Impact of Model, Methodological, and Parameter Uncertainty in the Economic Analysis of Vaccination Programs

Examining the Impact of Structural Uncertainty Across 10 Type 2 Diabetes Models: Results From the 2022 Mount Hood Challenge

OBJECTIVES

The Mount Hood Diabetes Challenge Network aimed to examine the impact of model structural uncertainty on the estimated cost-effectiveness of interventions for type 2 diabetes.

METHODS

Ten independent modeling groups completed a blinded simulation exercise to estimate the cost-effectiveness of 3 interventions in 2 type 2 diabetes populations. Modeling groups were provided with a common baseline population, cost and utility values associated with different model health states, and instructions regarding time horizon and discounting. We collated the results to identify variation in predictions of net monetary benefit (NMB) and the drivers of those differences.

RESULTS

Overall, modeling groups agreed which interventions had a positive NMB (ie, were cost-effective), Although estimates of NMB varied substantially-by up to £23 696 for 1 intervention. Variation was mainly driven through differences in risk equations for complications of diabetes and their implementation between models. The number of modeled health states was also a significant predictor of NMB.

CONCLUSIONS

This exercise demonstrates that structural uncertainty between different health economic models affects cost-effectiveness estimates. Although it is reassuring that a decision maker would likely reach similar conclusions on which interventions were cost-effective using most models, the range in numerical estimates generated across different models would nevertheless be important for price-setting negotiations with intervention developers. Minimizing the impact of structural uncertainty on healthcare decision making therefore remains an important priority. Model registries, which record and compare the impact of structural assumptions, offer one potential avenue to improve confidence in the robustness of health economic modeling.

A Systematic Review of Methodologies Used in Models of the Treatment of Diabetes Mellitus

BACKGROUND

Diabetes mellitus is a chronic and complex disease, increasing in prevalence and consequent health expenditure. Cost-effectiveness models with long time horizons are commonly used to perform economic evaluations of diabetes' treatments. As such, prediction accuracy and structural uncertainty are important features in cost-effectiveness models of chronic conditions.

OBJECTIVES

The aim of this systematic review is to identify and review published cost-effectiveness models of diabetes treatments developed between 2011 and 2022 regarding their methodological characteristics. Further, it also appraises the quality of the methods used, and discusses opportunities for further methodological research.

METHODS

A systematic literature review was conducted in MEDLINE and Embase to identify peer-reviewed papers reporting cost-effectiveness models of diabetes treatments, with time horizons of more than 5 years, published in English between 1 January 2011 and 31 of December 2022. Screening, full-text inclusion, data extraction, quality assessment and data synthesis using narrative synthesis were performed. The Philips checklist was used for quality assessment of the included studies. The study was registered in PROSPERO (CRD42021248999).

RESULTS

The literature search identified 30 studies presenting 29 unique cost-effectiveness models of type 1 and/or type 2 diabetes treatments. The review identified 26 type 2 diabetes mellitus (T2DM) models, 3 type 1 DM (T1DM) models and one model for both types of diabetes. Fifteen models were patient-level models, whereas 14 were at cohort level. Parameter uncertainty was assessed thoroughly in most of the models, whereas structural uncertainty was seldom addressed. All the models where validation was conducted performed well. The methodological quality of the models with respect to structure was high, whereas with respect to data modelling it was moderate.

CONCLUSIONS

Models developed in the past 12 years for health economic evaluations of diabetes treatments are of high-quality and make use of advanced methods. However, further developments are needed to improve the statistical modelling component of cost-effectiveness models and to provide better assessment of structural uncertainty.

Systematic review of rotavirus vaccination cost-effectiveness in high income settings utilising dynamic transmission modelling techniques

PURPOSE

This systematic review presents cost-effectiveness studies of rotavirus vaccination in high-income settings based on dynamic transmission modelling to inform policy decisions about implementing rotavirus vaccination programmes.

METHODS

We searched CEA Registry, MEDLINE, Embase, Health Technology Assessment Database, Scopus, and the National Health Service Economic Evaluation Database for studies published since 2002. Full economic evaluation studies based on dynamic transmission models, focusing on high-income countries, live oral rotavirus vaccine and children ≤ 5 years of age were eligible for inclusion. Included studies were appraised for quality and risk of bias using the Consensus on Health Economic Criteria (CHEC) list and the Philips checklist. The review protocol was prospectively registered with PROSPERO (CRD42020208406).

RESULTS

A total of four economic evaluations were identified. Study settings included England and Wales, France, Norway, and the United States. All studies compared either pentavalent or monovalent rotavirus vaccines to no intervention. All studies were cost-utility analyses that reported incremental cost per quality-adjusted life year (QALY) gained. Included studies consistently concluded that rotavirus vaccination is cost-effective compared with no vaccination relative to the respective country's willingness to pay threshold when herd protection benefits are incorporated in the modelling framework.

CONCLUSIONS

Rotavirus vaccination was found to be cost-effective in all identified studies that used dynamic transmission models in high-income settings where child mortality rates due to rotavirus gastroenteritis are close to zero. Previous systematic reviews of economic evaluations considered mostly static models and had less conclusive findings than the current study. This review suggests that modelling choices influence cost-effectiveness results for rotavirus vaccination. Specifically, the review suggests that dynamic transmission models are more likely to account for the full impact of rotavirus vaccination than static models in cost-effectiveness analyses.

Comparison of model predictions of typhoid conjugate vaccine public health impact and cost-effectiveness

Models are useful to inform policy decisions on typhoid conjugate vaccine (TCV) deployment in endemic settings. However, methodological choices can influence model-predicted outcomes. To provide robust estimates for the potential public health impact of TCVs that account for structural model differences, we compared four dynamic and one static mathematical model of typhoid transmission and vaccine impact. All models were fitted to a common dataset of age-specific typhoid fever cases in Kolkata, India. We evaluated three TCV strategies: no vaccination, routine vaccination at 9 months of age, and routine vaccination at 9 months with a one-time catch-up campaign (ages 9 months to 15 years). The primary outcome was the predicted percent reduction in symptomatic typhoid cases over 10 years after vaccine introduction. For three models with economic analyses (Models A-C), we also compared the incremental cost-effectiveness ratios (ICERs), calculated as the incremental cost (US$) per disability-adjusted life-year (DALY) averted. Routine vaccination was predicted to reduce symptomatic cases by 10-46 % over a 10-year time horizon under an optimistic scenario (95 % initial vaccine efficacy and 19-year mean duration of protection), and by 2-16 % under a pessimistic scenario (82 % initial efficacy and 6-year mean protection). Adding a catch-up campaign predicted a reduction in incidence of 36-90 % and 6-35 % in the optimistic and pessimistic scenarios, respectively. Vaccine impact was predicted to decrease as the relative contribution of chronic carriers to transmission increased. Models A-C all predicted routine vaccination with or without a catch-up campaign to be cost-effective compared to no vaccination, with ICERs varying from $95-789 per DALY averted; two models predicted the ICER of routine vaccination alone to be greater than with the addition of catch-up campaign. Despite differences in model-predicted vaccine impact and cost-effectiveness, routine vaccination plus a catch-up campaign is likely to be impactful and cost-effective in high incidence settings such as Kolkata.

A comprehensive review of official discount rates in guidelines of health economic evaluations over time: the trends and roots

BACKGROUND

The question of discounting in health economics is anything but settled, so much so that a section of the Health Technology Assessment (HTA) guidelines is devoted to it.

OBJECTIVE

This study aimed to review the trend of the value of the official discount rates (DRs) of costs and health outcomes and their roots worldwide.

METHODS

Four methods were combined to identify official DRs over time globally. These methods included a systematic review of the HTA/pharmacoeconomic/health economic evaluation guidelines, a review of methodological documents or guidelines accessible on the websites of HTA organizations, and two separated reviews of the websites of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the Guide to Health Economic Analysis and Research (GEAR).

RESULTS

Our systematic search eventually yielded 339 documents from the literature, 35 links from the website of the HTA organizations, 51 documents from the website of the ISPOR, and 29 documents from the website of the GEAR. These documents referred to 48 countries over 30 years and 43 transnational guidelines over 43 years. DRs of 3% and 5% had the most frequent value. Among them, 38 countries always used an equal DR of costs and health outcomes. We categorized the rationales for selecting DRs into eight groups for the national documents and six groups for the transnational documents.

