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Cost-effectiveness analysis (CEA) is a well-known, but resource intensive, method for comparing the costs and health outcomes of health interventions. To build on available evidence, researchers are developing methods to transfer CEA across settings; previous methods do not use all available results nor quantify differences across settings. We conducted a meta-regression analysis of published CEAs of human papillomavirus (HPV) vaccination to quantify the effects of factors at the country, intervention, and method-level, and predict incremental cost-effectiveness ratios (ICERs) for HPV vaccination in 195 countries. We used 613 ICERs reported in 75 studies from the Tufts University’s Cost-Effectiveness Analysis (CEA) Registry and the Global Health CEA Registry, and extracted an additional 1,215 one-way sensitivity analyses. A five-stage, mixed-effects meta-regression framework was used to predict country-specific ICERs. The probability that HPV vaccination is cost-saving in each country was predicted using a logistic regression model. Covariates for both models included methods and intervention characteristics, and each country’s cervical cancer burden and gross domestic product per capita. ICERs are positively related to vaccine cost, and negatively related to cervical cancer burden. The mean predicted ICER for HPV vaccination is 2017 US$4,217 per DALY averted (95% uncertainty interval (UI): US$773–13,448) globally, and below US$800 per DALY averted in 64 countries. Predicted ICERs are lowest in Sub-Saharan Africa and South Asia, with a population-weighted mean ICER across 46 countries of US$706 per DALY averted (95% UI: $130–2,245), and across five countries of US$489 per DALY averted (95% UI: $90–1,557), respectively. Meta-regression analyses can be conducted on CEA, where one-way sensitivity analyses are used to quantify the effects of factors at the intervention and method-level. Building on all published results, our predictions support introducing and expanding HPV vaccination, especially in countries that are eligible for subsidized vaccines from GAVI, the Vaccine Alliance, and Pan American Health Organization.

Poor quality diets contribute to malnutrition globally, but evidence is weak on the cost-effectiveness of food-based interventions that shift diets. This study assessed 11 candidate interventions developed through Delphi techniques to improve diets in India, Nigeria, and Ethiopia. A Markov simulation model incorporated time, individual-level, nutrition, and policy parameters to estimate health impacts and cost-effectiveness for reducing stunting, anaemia, diarrhea, and mortality in preschool children. At an assumed 80% coverage, interventions considered would potentially save between 0·16 and 3·20 years of life per child. The average cost-effectiveness ratio ranged from US$9 to US$2000 per life year saved. This approach, linking expert knowledge, known costs, and modelling, offers potential for estimating cost-effective investments for better informed policy choice where empirical evidence is limited., Highlights • Few studies estimate the potential cost-effectiveness of programs for improving health through diets. • Expert knowledge linked to modelling offers a basis for assessing potential alternatives where data are lacking. • Our analysis assessed 11 candidate interventions for Ethiopia, India, and Nigeria derived from local expert opinion. • Modelling demonstrates these programs' potential health impacts and cost-effectiveness. • The modelling of estimated benefits can support best-buy policy and program choices.

The research agenda towards an HIV cure is building rapidly. In this article, we discuss the reasons for and methodological approach to using mathematical modelling and cost-effectiveness analysis in this agenda. We provide a brief description of the proof of concept for cure and the current directions of cure research. We then review the types of clinical economic evaluations, including cost analysis, cost-benefit analysis and cost-effectiveness analysis. We describe the use of mathematical modelling and cost-effectiveness analysis early in the HIV epidemic as well as in the era of combination antiretroviral therapy. We then highlight the novel methodology of Value of Information (VOI) analysis and its potential role in the planning of clinical trials. We close with recommendations for modelling and cost-effectiveness analysis in the HIV cure agenda.

The research agenda towards an HIV cure is building rapidly. In this article, we discuss the reasons for and methodological approach to using mathematical modelling and cost-effectiveness analysis in this agenda. We provide a brief description of the proof of concept for cure and the current directions of cure research. We then review the types of clinical economic evaluations, including cost analysis, cost-benefit analysis and cost-effectiveness analysis. We describe the use of mathematical modelling and cost-effectiveness analysis early in the HIV epidemic as well as in the era of combination antiretroviral therapy. We then highlight the novel methodology of Value of Information (VOI) analysis and its potential role in the planning of clinical trials. We close with recommendations for modelling and cost-effectiveness analysis in the HIV cure agenda.