Economic Modeling Research Articles

Exploring the significance and priority of digital product passports implementation in building renovation projects targeting circular economy

PurposeThis study explores the significance and implementation priorities for Digital Product Passports (DPP) in the context of building renovation projects. It aims to reveal bottlenecks and how a data-driven workflow bridges the DPP understanding/implementation gap, facilitating the transition towards practices aligned with the EU Green Deal goals.Design/methodology/approachA mixed-methods embedded design was employed for a real-case study exploration. Desk research and field observations ground the two-level analysis combining project documentation, namely the Bill of Quantities (BoQ), with different criteria in digitalisation and sustainability, such as economic ratio, 3D modelling, waste management, hazards, energy performance and facility management. All results were interpreted from the DPP lens.FindingsThe analysis revealed a system for identifying building products representing a significant part of the renovation budget. About 11 priority DPPs were found. Some are crucial for both the deconstruction and construction phases, highlighting the need for an incremental and strategic approach to DPP implementation.Research limitations/implicationsThe study is limited to a single case study. Constraints are minimised given the sample's archetype representativeness. The outcomes introduce the need for strategic thinking for incremental DPP implementation. Future research will explore additional criteria and cases.Originality/valueThe research has resulted in a classification framework for DPPs' significance and priority, which is provided with case results. The outcome of the framework provides views on concept alignment to make the implementation in construction more straightforward. Its practical use can be replicated in other projects, emphasizing the importance of data structure and management for the circular economy.

Strengthening China’s National Essential Public Health Services Package for hypertension and diabetes care: protocol for an interrupted time series study with mixed-methods process evaluation and health economic evaluation

BackgroundDespite major primary health care (PHC) reforms in China with the 2009 launch of the National Essential Public Health Service Package, the country experiences many challenges in improving the management of non-communicable diseases in PHC facilities. “EMERALD” is a multifaceted implementation strategy to strengthen the management of hypertension and type-2 diabetes mellitus (T2DM) in PHC facilities. The study aims to: (1) examine the effectiveness of EMERALD in improving hypertension and T2DM management; (2) evaluate the implementation of the interventions; and (3) use the study findings to model the long-term health economic impact of the interventions.MethodsThe EMERALD intervention components include: (1) empowerment for PHC providers through training and capacity building; (2) empowerment for patient communities through multi-media health education; and (3) empowerment for local health administrators through health data monitoring and strengthening governance of local PHC programs. An interrupted time series design will be used to determine the effectiveness of the interventions based on routinely collected health data extracted from local health information systems. The primary effectiveness outcome is the guideline-recommended treatment rates for people with hypertension and T2DM. Secondary effectiveness outcomes include hypertension and T2DM diagnosis and control rates, and enrolment and adherence rates to the recommended care processes in the National Essential Public Health Service Package. A mixed-methods process evaluation will be conducted to evaluate the implementation of the interventions, including the reach of the target population, adequacy of adoption, level of implementation fidelity, and maintenance. Qualitative interviews with policy makers, health administrators, PHC providers, and patients with hypertension and/or T2DM will be conducted to further identify factors influencing the implementation. In addition, health economic modelling will be performed to explore the long-term incremental costs and benefits of the interventions.DiscussionThis study is expected to generate important evidence on the effectiveness, implementation, and health economic impact of complex PHC interventions to strengthen the primary care sector’s contribution to addressing the growing burden of non-communicable diseases in China.Trial registrationThe study has been registered on Chinese Clinical Trial Registry at https://www.chictr.org.cn/ (Registration number ChiCTR2400082036, on March 19th 2024).