CONCLUSION

The comparability approach was the most frequent rationale for choosing the DR in national and transnational guidelines. The value of DR of costs and health outcomes ranged from zero to 10% over the years, but the most common values were 3% and 5%, mainly arising from the comparability approach chosen. Several transnational guidelines have suggested a specific DR without taking into account countries' economic conditions. It is useful to establish a specific guideline for calculating and updating the DR of the health sector in each country.

Exploring Structural Uncertainty and Impact of Health State Utility Values on Lifetime Outcomes in Diabetes Economic Simulation Models: Findings from the Ninth Mount Hood Diabetes Quality-of-Life Challenge

BACKGROUND

Structural uncertainty can affect model-based economic simulation estimates and study conclusions. Unfortunately, unlike parameter uncertainty, relatively little is known about its magnitude of impact on life-years (LYs) and quality-adjusted life-years (QALYs) in modeling of diabetes. We leveraged the Mount Hood Diabetes Challenge Network, a biennial conference attended by international diabetes modeling groups, to assess structural uncertainty in simulating QALYs in type 2 diabetes simulation models.

METHODS

Eleven type 2 diabetes simulation modeling groups participated in the 9th Mount Hood Diabetes Challenge. Modeling groups simulated 5 diabetes-related intervention profiles using predefined baseline characteristics and a standard utility value set for diabetes-related complications. LYs and QALYs were reported. Simulations were repeated using lower and upper limits of the 95% confidence intervals of utility inputs. Changes in LYs and QALYs from tested interventions were compared across models. Additional analyses were conducted postchallenge to investigate drivers of cross-model differences.

RESULTS

Substantial cross-model variability in incremental LYs and QALYs was observed, particularly for HbA1c and body mass index (BMI) intervention profiles. For a 0.5%-point permanent HbA1c reduction, LY gains ranged from 0.050 to 0.750. For a 1-unit permanent BMI reduction, incremental QALYs varied from a small decrease in QALYs (-0.024) to an increase of 0.203. Changes in utility values of health states had a much smaller impact (to the hundredth of a decimal place) on incremental QALYs. Microsimulation models were found to generate a mean of 3.41 more LYs than cohort simulation models (P = 0.049).

CONCLUSIONS

Variations in utility values contribute to a lesser extent than uncertainty captured as structural uncertainty. These findings reinforce the importance of assessing structural uncertainty thoroughly because the choice of model (or models) can influence study results, which can serve as evidence for resource allocation decisions.HighlightsThe findings indicate substantial cross-model variability in QALY predictions for a standardized set of simulation scenarios and is considerably larger than within model variability to alternative health state utility values (e.g., lower and upper limits of the 95% confidence intervals of utility inputs).There is a need to understand and assess structural uncertainty, as the choice of model to inform resource allocation decisions can matter more than the choice of health state utility values.

Development of a conceptual model for evaluating new non-curative and curative therapies for sickle cell disease

BACKGROUND

Sickle cell disease (SCD) is a clinically heterogeneous disease with many acute and chronic complications driven by ongoing vaso-occlusion and hemolysis. It causes a disproportionate burden on Black and Hispanic communities. Our objective was to follow the SMDM/ISPOR Task Force recommendations for good practices and create a conceptual model of the progression of SCD under current clinical practice to inform cost-effectiveness analyses (CEA) of promising curative therapies in the pipeline over a lifetime horizon.

METHODS

We used consultations with experts, providers, and patients to identify acute events and chronic conditions in the conceptual model. We compared our model structure to previous CEA models of interventions for SCD, assessed the prevalence of the identified disease attributes in Medicaid and Medicare claims databases, and identified relevant outcomes following the 2nd Panel in CEA. We determined an appropriate modeling technique and relevant data sources for parameterizing the model.

RESULTS

The conceptual model structure included four dimensions of disease: chronic pain, acute events, chronic conditions, and treatment complications, spanning 26 disease attributes with significant impacts on health-related quality of life and resource. We modeled chronic pain separately to reflect its importance to patients and interaction with all other disease attributes. We identified additional data sources for health state utilities and non-medical costs and benefits of SCD. We will use a microsimulation model with age- and sex-specific transitions between health states predicted by patient demographic characteristics and disease history.

CONCLUSION

Developing the model structure through an explicit process of model conceptualization can increase the transparency and accuracy of results. We will populate the conceptual model with the data sources described and evaluate the cost-effectiveness of curative therapies.

Methods for Extrapolating Survival Analyses for the Economic Evaluation of Advanced Therapy Medicinal Products

There are two significant challenges for analysts conducting economic evaluations of advanced therapy medicinal products (ATMPs): (i) estimating long-term treatment effects in the absence of mature clinical data, and (ii) capturing potentially complex hazard functions. This review identifies and critiques a variety of methods that can be used to overcome these challenges. The narrative review is informed by a rapid literature review of methods used for the extrapolation of survival analyses in the economic evaluation of ATMPs. There are several methods that are more suitable than traditional parametric survival modelling approaches for capturing complex hazard functions, including, cure-mixture models and restricted cubic spline models. In the absence of mature clinical data, analysts may augment clinical trial data with data from other sources to aid extrapolation, however, the relative merits of employing methods for including data from different sources is not well understood. Given the high and potentially irrecoverable costs of making incorrect decisions concerning the reimbursement or commissioning of ATMPs, it is important that economic evaluations are correctly specified, and that both parameter and structural uncertainty associated with survival extrapolations are considered. Value of information analyses allow for this uncertainty to be expressed explicitly, and in monetary terms.

The burden of vaccine hesitancy for routine immunization in Yaounde-Cameroon: A cross-sectional study

Immunization is the most cost-effective health intervention in the world yet, vaccination uptake is still low with less than 50% of children aged 12-23 months fully vaccinated in Cameroon by 2018. The objective of this study was to estimate the burden of vaccine hesitancy associated with routine vaccines in Yaounde-Cameroon. A two-stage cross-sectional cluster survey was conducted in Yaoundé in November 2021, targeting parents/guardians of children 0-59 months. Clusters were selected with probability proportionate to size (PPS) and household's selection done using a restricted sampling method. Data collection was done using an interviewer-administered questionnaire, "Core Closed Questions" and "Likert Scale Questions" proposed by the WHO Vaccine Hesitancy Technical Working Group in 2014. Vaccine hesitancy was analyzed as proportions of parent's/guardian's self-reported vaccine refusal or delay in vaccination with 95% confidence interval. This was stratified by household wealth level and tested using Chi-Square test to appreciate the effect of household wealth on vaccine hesitancy. A total of 529 participants were enrolled out of 708 visited, giving a non-response rate of 25%. In total, vaccine hesitancy was reported in 137(25.90[22.35-29.80] %), and oral polio vaccine(OPV) was the most affected vaccine with hesitancy of 10%. Vaccine hesitancy prevalence did not vary significantly across different households' wealth levels (p-value = 0.3786). However, in wealthy households' refusal of vaccines (14%) was less than in poorer households (20%). Lack of trust was reported as the leading cause of vaccine refusal (43%). Vaccine hesitancy prevalence in Yaounde is high and oral polio vaccine(OPV) was the most affected vaccine. The level of weath does not affect vaccine hesitancy and lack of trust was the leading cause of vaccine hesitancy related to routine immunization in Yaounde-Cameroon. We, recommend that the burden of vaccine hesitancy should be assessed at national scale and root causes investigated.

Self-Reporting of Risk Pathways and Parameter Values for Foot-and-Mouth Disease in Slaughter Cattle from Alternative Production Systems by Kenyan and Ugandan Veterinarians

Countries in which foot-and-mouth disease (FMD) is endemic may face bans on the export of FMD-susceptible livestock and products because of the associated risk for transmission of FMD virus. Risk assessment is an essential tool for demonstrating the fitness of one’s goods for the international marketplace and for improving animal health. However, it is difficult to obtain the necessary data for such risk assessments in many countries where FMD is present. This study bridged the gaps of traditional participatory and expert elicitation approaches by partnering with veterinarians from the National Veterinary Services of Kenya (n = 13) and Uganda (n = 10) enrolled in an extended capacity-building program to systematically collect rich, local knowledge in a format appropriate for formal quantitative analysis. Participants mapped risk pathways and quantified variables that determine the risk of infection among cattle at slaughter originating from each of four beef production systems in each country. Findings highlighted that risk processes differ between management systems, that disease and sale are not always independent events, and that events on the risk pathway are influenced by the actions and motivations of value chain actors. The results provide necessary information for evaluating the risk of FMD among cattle pre-harvest in Kenya and Uganda and provide a framework for similar evaluation in other endemic settings.

