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. 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). 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. 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.

Modelling studies have been widely used to inform human papillomavirus (HPV) vaccination policy decisions; however, many models exist and it is not known whether they produce consistent predictions of population-level effectiveness and herd effects. We did a systematic review and meta-analysis of model predictions of the long-term population-level effectiveness of vaccination against HPV 16, 18, 6, and 11 infection in women and men, to examine the variability in predicted herd effects, incremental benefit of vaccinating boys, and potential for HPV-vaccine-type elimination. We searched MEDLINE and Embase for transmission-dynamic modelling studies published between Jan 1, 2009, and April 28, 2015, that predicted the population-level impact of vaccination on HPV 6, 11, 16, and 18 infections in high-income countries. We contacted authors to determine whether they were willing to produce new predictions for standardised scenarios. Strategies investigated were girls-only vaccination and girls and boys vaccination at age 12 years. Base-case vaccine characteristics were 100% efficacy and lifetime protection. We did sensitivity analyses by varying vaccination coverage, vaccine efficacy, and duration of protection. For all scenarios we pooled model predictions of relative reductions in HPV prevalence (RRprev) over time after vaccination and summarised results using the median and 10th and 90th percentiles (80% uncertainty intervals [UI]). 16 of 19 eligible models from ten high-income countries provided predictions. Under base-case assumptions, 40% vaccination coverage and girls-only vaccination, the RRprev of HPV 16 among women and men was 0·53 (80% UI 0·46-0·68) and 0·36 (0·28-0·61), respectively, after 70 years. With 80% girls-only vaccination coverage, the RRprev of HPV 16 among women and men was 0·93 (0·90-1·00) and 0·83 (0·75-1·00), respectively. Vaccinating boys in addition to girls increased the RRprev of HPV 16 among women and men by 0·18 (0·13-0·32) and 0·35 (0·27-0·39) for 40% coverage, and 0·07 (0·00-0·10) and 0·16 (0·01-0·25) for 80% coverage, respectively. The RRprev were greater for HPV 6, 11, and 18 than for HPV 16 for all scenarios investigated. Finally at 80% coverage, most models predicted that girls and boys vaccination would eliminate HPV 6, 11, 16, and 18, with a median RRprev of 1·00 for women and men for all four HPV types. Variability in pooled findings was low, but increased with lower vaccination coverage and shorter vaccine protection (from lifetime to 20 years). Although HPV models differ in structure, data used for calibration, and settings, our population-level predictions were generally concordant and suggest that strong herd effects are expected from vaccinating girls only, even with coverage as low as 20%. Elimination of HPV 16, 18, 6, and 11 is possible if 80% coverage in girls and boys is reached and if high vaccine efficacy is maintained over time. Canadian Institutes of Health Research.

Economic evidence is increasingly being used for informing health policies. However, the underlining principles of health economic analyses are not always fully understood by non-health economists, and inappropriate types of analyses, as well as inconsistent methodologies, may be being used for informing health policy decisions. In addition, there is a lack of open access information and methodological guidance targeted to public health professionals, particularly those based in low- and middle-income country (LMIC) settings. The objective of this review is to provide a comprehensive and accessible introduction to economic evaluations for public health professionals with a focus on LMIC settings. We cover the main principles underlining the most common types of full economic evaluations used in healthcare decision making in the context of priority setting (namely cost-effectiveness/cost-utility analyses, cost-benefit analyses), and outline their key features, strengths and weaknesses. It is envisioned that this will help those conducting such analyses, as well as stakeholders that need to interpret their output, gain a greater understanding of these methods and help them select/distinguish between the different approaches. In particular, we highlight the need for greater awareness of the methods used to place a monetary value on the health benefits of interventions, and the potential for such estimates to be misinterpreted. Specifically, the economic benefits reported are typically an approximation, summarising the health benefits experienced by a population monetarily in terms of individual preferences or potential productivity gains, rather than actual realisable or fiscal monetary benefits to payers or society.

The term ‘perspective’ in the context of economic evaluations and costing studies in healthcare refers to the viewpoint that an analyst has adopted to define the types of costs and outcomes to consider in their studies. However, there are currently notable variations in terms of methodological recommendations, definitions, and applications of different perspectives, depending on the objective or intended user of the study. This can make it a complex area for stakeholders when interpreting these studies. Consequently, there is a need for a comprehensive overview regarding the different types of perspectives employed in such analyses, along with the corresponding implications of their use. This is particularly important, in the context of low-and-middle-income countries (LMICs), where practical guidelines may be less well-established and infrastructure for conducting economic evaluations may be more limited. This article addresses this gap by summarising the main types of perspectives commonly found in the literature to a broad audience (namely the patient, payer, health care providers, healthcare sector, health system, and societal perspectives), providing their most established definitions and outlining the corresponding implications of their uses in health economic studies, with examples particularly from LMIC settings. We then discuss important considerations when selecting the perspective and present key arguments to consider when deciding whether the societal perspective should be used. We conclude that there is no one-size-fits-all answer to what perspective should be used and the perspective chosen will be influenced by the context, policymakers'/stakeholders’ viewpoints, resource/data availability, and intended use of the analysis. Moving forward, considering the ongoing issues regarding the variation in terminology and practice in this area, we urge that more standardised definitions of the different perspectives and the boundaries between them are further developed to support future studies and guidelines, as well as to improve the interpretation and comparison of health economic evidence.