis elimination would account for a 1·5% increase to the WHO ambitious health-care strengthening scenario costs, avert an additional 4·6% premature deaths, and add an additional 9·6% healthy life-years from 2016-30. INTERPRETATION: Access to affordable medicines in all countries will be key to reach hepatitis elimination. This study suggests that elimination is feasible in the context of universal health coverage. It points to commodities as key determinants for the overall price tag and to options for cost reduction strategies. FUNDING: WHO, United States Centers for Disease Control and Prevention, Unitaid.

Cost-effective interventions for breast cancer, cervical cancer, and colorectal cancer: new results from WHO-CHOICE.

BACKGROUND: Following the adoption of the Global Action Plan for the Prevention and Control of NCDs 2013-2020, an update to the Appendix 3 of the action plan was requested by Member States in 2016, endorsed by the Seventieth World Health Assembly in May 2017 and provides a list of recommended NCD interventions. The main contribution of this paper is to present results of analyses identifying how decision makers can achieve maximum health gain using the cancer interventions listed in the Appendix 3. We also present methods used to calculate new WHO-CHOICE cost-effectiveness results for breast cancer, cervical cancer, and colorectal cancer in Southeast Asia and eastern sub-Saharan Africa. METHODS: We used "Generalized Cost-Effectiveness Analysis" for our analysis which uses a hypothetical null reference case, where the impacts of all current interventions are removed, in order to identify the optimal package of interventions. All health system costs, regardless of payer, were included. Health outcomes are reported as the gain in healthy life years due to a specific intervention scenario and were estimated using a deterministic state-transition cohort simulation (Markov model). RESULTS: Vaccination against human papillomavirus (two doses) for 9-13-year-old girls (in eastern sub-Saharan Africa) and HPV vaccination combined with prevention of cervical cancer by screening of women aged 30-49 years through visual inspection with acetic acid linked with timely treatment of pre-cancerous lesions (in Southeast Asia) were found to be the most cost effective interventions. For breast cancer, in both regions the treatment of breast cancer, stages I and II, with surgery ± systemic therapy, at 95% coverage, was found to be the most cost-effective intervention. For colorectal cancer, treatment of colorectal cancer, stages I and II, with surgery ± chemotherapy and radiotherapy, at 95% coverage, was found to be the most cost-effective intervention. CONCLUSION: The results demonstrate that cancer prevention and control interventions are cost-effective and can be implemented through a step-wise approach to achieve maximum health benefits. As the global community moves toward universal health coverage, this analysis can support decision makers in identifying a core package of cancer services, ensuring treatment and palliative care for all.

Cost-effectiveness of strategies to prevent road traffic injuries in eastern sub-Saharan Africa and Southeast Asia: new results from WHO-CHOICE.

BACKGROUND: Road safety has been receiving increased attention through the United Nations Decade of Action on Road Safety, and is also now specifically addressed in the sustainable development goals 3.6 and 11.2. In an effort to enhance the response to Road Traffic Injuries (RTIs), this paper aims to examine the cost effectiveness of proven preventive interventions and forms part of an update of the WHO-CHOICE programme. METHODS: Generalized cost-effectiveness analysis (GCEA) approach was used for our analysis. GCEA applies a null reference case, in which the effects of currently implemented interventions are subtracted from current rates of burden, in order to identify the most efficient package of interventions. A population model was used to arrive at estimates of intervention effectiveness. All heath system costs required to deliver the intervention, regardless of payer, were included. Interventions are considered to be implemented for 100 years. The analysis was undertaken for eastern sub-Saharan Africa and Southeast Asia. RESULTS: In Southeast Asia, among individual interventions, drink driving legislation and its enforcement via random breath testing of drivers at roadside checkpoints, at 80% coverage, was found to be the most cost-effective intervention. Moreover, the combination of "speed limits + random breath testing + motorcycle helmet use", at 90% coverage, was found to be the most cost-effective package. In eastern sub-Saharan Africa, enforcement of speed limits via mobile/handheld cameras, at 80% coverage, was found to be the most cost-effective single intervention. The combination of "seatbelt use + motorcycle helmet use + speed limits + random breath testing" at 90% coverage was found to be the most cost-effective intervention package. CONCLUSION: This study presents updated estimates on cost-effectiveness of practical, evidence-based strategies that countries can use to address the burden of RTIs. The combination of individual interventions that enforces simultaneously multiple road safety measures are proving to be the most cost-effective scenarios. It is important to note, however, that, in addition to enacting and enforcing legislation on the risk factors highlighted as part of this paper, countries need to have a coordinated, multi-faceted strategy to improve road safety.

Investing in non-communicable diseases: an estimation of the return on investment for prevention and treatment services.

The global burden of non-communicable diseases (NCDs) is growing, and there is an urgent need to estimate the costs and benefits of an investment strategy to prevent and control NCDs. Results from an investment-case analysis can provide important new evidence to inform decision making by governments and donors. We propose a methodology for calculating the economic benefits of investing in NCDs during the Sustainable Development Goals (SDGs) era, and we applied this methodology to cardiovascular disease prevention in 20 countries with the highest NCD burden. For a limited set of prevention interventions, we estimated that US$120 billion must be invested in these countries between 2015 and 2030. This investment represents an additional $1·50 per capita per year and would avert 15 million deaths, 8 million incidents of ischaemic heart disease, and 13 million incidents of stroke in the 20 countries. Benefit-cost ratios varied between interventions and country-income levels, with an average ratio of 5·6 for economic returns but a ratio of 10·9 if social returns are included. Investing in cardiovascular disease prevention is integral to achieving SDG target 3.4 (reducing premature mortality from NCDs by a third) and to progress towards SDG target 3.8 (the realisation of universal health coverage). Many countries have implemented cost-effective interventions at low levels, so the potential to achieve these targets and strengthen national income by scaling up these interventions is enormous.