Online Cost-Effectiveness ANalysis (OCEAN): a user-friendly interface to conduct cost-effectiveness analyses for cervical cancer

Background

Most cost-effectiveness analyses in the context of cervical cancer prevention involve the use of mathematical models to simulate HPV infection, cervical disease and prevention strategies. However, it is common for professionals who would need to perform these analyses to not be familiar with the models. This work introduces the Online Cost-Effectiveness ANalysis tool, featuring an easy-to-use web interface providing health professionals, researchers and decision makers involved in cervical cancer prevention programmes with a useful instrument to conduct complex cost-effectiveness analyses, which are becoming an essential tool as an approach for supporting decision-making that involves important trade-offs.

Results

The users can run cost-effectiveness evaluations of cervical cancer prevention strategies without deep knowledge of the underlying mathematical model or any programming language, obtaining the most relevant costs and health outcomes in a user-friendly format. The results provided by the tool are consistent with the existing literature.

Conclusions

Having such a tool will be an asset to the cervical cancer prevention community, providing researchers with an easy-to-use instrument to conduct cost-effectiveness analyses.

Choosing awareness over fear: Risk analysis and free trade support global food security

Livestock production and global trade are key components to achieving food security, but are bedfellows with the risk for emergence and spread of infectious diseases. The World Trade Organization's Agreement on the Application of Sanitary and Phytosanitary Measures outlines provisions for member countries to protect animal, plant, and public health while promoting free trade. The capacity for risk analysis equips countries to increase access to export markets, improve local animal health and food safety regarding known hazards, and build the institutional capacity to respond to unexpected events. The COVID-19 pandemic has highlighted the need to detect, report, and implement effective response measures to emerging challenges on a local and global scale, and it is crucial that these measures are implemented in a way that supports food production and trade. The use of risk analysis coupled with sound understanding of underlying system dynamics will contribute to resilient and enduring food systems.

Structuring a conceptual model for cost-effectiveness analysis of frailty interventions

BACKGROUND

Frailty is a major health issue which impacts the life of older people, posing a significant challenge to the health system. One of the key emerging areas is the development of frailty interventions to halt or reverse the progression of the condition. In many countries, economic evidence is required to inform public funding decisions for such interventions, and cost-effectiveness models are needed to estimate long-term costs and effects. Such models should capture current clinical understanding of frailty, its progression and its health consequences. The objective of this paper is to present a conceptual model of frailty that can be used to inform the development of a cost-effectiveness model to evaluate frailty interventions.

METHODS

After critical analysis of the clinical and economic literature, a Delphi study consisting of experts from the disciplines of clinical medicine and epidemiology was undertaken to inform the key components of the conceptual model. We also identified relevant databases that can be used to populate and validate the model.

RESULTS

A list of significant health states/events for which frailty is a strong independent risk factor was identified (e.g., hip fracture, hospital admission, delirium, death). We also identified a list of important patient attributes that may influence disease progression (e.g., age, gender, previous hospital admissions, depression). A number of large-scale relevant databases were also identified to populate and validate the cost-effectiveness model. Face validity of model structure was confirmed by experts.

DISCUSSION AND CONCLUSIONS

The proposed conceptual model is being used as a basis for developing a new cost-effectiveness model to estimate lifetime costs and outcomes associated with a range of frailty interventions. Using an appropriate model structure, which more accurately reflects the natural history of frailty, will improve model transparency and accuracy. This will ultimately lead to better informed public funding decisions around interventions to manage frailty.

Competing biomedical HIV prevention strategies: potential cost-effectiveness of HIV vaccines and PrEP in Seattle, WA

INTRODUCTION

Promising HIV vaccine candidates are steadily progressing through the clinical trial pipeline. Once available, HIV vaccines will be an important complement but also potential competitor to other biomedical prevention tools such as pre-exposure prophylaxis (PrEP). Accordingly, the value of HIV vaccines and the policies for rollout may depend on that interplay and tradeoffs with utilization of existing products. In this economic modelling analysis, we estimate the cost-effectiveness of HIV vaccines considering their potential interaction with PrEP and condom use.

METHODS

We developed a dynamic model of HIV transmission among the men who have sex with men population (MSM), aged 15-64 years, in Seattle, WA offered PrEP and HIV vaccine over a time horizon of 2025-2045. A healthcare sector perspective with annual discount rate of 3% for costs (2017 USD) and quality-adjusted life years (QALYs) was used. The primary economic endpoint is the incremental cost-effectiveness ratio (ICER) when compared to no HIV vaccine availability.

RESULTS

HIV vaccines improved population health and increased healthcare costs. Vaccination campaigns achieving 90% coverage of high-risk men and 60% coverage of other men within five years of introduction are projected to avoid 40% of new HIV infections between 2025 and 2045. This increased total healthcare costs by $30 million, with some PrEP costs shifted to HIV vaccine spending. HIV vaccines are estimated to have an ICER of $42,473/QALY, considered cost-effective using a threshold of $150,000/QALY. Results were most sensitive to HIV vaccine efficacy and future changes in the cost of PrEP drugs. Sensitivity analysis found ranges of 30-70% HIV vaccine efficacy remained cost-effective. Results were also sensitive to reductions in condom use among PrEP and vaccine users.

CONCLUSIONS

Access to an HIV vaccine is desirable as it could increase the overall effectiveness of combination HIV prevention efforts and improve population health. Planning for the rollout and scale-up of HIV vaccines should carefully consider the design of policies that guide interactions between vaccine and PrEP utilization and potential competition.

The importance of accounting for the uncertainty around the preference-based health-related quality-of-life measures value sets: a systematic review

Preference-based measures of health-related quality-of-life including, but not limited to, the EQ-5D, HUI2 and the SF-6D have been increasingly used in calculations of quality-adjusted life years for cost effectiveness analyses. However, the uncertainty around the measures' value sets is commonly ignored in economic evaluation. There are several types of uncertainties, including methodological, structural, and parameter uncertainties, with the latter being the focus of this review paper. The objective is to highlight the gap in the literature regarding the existence of uncertainty in the value sets, focusing mainly on the EQ-5D and SF-6D. To the best of the authors' knowledge, this is the first systematic review revolving around uncertainty. After searching extensively for studies involving uncertainties in all preference-based measures, the results showed that uncertainty has been approached through different means, while parameter uncertainty has been ignored in most, if not all, cases. These findings suggest that uncertainty should be accounted for when using preference-based measures in economic evaluations. Ignoring this additional information could impact misleadingly on policy decisions.

Multivariable and Structural Uncertainty Analyses for Cost-Effectiveness Estimates: Back to the Future

BACKGROUND

In this commentary, celebrating the 20th anniversary of the journal Value in Health, I present a brief overview and illustration of the evolution over the past 20 years of the methodological literature providing guidelines for multivariable and structural uncertainty analysis for cost-effectiveness estimates.

METHODS

To illustrate the impact of the guidelines for uncertainty analyses, I show how the inclusion of multivariable and structural uncertainty analyses in cost-effectiveness analyses published in Value in Health changed over the past 20 years using publications from 1999/2000, 2007 and 2017.

RESULTS

The commentary is organized in three sections: past, focusing on the development and use of methods for multivariable uncertainty analysis; present, focusing on the growing awareness of the need for structural uncertainty analysis, suggested frameworks for structural uncertainty analysis and how it is currently implemented; and future, considering different methods for combining multivariable and structural uncertainty analyses over the next decades.

CONCLUSIONS

I conclude by suggesting how the continued evolution of uncertainty analyses in published studies and health technology assessment submissions can best take into account an important goal of cost-effectiveness analyses: to provide useful information to decision makers.

Model Structuring for Economic Evaluations of New Health Technologies

In countries such as Australia, the UK and Canada, decisions on whether to fund new health technologies are commonly informed by decision analytic models. While the impact of making inappropriate structural choices/assumptions on model predictions is well noted, there is a lack of clarity about the definition of key structural aspects, the process of developing model structure (including the development of conceptual models) and uncertainty associated with the structuring process (structural uncertainty) in guidelines developed by national funding bodies. This forms the focus of this article. Building on the reports of good modelling practice, and recognising the fundamental role of model structuring within the model development process, we specified key structural choices and provided ideas about model structuring for the future direction. This will help to further standardise guidelines developed by national funding bodies, with potential impact on transparency, comprehensiveness and consistency of model structuring. We argue that the process of model structuring and structural sensitivity analysis should be documented in a more systematic and transparent way in submissions to national funding bodies. Within the decision-making process, the development of conceptual models and presentation of all key structural choices would mean that national funding bodies could be more confident of maximising value for money when making public funding decisions.