DEFINING COMPONENTS OF THE METHODOLOGICAL PLATFORM FOR FORMING A BUSINESS PORTFOLIO OF A COMPANY IN THE UPDATED FORMAT OF MODERN DEVELOPMENT

The article is devoted to the analysis of the economic and operational imperatives of forming a business portfolio for a development company in the construction sector. A successful business portfolio management strategy requires the integration of financial, organizational, and technological aspects to ensure the sustainability and competitiveness of the business. In modern conditions, real estate development is one of the key factors that determines the dynamics of enterprise development, as it includes a comprehensive approach to asset management, from planning and financing to the construction and operation of objects. The theoretical and methodological foundations of the genesis of development at the current stage of the construction market's evolution have been analyzed.The methodological platform for forming a business portfolio should be based on the principles of rational resource management, risk analysis, and technological optimization. Changes in development activities require the active use of digital tools and a comprehensive approach to managing residential, commercial, and industrial properties, which allows for the maximization of profitability and minimization of risks.The article discusses the main stages of portfolio formation, such as strategic planning, selection of investment objects, and their integration into the overall structure of the enterprise. An economic and mathematical formalization of the process is also provided. For the successful operation of a development company, it is crucial to ensure coordinated work at all stages of the project — from planning and financing to construction and commissioning of the facilities.Particular attention is paid to the methods of economic and mathematical modelling (EMM) and quantitative risk analysis, which have become the basis for the development of the latest asset management strategies. The study analyses 35 different techniques. Each methodology offers unique tools for the effective management of development projects that allow forecasting financial flows, determining optimal investment strategies, and building the best plans for the development of a real estate portfolio. The specific methods used to value residential, commercial and industrial real estate are also discussed, taking into account their different levels of risk and return.It is important to note that the updated methodological platform is suitable for adaptation to the latest technologies and digital tools. This includes the introduction of a project management system, the use of artificial intelligence technologies to analyse large amounts of data, and the use of analytical tools to predict market trends. This approach helps to optimise asset management in a changing market environment. The analysis of the main components of the business portfolio formation platform also showed that important factors for the successful implementation of development projects are the speed of response to market changes, flexibility of management decisions, and the ability to minimise risks at all stages of the project.

General Population Mortality Adjustment in Survival Extrapolation of Cancer Trials: Exploring Plausibility and Implications for Cost-Effectiveness Analyses in HER2-Positive Breast Cancer in Sweden.

In economic evaluations of novel therapies, assessing lifetime effects based on trial data often necessitates survival extrapolation, with the choice of model affecting outcomes. The aim of this study was to assess accuracy and variability between alternative approaches to survival extrapolation. Data on HER2-positive breast cancer patients from the Swedish National Breast Cancer Register were used to fit standard parametric distribution (SPD) models and excess hazard (EH) models adjusting the survival projections based on general population mortality (GPM). Models were fitted using 6-y data for stage I and II, 4-y data for stage III, and 2-y data for stage IV cancer reflecting an early data cutoff while maintaining sufficient events for comparison of model estimates with actual long-term outcomes. We compared model projections of 15-y survival and restricted mean survival time (RMST) to 15-y registry data and explored the variability between models in extrapolations of long-term survival. Among 11,224 patients compared with the observed registry 15-y RMST estimates across the disease stages, EH cure models provided the most accurate estimates in patients with stage I to III cancer, whereas EH models without cure most closely matched survival in patients with stage IV cancer, in which cure assumption was less plausible. The Akaike information criterion-averaged model projections varied as follows: -8.2% to +5.3% for SPD models, -4.9% to +5.2% for the EH model without a cure assumption, and -19.3% to -0.2% for the EH model with a cure assumption. EH models significantly reduced between-model variance in the predicted RMSTs over a 50-y time horizon compared with SPD models. EH models may be considered as alternatives to SPD models to produce more accurate and plausible survival extrapolation that accounts for general population mortality. Excess hazard (EH) methods have been suggested as an approach to incorporate background mortality rates in economic evaluation using survival extrapolation.We highlight that EH models with or without a cure assumption can produce more accurate survival projections and significantly reduce between-model variability in comparison with standard parametric distribution models across cancer stages.EH models may be a preferred modeling method to reduce model uncertainty in health economic modeling since models that would otherwise have produced implausible extrapolations are constrained by the EH framework.Reduced uncertainty in economic evaluations will enhance the application of evidence-based health care decision making.