Econometric estimation of WHO-CHOICE country-specific costs for inpatient and outpatient health service delivery.

BACKGROUND: Policy makers require information on costs related to inpatient and outpatient health services to inform resource allocation decisions. METHODS: Country data sets were gathered in 2008-2010 through literature reviews, website searches and a public call for cost data. Multivariate regression analysis was used to explore the determinants of variability in unit costs using data from 30 countries. Two models were designed, with the inpatient and outpatient models drawing upon 3407 and 9028 observations respectively. Cost estimates are produced at country and regional level, with 95% confidence intervals. RESULTS: Inpatient costs across 30 countries are significantly associated with the type of hospital, ownership, as well as bed occupancy rate, average length of stay, and total number of inpatient admissions. Changes in outpatient costs are significantly associated with location, facility ownership and the level of care, as well as to the number of outpatient visits and visits per provider per day. CONCLUSIONS: These updated WHO-CHOICE service delivery unit costs are statistically robust and may be used by analysts as inputs for economic analysis. The models can predict country-specific unit costs at different capacity levels and in different settings.

Global health worker salary estimates: an econometric analysis of global earnings data.

BACKGROUND: Human resources are consistently cited as a leading contributor to health care costs; however the availability of internationally comparable data on health worker earnings for all countries is a challenge for estimating the costs of health care services. This paper describes an econometric model using cross sectional earnings data from the International Labour Organization (ILO) that the World Health Organizations (WHO)-Choosing Interventions that are Cost-effective programme (CHOICE) has used to prepare estimates of health worker earnings (in 2010 USD) for all WHO member states. METHODS: The ILO data contained 324 observations of earnings data across 4 skill levels for 193 countries. Using this data, along with the assumption that data were missing not at random, we used a Heckman two stage selection model to estimate earning data for each of the 4 skill levels for all WHO member states. RESULTS: It was possible to develop a prediction model for health worker earnings for all countries for which GDP data was available. Health worker earnings vary both within country due to skill level, as well as across countries. As a multiple of GDP per capita, earnings show a negative correlation with GDP-that is lower income countries pay their health workers relatively more than higher income countries. CONCLUSIONS: Limited data on health worker earnings is a limiting factor in estimating the costs of global health programmes. It is hoped that these estimates will support robust health care intervention costings and projections of resources needs over the Sustainable Development Goal period.

A Two-Step Markov Processes Approach for Parameterization of Cancer State-Transition Models for Low- and Middle-Income Countries.

Implementation of organized cancer screening and prevention programs in high-income countries (HICs) has considerably decreased cancer-related incidence and mortality. In low- and middle-income countries (LMICs), screening and early diagnosis programs are generally unavailable, and most cancers are diagnosed in late stages when survival is very low. Analyzing the cost-effectiveness of alternative cancer control programs and estimating resource needs will help prioritize interventions in LMICs. However, mathematical models of natural cancer onset and progression needed to conduct the economic analyses are predominantly based on populations in HICs because the longitudinal data on screening and diagnoses required for parameterization are unavailable in LMICs. Models currently used for LMICs mostly concentrate on directly calculating the shift in distribution of cancer diagnosis as an evaluative measure of screening. We present a mathematical methodology for the parameterization of natural cancer onset and progression, specifically for LMICs that do not have longitudinal data. This full onset and progression model can help conduct comprehensive analyses of cancer control programs, including cancer screening, by considering both the positive impact of screening as well as any adverse consequences, such as over-diagnosis and false-positive results. The methodology has been applied to breast, cervical, and colorectal cancers for 2 regions, under the World Health Organization categorization: Eastern Sub-Saharan Africa (AFRE) and Southeast Asia (SEARB). The cancer models have been incorporated into the Spectrum software and interfaced with country-specific demographic data through the demographic projections (DemProj) module and costing data through the OneHealth tool. These software are open-access and can be used by stakeholders to analyze screening strategies specific to their country of interest.

Priority Setting for Universal Health Coverage: We Need to Focus Both on Substance and on Process Comment on "Priority Setting for Universal Health Coverage: We Need Evidence-Informed Deliberative Processes, not Just More Evidence on Cost-Effectiveness".

In an editorial published in this journal, Baltussen et al argue that information on cost-effectiveness is not sufficient for priority setting for universal health coverage (UHC), a claim which is correct as far as it goes. However, their focus on the procedural legitimacy of 'micro' priority setting processes (eg, decisions concerning the reimbursement of specific interventions), and their related assumption that values for priority setting are determined only at this level, leads them to ignore the relevance of higher level, 'macro' priority setting processes, for example, consultations held by World Health Organization (WHO) Member States and other global stakeholders that have resulted in widespread consensus on the principles of UHC. Priority setting is not merely about discrete choices, nor should the focus be exclusively (or even mainly) on improving the procedural elements of micro priority setting processes. Systemic activities that shape the health system environment, such as strategic planning, as well as the substantive content of global policy instruments, are critical elements for priority setting for UHC.