Simultaneously characterizing the comparative economics of routine female adolescent nonavalent human papillomavirus (HPV) vaccination and assortativity of sexual mixing in Hong Kong Chinese: a modeling analysis

BACKGROUND

Although routine vaccination of females before sexual debut against human papillomavirus (HPV) has been found to be cost-effective around the world, its cost-benefit has rarely been examined. We evaluate both the cost-effectiveness and cost-benefit of routine female adolescent nonavalent HPV vaccination in Hong Kong to guide its policy, and by extension that of mainland China, on HPV vaccination. One major obstacle is the lack of data on assortativity of sexual mixing. Such difficulty could be overcome by inferring sexual mixing parameters from HPV epidemiologic data.

METHODS

We use an age-structured transmission model coupled with stochastic individual-based simulations to estimate the health and economic impact of routine nonavalent HPV vaccination for girls at age 12 on cervical cancer burden and consider vaccine uptake at 25%, 50%, and 75% with at least 20 years of vaccine protection. Bayesian inference was employed to parameterize the model using local data on HPV prevalence and cervical cancer incidence. We use the human capital approach in the cost-benefit analysis (CBA) and GDP per capita as the indicative willingness-to-pay threshold in the cost-effectiveness analysis (CEA). Finally, we estimate the threshold vaccine cost (TVC), which is the maximum cost for fully vaccinating one girl at which routine female adolescent nonavalent HPV vaccination is cost-beneficial or cost-effective.

RESULTS

As vaccine uptake increased, TVC decreased (i.e., economically more stringent) in the CBA but increased in the CEA. When vaccine uptake was 75% and the vaccine provided only 20 years of protection, the TVC was US$444 ($373-506) and $689 ($646-734) in the CBA and CEA, respectively, increasing by approximately 2-4% if vaccine protection was assumed lifelong. TVC is likely to be far higher when non-cervical diseases are included. The inferred sexual mixing parameters suggest that sexual mixing in Hong Kong is highly assortative by both age and sexual activity level.

CONCLUSIONS

Routine HPV vaccination of 12-year-old females is highly likely to be cost-beneficial and cost-effective in Hong Kong. Inference of sexual mixing parameters from epidemiologic data of prevalent sexually transmitted diseases (i.e., HPV, chlamydia, etc.) is a potentially fruitful but largely untapped methodology for understanding sexual behaviors in the population.

Quantifying population-level health benefits and harms of e-cigarette use in the United States

BACKGROUND

Electronic cigarettes (e-cigarettes) may help cigarette smokers quit smoking, yet they may also facilitate cigarette smoking for never-smokers. We quantify the balance of health benefits and harms associated with e-cigarette use at the population level.

METHODS AND FINDINGS

Monte Carlo stochastic simulation model. Model parameters were drawn from census counts, national health and tobacco use surveys, and published literature. We calculate the expected years of life gained or lost from the impact of e-cigarette use on smoking cessation among current smokers and transition to long-term cigarette smoking among never smokers for the 2014 US population cohort.

RESULTS

The model estimated that 2,070 additional current cigarette smoking adults aged 25-69 (95% CI: -42,900 to 46,200) would quit smoking in 2015 and remain continually abstinent from smoking for ≥7 years through the use of e-cigarettes in 2014. The model also estimated 168,000 additional never-cigarette smoking adolescents aged 12-17 and young adults aged 18-29 (95% CI: 114,000 to 229,000), would initiate cigarette smoking in 2015 and eventually become daily cigarette smokers at age 35-39 through the use of e-cigarettes in 2014. Overall, the model estimated that e-cigarette use in 2014 would lead to 1,510,000 years of life lost (95% CI: 920,000 to 2,160,000), assuming an optimistic 95% relative harm reduction of e-cigarette use compared to cigarette smoking. As the relative harm reduction decreased, the model estimated a greater number of years of life lost. For example, the model estimated-1,550,000 years of life lost (95% CI: -2,200,000 to -980,000) assuming an approximately 75% relative harm reduction and -1,600,000 years of life lost (95% CI: -2,290,000 to -1,030,000) assuming an approximately 50% relative harm reduction.

CONCLUSIONS

Based on the existing scientific evidence related to e-cigarettes and optimistic assumptions about the relative harm of e-cigarette use compared to cigarette smoking, e-cigarette use currently represents more population-level harm than benefit. Effective national, state, and local efforts are needed to reduce e-cigarette use among youth and young adults if e-cigarettes are to confer a net population-level benefit in the future.

The Importance of Model Structure in the Cost-Effectiveness Analysis of Primary Care Interventions for the Management of Hypertension

BACKGROUND

Management of hypertension can lead to significant reductions in blood pressure, thereby reducing the risk of cardiovascular disease. Modeling the course of cardiovascular disease is not without complications, and uncertainty surrounding the structure of a model will almost always arise once a choice of a model structure is defined.

OBJECTIVES

To provide a practical illustration of the impact on the results of cost-effectiveness of changing or adapting model structures in a previously published cost-utility analysis of a primary care intervention for the management of hypertension Targets and Self-Management for the Control of Blood Pressure in Stroke and at Risk Groups (TASMIN-SR).

METHODS

The case study assessed the structural uncertainty arising from model structure and from the exclusion of secondary events. Four alternative model structures were implemented. Long-term cost-effectiveness was estimated and the results compared with those from the TASMIN-SR model.

RESULTS

The main cost-effectiveness results obtained in the TASMIN-SR study did not change with the implementation of alternative model structures. Choice of model type was limited to a cohort Markov model, and because of the lack of epidemiological data, only model 4 captured structural uncertainty arising from the exclusion of secondary events in the case study model.

CONCLUSIONS

The results of this study indicate that the main conclusions drawn from the TASMIN-SR model of cost-effectiveness were robust to changes in model structure and the inclusion of secondary events. Even though one of the models produced results that were different to those of TASMIN-SR, the fact that the main conclusions were identical suggests that a more parsimonious model may have sufficed.

Cost-utility analysis of antiviral use under pandemic influenza using a novel approach - linking pharmacology, epidemiology and heath economics

Simulation models are used widely in pharmacology, epidemiology and health economics (HEs). However, there have been no attempts to incorporate models from these disciplines into a single integrated model. Accordingly, we explored this linkage to evaluate the epidemiological and economic impact of oseltamivir dose optimisation in supporting pandemic influenza planning in the USA. An HE decision analytic model was linked to a pharmacokinetic/pharmacodynamics (PK/PD) - dynamic transmission model simulating the impact of pandemic influenza with low virulence and low transmissibility and, high virulence and high transmissibility. The cost-utility analysis was from the payer and societal perspectives, comparing oseltamivir 75 and 150 mg twice daily (BID) to no treatment over a 1-year time horizon. Model parameters were derived from published studies. Outcomes were measured as cost per quality-adjusted life year (QALY) gained. Sensitivity analyses were performed to examine the integrated model's robustness. Under both pandemic scenarios, compared to no treatment, the use of oseltamivir 75 or 150 mg BID led to a significant reduction of influenza episodes and influenza-related deaths, translating to substantial savings of QALYs. Overall drug costs were offset by the reduction of both direct and indirect costs, making these two interventions cost-saving from both perspectives. The results were sensitive to the proportion of inpatient presentation at the emergency visit and patients' quality of life. Integrating PK/PD-EPI/HE models is achievable. Whilst further refinement of this novel linkage model to more closely mimic the reality is needed, the current study has generated useful insights to support influenza pandemic planning.

Impact of model calibration on cost-effectiveness analysis of cervical cancer prevention

Markov chain models are commonly used to simulate the natural history of human papillomavirus infection and subsequent cervical lesions with the aim of predicting future benefits of health interventions. Developing and calibrating these models entails making a number of critical decisions that will influence the ability of the model to reflect real conditions and predict future situations. Accuracy of selected inputs and calibration procedures are two of the crucial aspects for model performance and understanding their influence is essential, especially when involves policy decisions. The aim of this work is to assess the health and economic impact on cervical cancer prevention strategies currently under discussion according to the most common methods of model calibration combined with different accuracy degree of initial inputs. Model results show large differences on the goodness of fit and cost-effectiveness outcomes depending on the calibration approach used, and these variations may affect health policy decisions. Our findings strengthen the importance of obtaining good calibrated probability matrices to get reliable health and cost outcomes, and are directly generalizable to any cost-effectiveness analysis based on Markov chain models.