A comparative review of de- and post-growth modeling studies

In recent years, a small but rapidly growing field of modeling alternatives to growth as represented by the de- (DG) and post-growth (PG) discourses has emerged. We compare selected model characteristics of 75 DG and PG related modeling studies, compiled through a systematic literature review (2000−2023), and link model structures and results to different theoretically contested debates surrounding DG/PG. The reviewed studies cover different geographical and temporal scopes, economic theories, modeling techniques and operationalizations of DG/PG. The majority of studies models DG/PG as intentional transition and does not question its compatibility with a capitalist system, while more radical strands of the DG/PG discourse are excluded. Although DG/PG modeling exercises frequently explore the effects of sustainability policies, they represent only a fraction of theoretical DG policy proposals, with the most frequent being: working time reduction, maximum income caps, carbon taxes and a universal basic income. DG/PG modeling studies have demonstrated the importance of integrating biophysical constraints in economic modeling but also have quantitatively assessed the feasibility of environmental integrity and social well-being without growth. Nonetheless, future modeling could be rendered more realistic by paying more attention to the Global South, introducing heterogeneous agents driving sustainability transitions and including multiple planetary boundaries.

Foslevodopa/foscarbidopa (LDp/CDp) in advanced Parkinson’s Disease (aPD): demonstration of savings from a societal perspective in the UK

Aims In advanced Parkinson’s disease (aPD), adequate 24-hour control of OFF-time may not be achievable using oral/transdermal therapies. Clinical trials of foslevodopa/foscarbidopa (LDp/CDP) demonstrate meaningful reductions in OFF-time and OFF-related sleep disturbance in aPD. Previous analyses have only considered direct medical costs: this analysis considers a broader societal perspective (direct non-medical costs, informal care, loss of earnings, productivity and tax). Methods Inputs for the societal impact model were taken from a cost-utility model comparing LDp/CDp with best medical treatment (BMT), accepted by the UK National Institute of Health and Care Excellence (NICE). Quintiles of normalized OFF-time across a 16-hour waking day in each treatment group were applied to literature-based estimates for direct medical, non-medical and indirect costs. The resulting state-specific cost estimates were applied to the modelled aPD patient population. Results The model estimates the potential UK population for LDp/CDp at 17,505. Continuous 24-hour delivery of LDp/CDp results in greater time spent in in OFF-time states 0-1 (0-4 hours of OFF-time/16-hour waking day) vs BMT alone. Net savings if all eligible patients receive LDp/CDp are £79.1M in year 1, £235.4M in year 2, rising to £262.2M in year 3, declining to £222.9M in year 4 and £153.7M in year 5 as disease progresses and efficacy of LDp/CDp declines, Estimated total net savings are £953M after 5 years. Results are robust in scenario analyses (excluding costs of excessive sleepiness, earnings loss, productivity and tax loss). Limitations A NICE-accepted model was used as the economic modelling basis for the societal impact model, however, much of the data was derived from Adelphi datasets, with the potential for inconsistent definitions. Conclusion When considered from a societal perspective, the use of LDp/CDp in aPD patients inadequately controlled on oral therapy, is associated with net healthcare and societal annual savings of over £79.1M vs BMT.

Статистический анализ влияния инноваций на производительность труда в субъектах ЦФО

The relevance of the research topic is due to the contradiction between the innovation activity of organisations and their contribution to regional socio-economic development. Innovation should lead to productivity growth and contribute to the creation of high-productivity jobs. However, the situation in many Russian regions is paradoxical one – despite of high innovation activity of small and medium-sized enterprises their labour productivity remains at the same level or decreases. The purpose of the research is to assess the impact of innovations on labour productivity for the Russian economy on the example of the Central Federal District regions. The paper verifies the hypothesis on the presence of statistically significant relationship between the indicators characterising the innovation activity of small and medium-sized enterprises, the index of labour productivity, and the growth of high-productive jobs in the Central Federal District regions through the methods of economic and mathematical modelling. According to the research results, the parameters of small and medium-sized enterprises innovation activity do not have a significant impact on the dynamics of socio-economic development of the Central Federal District regions.

