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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.

BACKGROUND:Promising school policies to improve children's diets include providing fresh fruits and vegetables (F&V) and competitive food restrictions on sugar-sweetened beverages (SSBs), yet the impact of national implementation of these policies in US schools on cardiometabolic disease (CMD) risk factors and outcomes is not known. Our objective was to estimate the impact of national implementation of F&V provision and SSB restriction in US elementary, middle, and high schools on dietary intake and body mass index (BMI) in children and future CMD mortality. METHODS:We used comparative risk assessment (CRA) frameworks to model the impacts of these policies with input parameters from nationally representative surveys, randomized-controlled trials, and systematic reviews and meta-analyses. For children ages 5-18 years, this incorporated national data on current dietary intakes and BMI, impacts of these policies on diet, and estimated effects of dietary changes on BMI. In adults ages 25 and older, we further incorporated the sustainability of dietary changes to adulthood, effects of dietary changes on CMD, and national CMD death statistics, modeling effects if these policies had been in place when current US adults were children. Uncertainty across inputs was incorporated using 1000 Monte Carlo simulations. RESULTS:National F&V provision would increase daily fruit intake in children by as much as 25.0% (95% uncertainty interval (UI): 15.4, 37.7%), and would have small effects on vegetable intake. SSB restriction would decrease daily SSB intake by as much as 26.5% (95% UI: 6.4, 46.4%), and reduce BMI by as much as 0.7% (95% UI: 0.2, 1.2%). If F&V provision and SSB restriction were nationally implemented, an estimated 22,383 CMD deaths/year (95% UI: 18735, 25930) would be averted. CONCLUSION:National school F&V provision and SSB restriction policies implemented in elementary, middle, and high schools could improve diet and BMI in children and reduce CMD mortality later in life.

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.