Dynamic transmission models for economic analysis applied to health care-associated infections: A review of the literature

BACKGROUND

Cost-effectiveness analyses are an important methodology in assessing whether a health care technology is suitable for widespread adoption. Common models used by economists, such as decision trees and Markov models, are appropriate for noninfectious diseases where treatment and exposure are independent. Diseases whose treatment and exposure are dependent require dynamic models to incorporate the nonlinear transmission effect. Two different types of models are often used for dynamic cost-effectiveness analyses: compartmental models and individual models. In this methodology-focused literature review, we describe each model type and summarize the literature associated with each using the example of health care-associated infections (HAIs).

METHODS

We conducted a review of the literature to identify dynamic cost-effectiveness analyses that examined interventions to prevent or treat HAIs. To be included in the review, studies needed to have each of 3 necessary components: involve economics, such as cost-effectiveness analysis and evidence of economic theory, use a dynamic transmission model, and examine HAIs.

RESULTS

Of the 9 articles published between 2005 and 2016 that met criteria to be included in our study, 3 used compartmental models and 6 used individual models.

CONCLUSIONS

Very few published studies exist that use dynamic transmission models to conduct economic analyses related to HAIs and even fewer studies have used these models to perform cost-effectiveness analyses.

Structural Sensitivity in HIV Modeling: A Case Study of Vaccination

Structural assumptions in infectious disease models, such as the choice of network or compartmental model type or the inclusion of different types of heterogeneity across individuals, might affect model predictions as much as or more than the choice of input parameters. We explore the potential implications of structural assumptions on HIV model predictions and policy conclusions. We illustrate the value of inference robustness assessment through a case study of the effects of a hypothetical HIV vaccine in multiple population subgroups over eight related transmission models, which we sequentially modify to vary over two dimensions: parameter complexity (e.g., the inclusion of age and HCV comorbidity) and contact/simulation complexity (e.g., aggregated compartmental vs. individual/disaggregated compartmental vs. network models). We find that estimates of HIV incidence reductions from network models and individual compartmental models vary, but those differences are overwhelmed by the differences in HIV incidence between such models and the aggregated compartmental models (which aggregate groups of individuals into compartments). Complexities such as age structure appear to buffer the effects of aggregation and increase the threshold of net vaccine effectiveness at which aggregated models begin to overestimate reductions. The differences introduced by parameter complexity in estimated incidence reduction also translate into substantial differences in cost-effectiveness estimates. Parameter complexity does not appear to play a consistent role in differentiating the projections of network models.

Using Parameter Constraints to Choose State Structures in Cost-Effectiveness Modelling

BACKGROUND

This article addresses the choice of state structure in a cost-effectiveness multi-state model. Key model outputs, such as treatment recommendations and prioritisation of future research, may be sensitive to state structure choice. For example, it may be uncertain whether to consider similar disease severities or similar clinical events as the same state or as separate states. Standard statistical methods for comparing models require a common reference dataset but merging states in a model aggregates the data, rendering these methods invalid.

METHODS

We propose a method that involves re-expressing a model with merged states as a model on the larger state space in which particular transition probabilities, costs and utilities are constrained to be equal between states. This produces a model that gives identical estimates of cost effectiveness to the model with merged states, while leaving the data unchanged. The comparison of state structures can be achieved by comparing maximised likelihoods or information criteria between constrained and unconstrained models. We can thus test whether the costs and/or health consequences for a patient in two states are the same, and hence if the states can be merged. We note that different structures can be used for rates, costs and utilities, as appropriate.

APPLICATION

We illustrate our method with applications to two recent models evaluating the cost effectiveness of prescribing anti-depressant medications by depression severity and the cost effectiveness of diagnostic tests for coronary artery disease.

CONCLUSIONS

State structures in cost-effectiveness models can be compared using standard methods to compare constrained and unconstrained models.

The Potential Cost-Effectiveness of HIV Vaccines: A Systematic Review

OBJECTIVE

The aim of this paper was to review and compare HIV vaccine cost-effectiveness analyses and describe the effects of uncertainty in model, methodology, and parameterization.

METHODS

We systematically searched MEDLINE (1985 through May 2016), EMBASE, the Tufts CEA Registry, and reference lists of articles following Cochrane guidelines and PRISMA reporting. Eligibility criteria included peer-reviewed manuscripts with economic models estimating cost-effectiveness of preventative HIV vaccines. Two reviewers independently assessed study quality and extracted data on model assumptions, characteristics, input parameters, and outcomes.

RESULTS

The search yielded 71 studies, of which 11 met criteria for inclusion. Populations included low-income (n=7), middle-income (n=4), and high-income countries (n=2). Model structure varied including decision tree (n=1), Markov (n=5), compartmental (n=4), and microsimulation (n=1). Most measured outcomes in quality adjusted life-years (QALYs) gained (n=6) while others used unadjusted (n=3) or disability adjusted life-years (n=2). HIV vaccine cost ranged from $1.54 -$75 USD in low-income countries, $55-$100 in middle-income countries, and $500-$1,000 in the United States. Base case ICERs ranged from dominant (cost-offsetting) to $91,000 per QALY gained.

CONCLUSION

Most models predicted HIV vaccines would be cost-effective. Model assumptions about vaccine price, HIV treatment costs, epidemic context, and willingness to pay influenced results more consistently than assumptions on HIV transmission dynamics.

Estimating long-term clinical effectiveness and cost-effectiveness of HPV 16/18 vaccine in China

BACKGROUND

Human papillomavirus (HPV) 16 and 18 are the two most common HPV oncogenic types that can be prevented by vaccination. This study aimed at assessing the cost-effectiveness of 3 doses of the bivalent HPV vaccine in rural and urban settings in China.

METHODS

A Markov model was adapted to reflect the lifetime of a modelled 100,000 12-year-old girls cohort in rural and urban settings in China. Input parameters were obtained from published literature, official reports and a two-round expert review panel. Clinical and economic outcomes of vaccination at age 12 with screening was compared to screening only. In the base case analysis, a 3 % discount rate, the vaccine cost of 247 CNY (US$ 39, PAHO vaccine cost in 2013), two rounds of screening in a life time and 70 % coverage for both screening and vaccination were used. One-way, two-way and probabilistic sensitivity analyses were performed. We used different thresholds of cost-effectiveness to reflect the diversity of economic development in China.

RESULTS

Vaccination in addition to screening could prevent 60 % more cervical cancer cases and deaths than screening only. The incremental cost effectiveness ratio varied largely when changing cost of vaccination and discount in one way analysis. Vaccination was very cost-effective when the vaccine cost ranged 87-630 CNY (US$ 13.8-100) in rural and 87-750 CNY (US$ 13.8-119) in urban; and remained cost-effective when the vaccine cost ranged 630-1,700 CNY (US$ 100-270) in rural and 750-1,900 CNY (US$ 119-302) in urban in two way analysis. Probabilistic sensitivity analyses showed that model results were robust.

CONCLUSIONS

In both rural and urban, the vaccination cost and discounting are important factors determining the cost-effectiveness of HPV vaccination; policy makers in China should take these into account when making a decision on the introduction of HPV vaccine. In areas with a high burden of cervical cancer and limited screening activities, HPV vaccination should be prioritized. However, the vaccine cost needs to be reduced in order to make it very cost-effective and affordable as well, in particular in poverty areas with high disease burden.

Methods to construct a step-by-step beginner's guide to decision analytic cost-effectiveness modeling

BACKGROUND

Although guidance on good research practice in health economic modeling is widely available, there is still a need for a simpler instructive resource which could guide a beginner modeler alongside modeling for the first time.

AIM

To develop a beginner's guide to be used as a handheld guide contemporaneous to the model development process.

METHODS

A systematic review of best practice guidelines was used to construct a framework of steps undertaken during the model development process. Focused methods review supplemented this framework. Consensus was obtained among a group of model developers to review and finalize the content of the preliminary beginner's guide. The final beginner's guide was used to develop cost-effectiveness models.

RESULTS

Thirty-two best practice guidelines were data extracted, synthesized, and critically evaluated to identify steps for model development, which formed a framework for the beginner's guide. Within five phases of model development, eight broad submethods were identified and 19 methodological reviews were conducted to develop the content of the draft beginner's guide. Two rounds of consensus agreement were undertaken to reach agreement on the final beginner's guide. To assess fitness for purpose (ease of use and completeness), models were developed independently and by the researcher using the beginner's guide.

CONCLUSION

A combination of systematic review, methods reviews, consensus agreement, and validation was used to construct a step-by-step beginner's guide for developing decision analytical cost-effectiveness models. The final beginner's guide is a step-by-step resource to accompany the model development process from understanding the problem to be modeled, model conceptualization, model implementation, and model checking through to reporting of the model results.