Aging In The Face of Diabetes: Severe Hypoglycemia in Older Adults

Global rates of type 1 and type 2 diabetes (T1D, T2D) continue to climb, despite medical advancements. Older adults constitute one of the fastest growing segments of the diabetes population, backed by the world’s unprecedented aging population, decreased diabetes mortality rates, and the obesity epidemic. In Canada, individuals aged ≥65 years account for more than a quarter of all prevalent diabetes cases, far exceeding the other age groups. Older adults with diabetes face the highest risks of microvascular and macrovascular complications, which, compared to younger age cohorts, can contribute to significant functional loss, frailty, and premature mortality. A considerable amount of research links intensive glucose-lowering with insulin or secretagogues to reduced cardiovascular disease. However, the consequent risk of severe hypoglycemia and related sequelae can be particularly catastrophic for older adults, exacerbated by coexisting health conditions and age-related social needs. Approximately 40% of Canadians with T2D aged ≥65 years currently use secretagogues, while 27% use insulin—alongside all those with T1D. Longitudinal evidence suggests that since the year 2000, hospital admission rates for hypoglycemia have consistently surpassed those for hyperglycemia, especially among individuals aged 75 years and above. Economic modelling estimates that the Canadian healthcare system spends $125,932 CAD per year on iatrogenic hypoglycemia, with the bulk of these costs likely allocated to people ≥65 years. Diabetes in older adults is a pressing public health issue in Canada, marked by clinical diversity and widespread use of medications that are prone to cause hypoglycemia. This review outlines recent epidemiologic findings on severe hypoglycemia among community-dwelling older adults with T1D or T2D treated with insulin or secretagogues. Understanding the complex factors contributing to severe hypoglycemia in this population is crucial for developing tailored prevention strategies that are both effective and safe.

Tapestry: Collaborative Tool for Regional Data and Modeling

This paper introduces and describes the Tapestry regional economic data and modeling project. Tapestry is an open source set of data generating algorithms, harmonization bridges, data organizing procedures and data models. It is also a database that provides access to Tapestry also represents a collaborative environment where researchers can use and improve data generating algorithms and methods. Tapestry represents many types of regional economic data and models, but ultimately it is designed to generate inter-regional social accounting matrices for every county in the United States.

Technology and the Global Economy

Interpreting individual heterogeneity in terms of probability theory has proved powerful in connecting behavior at the individual and aggregate levels. Returning to Ricardo's focus on comparative efficiency as a basis for international trade, much recent quantitative equilibrium modeling of the global economy builds on particular probabilistic assumptions about technology. We review these assumptions and discuss how they deliver a unified framework underlying a wide range of static and dynamic equilibrium models.

Multibenchmark reality checks

Empirical economic modelers often have to choose between two classes of models, with each class containing multiple models. In many cases, this decision is based on the predictive ability of the considered models. This entails that multiple testing and/or p-hacking pose known risks. This study presents a new statistical approach for comparing all model in a single test, serving as a multi-benchmark reality check test. The behavior of the test is studied asymptotically and in small finite samples. We show how the new approach works by analyzing whether one family of linear bivariate models outperforms a univariate family in predicting commodity prices. This paper raises new questions for future research. From an empirical viewpoint, we present several open questions in economic modeling that can be tested with multi-benchmark tests. Meanwhile, from a theoretical viewpoint, further studies can investigate whether a more general method for approximating or simulating the test distribution can be developed.

Transition of mild cognitive impairment to Alzheimer's disease: Medications as modifiable risk factors.