Methods for Health Economic Evaluation of Vaccines and Immunization Decision Frameworks: A Consensus Framework from a European Vaccine Economics Community

BACKGROUND

Incremental cost-effectiveness and cost-utility analyses [health economic evaluations (HEEs)] of vaccines are routinely considered in decision making on immunization in various industrialized countries. While guidelines advocating more standardization of such HEEs (mainly for curative drugs) exist, several immunization-specific aspects (e.g. indirect effects or discounting approach) are still a subject of debate within the scientific community.

OBJECTIVE

The objective of this study was to develop a consensus framework for HEEs of vaccines to support the development of national guidelines in Europe.

METHODS

A systematic literature review was conducted to identify prevailing issues related to HEEs of vaccines. Furthermore, European experts in the field of health economics and immunization decision making were nominated and asked to select relevant aspects for discussion. Based on this, a workshop was held with these experts. Aspects on 'mathematical modelling', 'health economics' and 'decision making' were debated in group-work sessions (GWS) to formulate recommendations and/or--if applicable--to state 'pros' and 'contras'.

RESULTS

A total of 13 different aspects were identified for modelling and HEE: model selection, time horizon of models, natural disease history, measures of vaccine-induced protection, duration of vaccine-induced protection, indirect effects apart from herd protection, target population, model calibration and validation, handling uncertainty, discounting, health-related quality of life, cost components, and perspectives. For decision making, there were four aspects regarding the purpose and the integration of HEEs of vaccines in decision making as well as the variation of parameters within uncertainty analyses and the reporting of results from HEEs. For each aspect, background information and an expert consensus were formulated.

CONCLUSIONS

There was consensus that when HEEs are used to prioritize healthcare funding, this should be done in a consistent way across all interventions, including vaccines. However, proper evaluation of vaccines implies using tools that are not commonly used for therapeutic drugs. Due to the complexity of and uncertainties around vaccination, transparency in the documentation of HEEs and during subsequent decision making is essential.

Lifestyle Interventions to Prevent Type 2 Diabetes: A Systematic Review of Economic Evaluation Studies

Objective. To summarize key findings of economic evaluations of lifestyle interventions for the primary prevention of type 2 diabetes (T2D) in high-risk subjects. Methods. We conducted a systematic review of peer-reviewed original studies published since January 2009 in English, French, and Spanish. Eligible studies were identified through relevant databases including PubMed, Medline, National Health Services Economic Evaluation, CINHAL, EconLit, Web of sciences, EMBASE, and the Latin American and Caribbean Health Sciences Literature. Studies targeting obesity were also included. Data were extracted using a standardized method. The BMJ checklist was used to assess study quality. The heterogeneity of lifestyle interventions precluded a meta-analysis. Results. Overall, 20 studies were retained, including six focusing on obesity control. Seven were conducted within trials and 13 using modeling techniques. T2D prevention by physical activity or diet or both proved cost-effective according to accepted thresholds, except for five inconclusive studies, three on diabetes prevention and two on obesity control. Most studies exhibited limitations in reporting results, primarily with regard to generalizability and justification of selected sensitivity parameters. Conclusion. This confirms that lifestyle interventions for the primary prevention of diabetes are cost-effective. Such interventions should be further promoted as sound investment in the fight against diabetes.

Dissecting the indirect effects caused by vaccines into the basic elements

Vaccination directly protects vaccinated individuals, but it also has the potential for indirectly protecting the unvaccinated in a population (herd protection). Unintended negative consequences such as the re-manifestation of infection, mainly expressed as age shifts, result from vaccination programs as well. We discuss the necessary conditions for achieving optimal herd protection (i.e., high quality vaccine-induced immunity, substantial effect on the force of infection, and appropriate vaccine coverage and distribution), as well as the conditions under which age shifts are likely to occur. We show examples to illustrate these effects. Substantial ambiguity in observing and quantifying these indirect vaccine effects makes accurate evaluation troublesome even though the nature of these outcomes may be critical for accurate assessment of the economic value when decision makers are evaluating a novel vaccine for introduction into a particular region or population group. More investigation is needed to identify and develop successful assessment methodologies for precisely analyzing these outcomes.

Welfarism versus extra-welfarism: can the choice of economic evaluation approach impact on the adoption decisions recommended by economic evaluation studies?

A long-running debate surrounds the equivalence of the welfarist and extra-welfarist approaches to economic evaluation. There is a growing belief that the extra-welfarist approach may not necessarily provide all the information that decisionmakers require in certain contexts, e.g. evaluation of complex interventions. As the number of these interventions being evaluated increases, it is crucial that the most appropriate economic evaluation approach is used to enable decisionmakers to be confident in their adoption decisions. We conducted a literature review to evaluate the potential for the choice of economic evaluation approach to impact on the adoption decisions recommended by economic evaluation studies. We found that for every five studies applying both approaches, one shows limited or no concordance in economic evaluation results: the different approaches suggest conflicting adoption decisions, and there is no pattern to which approach provides the most convincing adoption evidence. Only one study in ten indicates which results will best inform adoption decisions. We conclude that the choice of approach can significantly impact on the adoption decisions recommended by economic evaluation studies, with conflicting results creating confusion over whether or not interventions provide good value for money. Health economists rarely provide sufficient guidance to decisionmakers to alleviate this confusion.

Exploring structural uncertainty in model-based economic evaluations

Given the inherent uncertainty in estimates produced by decision analytic models, the assessment of uncertainty in model-based evaluations is an essential part of the decision-making process. Although the impact of uncertainty around the choice of model structure and making incorrect structural assumptions on model predictions is noted, relatively little attention has been paid to characterising this type of uncertainty in guidelines developed by national funding bodies such as the Australian Pharmaceutical Benefits Advisory Committee (PBAC). The absence of a detailed description and evaluation of structural uncertainty can add further uncertainty to the decision-making process, with potential impact on the quality of funding decisions. This paper provides a summary of key elements of structural uncertainty describing why it matters and how it could be characterised. Five alternative approaches to characterising structural uncertainty are discussed, including scenario analysis, model selection, model averaging, parameterization and discrepancy. We argue that the potential effect of structural uncertainty on model predictions should be considered in submissions to national funding bodies; however, the characterisation of structural uncertainty is not well defined within the guidelines of these bodies. There has been little consideration of the forms of structural sensitivity analysis that might best inform applied decision-making processes, and empirical research in this area is required.

Do different decision-analytic modeling approaches produce different results? A systematic review of cross-validation studies

When choosing a modeling approach for health economic evaluation, certain criteria are often considered (e.g., population resolution, interactivity, time advancement mechanism, resource constraints). However, whether these criteria and their associated modeling approach impacts results remain poorly understood. A systematic review was conducted to identify cross-validation studies (i.e., modeling a problem using different approaches with the same body of evidence) to offer insight on this topic. With respect to population resolution, reviewed studies suggested that both aggregate- and individual-level models will generate comparable results, although a practical trade-off exists between validity and feasibility. In terms of interactivity, infectious-disease models consistently showed that, depending on the assumptions regarding probability of disease exposure, dynamic and static models may produce dissimilar results with opposing policy recommendations. Empirical evidence on the remaining criteria is limited. Greater discussion will therefore be necessary to promote a deeper understanding of the benefits and limits to each modeling approach.

How robust are the natural history parameters used in chlamydia transmission dynamic models? A systematic review

Transmission dynamic models linked to economic analyses often form part of the decision making process when introducing new chlamydia screening interventions. Outputs from these transmission dynamic models can vary depending on the values of the parameters used to describe the infection. Therefore these values can have an important influence on policy and resource allocation. The risk of progression from infection to pelvic inflammatory disease has been extensively studied but the parameters which govern the transmission dynamics are frequently neglected. We conducted a systematic review of transmission dynamic models linked to economic analyses of chlamydia screening interventions to critically assess the source and variability of the proportion of infections that are asymptomatic, the duration of infection and the transmission probability. We identified nine relevant studies in Pubmed, Embase and the Cochrane database. We found that there is a wide variation in their natural history parameters, including an absolute difference in the proportion of asymptomatic infections of 25% in women and 75% in men, a six-fold difference in the duration of asymptomatic infection and a four-fold difference in the per act transmission probability. We consider that much of this variation can be explained by a lack of consensus in the literature. We found that a significant proportion of parameter values were referenced back to the early chlamydia literature, before the introduction of nucleic acid modes of diagnosis and the widespread testing of asymptomatic individuals. In conclusion, authors should use high quality contemporary evidence to inform their parameter values, clearly document their assumptions and make appropriate use of sensitivity analysis. This will help to make models more transparent and increase their utility to policy makers.

Reducing social inequalities in health: the role of simulation modelling in chronic disease epidemiology to evaluate the impact of population health interventions

Reducing health inequalities has become a major public health priority internationally. However, how best to achieve this goal is not well understood. Population health intervention research has the potential to address some of this knowledge gap. This review argues that simulation studies can produce unique evidence to build the population health intervention research evidence base on reducing social inequalities in health. To this effect, the advantages of using simulation models over other population health intervention research methods are discussed. Key questions regarding the potential challenges of developing simulation models to investigate population health intervention research on reducing social inequalities in health and the types of population health intervention research questions that can be answered using this methodology are reviewed. We use the example of social inequalities in coronary heart disease to illustrate how simulation models can elucidate the effectiveness of a number of ‘what-if’ counterfactual population health interventions on reducing social inequalities in coronary heart disease. Simulation models are a flexible, cost-effective, evidence-based research method with the capacity to inform public health policy-makers regarding the implementation of population health interventions to reduce social inequalities in health.

Pharmacoeconomic spotlight on rotavirus vaccine RIX4414 (Rotarix™) in developed countries

The most common cause of severe diarrhea in infants and young children is rotavirus gastroenteritis (RVGE), which is associated with significant morbidity, healthcare resource use, and direct and indirect costs in industrialized nations. The monovalent rotavirus vaccine RIX4414 (Rotarix™) is administered as a two-dose oral series in infants and has demonstrated protective efficacy against RVGE in clinical trials conducted in developed countries. In addition, various naturalistic studies have demonstrated ‘real-world’ effectiveness after the introduction of widespread rotavirus vaccination programs in the community setting.

Numerous cost-effectiveness analyses have been conducted in developed countries in which a universal rotavirus vaccination program using RIX4414 was compared with no universal rotavirus vaccination program. There was a high degree of variability in base-case results across studies even when the studies were conducted in the same country, often reflecting differences in the selection of data sources or assumptions used to populate the models. In addition, results were sensitive to plausible changes in a number of key input parameters. As such, it is not possible to definitively state whether a universal rotavirus vaccination program with RIX4414 is cost effective in developed countries, although results of some analyses in some countries suggest this is the case. In addition, international guidelines advocate universal vaccination of infants and children against rotavirus. It is also difficult to draw conclusions regarding the cost effectiveness of rotavirus vaccine RIX4414 relative to that of the pentavalent rotavirus vaccine, which is administered as a three-dose oral series. Although indirect comparisons in cost-effectiveness analyses indicate that RIX4414 provided more favorable incremental cost-effectiveness ratios when each vaccine was compared with no universal rotavirus vaccination program, results were generally sensitive to vaccine costs. Actual tender prices of a full vaccination course for each vaccine were not known at the time of the analyses and therefore had to be estimated.

A novel method to value real options in health care: the case of a multicohort human papillomavirus vaccination strategy

BACKGROUND

A large number of economic evaluations have already confirmed the cost-effectiveness of different human papillomavirus (HPV) vaccination strategies. Standard analyses might not capture the full economic value of novel vaccination programs because the cost-effectiveness paradigm fails to take into account the value of active management. Management decisions can be seen as real options, a term used to refer to the application of option pricing theory to the valuation of investments in nonfinancial assets in which much of the value is attributable to flexibility and learning over time.

OBJECTIVE

The aim of this article was to discuss the potential advantages shown by using the payoff method in the valuation of the cost-effectiveness of competing HPV immunization programs.

METHODS

This was the first study, to the best of our knowledge, to use the payoff method to determine the real option values of 4 different HPV vaccination strategies targeting female subjects aged 12, 15, 18, and 25 years. The payoff method derives the real option value from the triangular payoff distribution of the project's net present value, which is treated as a triangular fuzzy number. To inform the real option model, cost-effectiveness data were derived from an empirically calibrated Bayesian model designed to assess the cost-effectiveness of a multicohort HPV vaccination strategy in the context of the current cervical cancer screening program in Italy. A net health benefit approach was used to calculate the expected fuzzy net present value for each of the 4 vaccination strategies evaluated.

RESULTS

Costs per quality-adjusted life-year gained seemed to be related to the number of cohorts targeted: a single cohort of girls aged 12 years (€10,955 [95% CI, -1,021 to 28,212]) revealed the lowest cost among the 4 alternative strategies evaluated. The real option valuation challenged the cost-effectiveness dominance of a single cohort of 12-year-old girls. The simultaneous vaccination of 2 cohorts of girls aged 12 and 15 years yielded a real option value (€17,723) equivalent to that attributed to a single cohort of 12-year-old girls (€17,460).

CONCLUSIONS

The payoff method showed distinctive advantages in the valuation of the cost-effectiveness of competing health care interventions, essentially determined by the replacement of the nonfuzzy numbers that are commonly used in cost-effectiveness analysis models, with fuzzy numbers as an input to inform the real option pricing method. The real option approach to value uncertainty makes policy making in health care an evolutionary process and creates a new "space" for decision-making choices.

Dynamic transmission modeling: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force Working Group-5

The transmissible nature of communicable diseases is what sets them apart from other diseases modeled by health economists. The probability of a susceptible individual becoming infected at any one point in time (the force of infection) is related to the number of infectious individuals in the population, will change over time, and will feed back into the future force of infection. These nonlinear interactions produce transmission dynamics that require specific consideration when modeling an intervention that has an impact on the transmission of a pathogen. Best practices for designing and building these models are set out in this paper.

Novel health economic evaluation of a vaccination strategy to prevent HPV-related diseases: the BEST study

BACKGROUND

The development of human papillomavirus (HPV)-related diseases is not understood perfectly and uncertainties associated with commonly utilized probabilistic models must be considered. The study assessed the cost-effectiveness of a quadrivalent-based multicohort HPV vaccination strategy within a Bayesian framework.

METHODS

A full Bayesian multicohort Markov model was used, in which all unknown quantities were associated with suitable probability distributions reflecting the state of currently available knowledge. These distributions were informed by observed data or expert opinion. The model cycle lasted 1 year, whereas the follow-up time horizon was 90 years. Precancerous cervical lesions, cervical cancers, and anogenital warts were considered as outcomes.

RESULTS

The base case scenario (2 cohorts of girls aged 12 and 15 y) and other multicohort vaccination strategies (additional cohorts aged 18 and 25 y) were cost-effective, with a discounted cost per quality-adjusted life-year gained that corresponded to €12,013, €13,232, and €15,890 for vaccination programs based on 2, 3, and 4 cohorts, respectively. With multicohort vaccination strategies, the reduction in the number of HPV-related events occurred earlier (range, 3.8-6.4 y) when compared with a single cohort. The analysis of the expected value of information showed that the results of the model were subject to limited uncertainty (cost per patient = €12.6).

CONCLUSIONS

This methodological approach is designed to incorporate the uncertainty associated with HPV vaccination. Modeling the cost-effectiveness of a multicohort vaccination program with Bayesian statistics confirmed the value for money of quadrivalent-based HPV vaccination. The expected value of information gave the most appropriate and feasible representation of the true value of this program.

Categorization of methods used in cost-effectiveness analyses of vaccination programs based on outcomes from dynamic transmission models

The aim of this study is to categorize methods used to estimate the cost-effectiveness of vaccination programs using dynamic transmission models, and assess value to decision-makers. A targeted literature search of PubMed has been carried out for this purpose. A review of 43 articles presenting cost-effectiveness analyses of vaccination programs based on dynamic transmission models identified four methods for the estimation of a cost-effectiveness ratio: cumulative population values over a fixed time horizon; population values for a steady-state year; cohort values from time of program initiation; and cohort values at steady state. Cost-effectiveness estimates are sensitive to the choice of time horizon or number of cohorts included. Estimates at steady state are the most comparable to estimates for other healthcare interventions but do not account for pre-steady-state periods. Population values provide estimates of budget impact. In conclusion, four different methods were identified for converting clinical outcomes from a dynamic transmission model to cost-effectiveness estimates. Sensitivity analyses for time horizon or number of cohorts considered should be routinely performed.