Mild cognitive impairment (MCI) is a pre-clinical stage of Alzheimer's disease (AD). Understanding the transition probabilities across the disease continuum of AD, ranging from MCI to AD to Mortality is crucial for the economic modeling of AD and effective planning of future interventions and healthcare resource allocation decisions. This study uses the Multi-state Markov model to quantify the transition probabilities along the disease progression and specifically investigates medications as modifiable risk factors of AD associated with accelerated or decelerated transition times from MCI to AD, MCI to mortality, and AD to mortality. Individuals with MCI were identified from the National Alzheimer's Coordinating Center between September 2005 and May 2021. A three-state Markov model was postulated to model the disease progression among three states: MCI, AD, and mortality with adjustment for demographics, genetic characteristics, comorbidities and medications. Transition probabilities, the total length of stay in each state, and the hazard ratios of the use of medications for diabetes, hypertension, and hypercholesterolemia (the known modifiable risk factors of AD) were evaluated for these transitions. 3,324 individuals with MCI were identified. The probability of developing AD after one year since the initial diagnosis of MCI is 14.9%. After approximately 6 years from the initial diagnosis of MCI, the probability of transitioning to AD increases to nearly 41.7% before experiencing a subsequent decline. The expected total lengths of stay were 5.38 (95% CI: 0.002-6.03) years at MCI state and 7.61 (95%CI: 0.002-8.88) years at AD state. Patients with active use of lipid-lowering agents were associated with significantly lower hazards of transitioning from MCI to AD (HR: 0.83, 95%CI:0.71-0.96), MCI to mortality (HR: 0.51, 95%CI:0.34-0.77), and AD to mortality (HR: 0.81, 95%CI:0.66-0.99). Results suggest that lipid-lowering agents may confer a protective effect, delaying the onset of AD. Additionally, lipid-lowering agents indicate a favorable association with a longer survival time.

Cost analysis of cardiac MRI for cardiac transplant surveillance

National health expenditures in the United States have risen steadily since 1960. While lifesaving therapies exist for acquired and congenital heart diseases, for some children heart transplantation is their only chance for a period of durable survival. Like many advanced therapies, however, heart transplantation confers a significant cost to families and the health care system at large. Current heart transplant health surveillance relies on frequent cardiac catheterization with endomyocardial biopsy (cath-EMB) as periodic assessment of graft health and detection of possible life-threatening acute rejection. Cardiac magnetic resonance imaging (MRI) has emerged as a diagnostic tool which can characterize the myocardium, providing insights into graft health and potentially acute/chronic graft rejection. The PEACE study (R01-HL164995-02) aims to systematically evaluate the potential for using cardiac MRI parametric mapping as a pre-cath-EMB screening tool to alleviate both patient anxiety and discomfort, as well as the financial burden of cath-EMB. The PEACE trial aims to establish definitive evidence and criteria for determining when cath EMB is needed. For a technique to be practical in the real world, though, it must also be cost effective.Therefore, the goal of this current research is to determine a minimal set of measurement properties (positive predictive value (PPV), etc.) that cardiac MRI must attain to be cost-effective. These data will guide the decision-making for the PEACE trial results. Consistent with the recent emphasis on “Value MRI,” we sought to understand the potential Medicare savings, through economic cost analysis modeling, if cardiac MRI is used for cardiac transplant surveillance rather than cath-EMB surveillance. At even the most pessimistic positive test rate for MRI considered, these modeling results suggest substantial Medicare cost savings when using cardiac MRI parametric mapping as a screening tool for detecting acute cardiac rejection. Longitudinal cost savings are notable too.

Empirical Testing of Alternative Search Methods to Retrieve Utility Values for Health Economic Modelling.

The objective of this study is to compare different information retrieval methods that can be used to identify utility inputs for health economic models. Theusual practice of using systematic review methods was compared with two alternatives (iterative searching and rapid review), using a health technology assessment (HTA) case study in ulcerative colitis (UC). We analysed whether there were differences in the utility values identified when using the alternative search methods. Success was evaluated in terms of time, burden and relevance of identified information. The identified utility values were tested in an executable health economic model developed for UC, and the model results were compared. The usual practice of using systematic review search approaches identified the most publications but was also the least precise method and took longest to complete.The inclusion of data from the different search methods in the model did not lead to different conclusions across search methods. In this case study, usual practice was less efficient and resulted in the same health economic model conclusions as the alternative search methods. Further case studies are required to examine whether this conclusion might be generalisable.