Estimating and comparing the clinical and economic impact of paediatric rotavirus vaccination in Turkey using a simple versus an advanced model

BACKGROUND

The burden of rotavirus disease is high in Turkey, reflecting the large birth cohort (>1.2 million) and the risk of disease. Modelling can help to assess the potential economic impact of vaccination. We compared the output of an advanced model with a simple model requiring fewer data inputs. If the results are similar, this could be helpful for countries that have few data available.

METHODS

The advanced model was a previously published static Markov cohort model comparing costs and quality-adjusted life-year (QALY) outcomes of vaccination versus no vaccination. In contrast, the simple model used only a decision tree. Both models included data on demography, epidemiology, vaccine efficacy, resource use, unit costs, and utility scores from national databases and published papers. Only the perspective of the health care payer was considered in the analysis. The simple model had 23 variables, compared with 103 in the advanced model to allow additional comparisons of different vaccine types, dose schemes and vaccine waning.

RESULTS

With the same input data, both models showed that rotavirus vaccination in Turkey would improve health outcomes (fewer QALYs lost to rotavirus disease). The projected annual cost offsets were $29.9 million in the simple and $29.4 million in the advanced model. Sensitivity analysis indicated that in both models the main cost driver was disease incidence followed by cost for hospital care and medical visits. Vaccine efficacy had a smaller effect.

CONCLUSION

Both models reached similar conclusions. Both projected that rotavirus vaccination in Turkey would improve health outcomes and may result in savings in direct healthcare costs to offset the cost of vaccination. The analysis indicated that the simple model can produce meaningful economic results in conditions where few data are available.

Model Parameter Estimation and Uncertainty Analysis

A model’s purpose is to inform medical decisions and health care resource allocation. Modelers employ quantitative methods to structure the clinical, epidemiological, and economic evidence base and gain qualitative insight to assist decision makers in making better decisions. From a policy perspective, the value of a model-based analysis lies not simply in its ability to generate a precise point estimate for a specific outcome but also in the systematic examination and responsible reporting of uncertainty surrounding this outcome and the ultimate decision being addressed. Different concepts relating to uncertainty in decision modeling are explored. Stochastic (first-order) uncertainty is distinguished from both parameter (second-order) uncertainty and from heterogeneity, with structural uncertainty relating to the model itself forming another level of uncertainty to consider. The article argues that the estimation of point estimates and uncertainty in parameters is part of a single process and explores the link between parameter uncertainty through to decision uncertainty and the relationship to value-of-information analysis. The article also makes extensive recommendations around the reporting of uncertainty, both in terms of deterministic sensitivity analysis techniques and probabilistic methods. Expected value of perfect information is argued to be the most appropriate presentational technique, alongside cost-effectiveness acceptability curves, for representing decision uncertainty from probabilistic analysis.

Improving the Accuracy and Comparability of Model-Based Economic Evaluations of Health Technologies for Reimbursement Decisions

Increasingly, decision analytic models are used within economic evaluations of health technologies (e.g., pharmaceuticals) submitted to national reimbursement bodies in countries like Australia and UK, where such models play a fundamental role in informing public funding decisions. Concerns regarding the accuracy of model outputs and hence the credibility of national reimbursement decisions are frequently raised. We propose a framework for developing reference models for specific diseases to inform economic evaluations of health technologies and their appraisal. The structure of a reference model reflects the natural history of the condition under study and defines the clinical events to be represented, the relationships between the events, and the effect of patient characteristics on the probability and timing of events. We contend that the use of reference models will improve the accuracy and comparability of public funding decisions. This can lead to the more efficient allocation of public funds.

Dynamic transmission modeling: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--5

The transmissible nature of communicable diseases is what sets them apart from other diseases modeled by health economists. The probability of a susceptible individual becoming infected at any one point in time (the force of infection) is related to the number of infectious individuals in the population, will change over time, and will feed back into the future force of infection. These nonlinear interactions produce transmission dynamics that require specific consideration when modeling an intervention that has an impact on the transmission of a pathogen. Best practices for designing and building these models are set out in this article.

Model parameter estimation and uncertainty: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--6

A model's purpose is to inform medical decisions and health care resource allocation. Modelers employ quantitative methods to structure the clinical, epidemiological, and economic evidence base and gain qualitative insight to assist decision makers in making better decisions. From a policy perspective, the value of a model-based analysis lies not simply in its ability to generate a precise point estimate for a specific outcome but also in the systematic examination and responsible reporting of uncertainty surrounding this outcome and the ultimate decision being addressed. Different concepts relating to uncertainty in decision modeling are explored. Stochastic (first-order) uncertainty is distinguished from both parameter (second-order) uncertainty and from heterogeneity, with structural uncertainty relating to the model itself forming another level of uncertainty to consider. The article argues that the estimation of point estimates and uncertainty in parameters is part of a single process and explores the link between parameter uncertainty through to decision uncertainty and the relationship to value of information analysis. The article also makes extensive recommendations around the reporting of uncertainty, in terms of both deterministic sensitivity analysis techniques and probabilistic methods. Expected value of perfect information is argued to be the most appropriate presentational technique, alongside cost-effectiveness acceptability curves, for representing decision uncertainty from probabilistic analysis.

Direct and indirect effects of rotavirus vaccination: comparing predictions from transmission dynamic models

Early observations from countries that have introduced rotavirus vaccination suggest that there may be indirect protection for unvaccinated individuals, but it is unclear whether these benefits will extend to the long term. Transmission dynamic models have attempted to quantify the indirect protection that might be expected from rotavirus vaccination in developed countries, but results have varied. To better understand the magnitude and sources of variability in model projections, we undertook a comparative analysis of transmission dynamic models for rotavirus. We fit five models to reported rotavirus gastroenteritis (RVGE) data from England and Wales, and evaluated outcomes for short- and long-term vaccination effects. All of our models reproduced the important features of rotavirus epidemics in England and Wales. Models predicted that during the initial year after vaccine introduction, incidence of severe RVGE would be reduced 1.8–2.9 times more than expected from the direct effects of the vaccine alone (28–50% at 90% coverage), but over a 5-year period following vaccine introduction severe RVGE would be reduced only by 1.1–1.7 times more than expected from the direct effects (54–90% at 90% coverage). Projections for the long-term reduction of severe RVGE ranged from a 55% reduction at full coverage to elimination with at least 80% coverage. Our models predicted short-term reductions in the incidence of RVGE that exceeded estimates of the direct effects, consistent with observations from the United States and other countries. Some of the models predicted that the short-term indirect benefits may be offset by a partial shifting of the burden of RVGE to older unvaccinated individuals. Nonetheless, even when such a shift occurs, the overall reduction in severe RVGE is considerable. Discrepancies among model predictions reflect uncertainties about age variation in the risk and reporting of RVGE, and the duration of natural and vaccine-induced immunity, highlighting important questions for future research.

Treating childhood pneumonia in hard-to-reach areas: a model-based comparison of mobile clinics and community-based care

Background

Where hard-to-access populations (such as those living in insecure areas) lack access to basic health services, relief agencies, donors, and ministries of health face a dilemma in selecting the most effective intervention strategy. This paper uses a decision mathematical model to estimate the relative effectiveness of two alternative strategies, mobile clinics and fixed community-based health services, for antibiotic treatment of childhood pneumonia, the world's leading cause of child mortality.

Methods

A "Markov cycle tree" cohort model was developed in Excel with Visual Basic to compare the number of deaths from pneumonia in children aged 1 to 59 months expected under three scenarios: 1) No curative services available, 2) Curative services provided by a highly-skilled but intermittent mobile clinic, and 3) Curative services provided by a low-skilled community health post. Parameter values were informed by literature and expert interviews. Probabilistic sensitivity analyses were conducted for several plausible scenarios.

Results

We estimated median pneumonia-specific under-5 mortality rates of 0.51 (95% credible interval: 0.49 to 0.541) deaths per 10,000 child-days without treatment, 0.45 (95% CI: 0.43 to 0.48) with weekly mobile clinics, and 0.31 (95% CI: 0.29 to 0.32) with CHWs in fixed health posts. Sensitivity analyses found the fixed strategy superior, except when mobile clinics visited communities daily, where rates of care-seeking were substantially higher at mobile clinics than fixed posts, or where several variables simultaneously differed substantially from our baseline assumptions.

Conclusions

Current evidence does not support the hypothesis that mobile clinics are more effective than CHWs. A CHW strategy therefore warrants consideration in high-mortality, hard-to-access areas. Uncertainty remains, and parameter values may vary across contexts, but the model allows preliminary findings to be updated as new or context-specific evidence becomes available. Decision analytic modelling can guide needed field-based research efforts in hard-to-access areas and offer evidence-based insights for decision-makers.