Determinants of the human capital development and the national economy: economic and mathematical modeling of the relationship

Determinants of the human capital development and the national economy: economic and mathematical modeling of the relationship

Evaluating the cost-effectiveness of Cy-Tb for LTBI in India: a comprehensive economic modelling analysis.

Latent tuberculosis infection (LTBI) remains a significant challenge, as there is no gold standard diagnostic test. Current methods used for identifying LTBI are the interferon-γ release assay (IGRA), which is based on a blood test, and the tuberculin skin test (TST), which has low sensitivity. Both these tests are inadequate, primarily because they have limitations with the low bacterial burden characteristic of LTBI. This highlights the need for the development and adoption of more specific and accurate diagnostic tests to effectively identify LTBI. Herein we estimate the cost-effectiveness of the Cy-Tb test as compared with the TST for LTBI diagnosis. An economic modelling study was conducted from a health system perspective using decision tree analysis, which is most widely used for cost-effectiveness analysis using transition probabilities. Our goal was to estimate the incremental cost and number of TB cases prevented from LTBI using the Cy-Tb diagnostic test along with TB preventive therapy (TPT). Secondary data such as demographic characteristics, treatment outcome, diagnostic test results and cost data for the TST and Cy-Tb tests were collected from the published literature. The incremental cost-effectiveness ratio was calculated for the Cy-Tb test as compared with the TST. The uncertainty in the model was evaluated using one-way sensitivity analysis and probability sensitivity analysis. The study findings indicate that for diagnosing an additional LTBI case with the Cy-Tb test and to prevent a TB case by providing TPT prophylaxis, an additional cost of 18658 Indian rupees (US${\$}$223.5) is required. The probabilistic sensitivity analysis indicated that using the Cy-Tb test for diagnosing LTBI was cost-effective as compared with TST testing. If the cost of the Cy-Tb test is reduced, it becomes a cost-saving strategy. The Cy-Tb test for diagnosing LTBI is cost-effective at the current price, and price negotiations could further change it into a cost-saving strategy. This finding emphasizes the need for healthcare providers and policymakers to consider implementing the Cy-Tb test to maximize economic benefits. Bulk procurements can also be considered to further reduce costs and increase savings.

Risk factors underlying racial and ethnic disparities in tuberculosis diagnosis and treatment outcomes, 2011–19: a multiple mediation analysis of national surveillance data

Despite an overall decline in tuberculosis incidence and mortality in the USA in the past two decades, racial and ethnic disparities in tuberculosis outcomes persist. We aimed to examine the extent to which inequalities in health and neighbourhood-level social vulnerability mediate these disparities. We extracted data from the US National Tuberculosis Surveillance System on individuals with tuberculosis during 2011-19. Individuals with multidrug-resistant tuberculosis or missing data on race and ethnicity were excluded. We examined potential disparities in tuberculosis outcomes among US-born and non-US-born individuals and conducted a mediation analysis for groups with a higher risk of treatment incompletion (a summary outcome comprising diagnosis after death, treatment discontinuation, or death during treatment). We used sequential multiple mediation to evaluate eight potential mediators: three comorbid conditions (HIV, end-stage renal disease, and diabetes), homelessness, and four census tract-level measures (poverty, unemployment, insurance coverage, and racialised economic segregation [measured by Index of Concentration at the ExtremesRace-Income]). We estimated the marginal contribution of each mediator using Shapley values. During 2011-19, 27 788 US-born individuals and 57 225 non-US-born individuals were diagnosed with active tuberculosis, of whom 27 605 and 56 253 individuals, respectively, met eligibility criteria for our analyses. We did not observe evidence of disparities in tuberculosis outcomes for non-US-born individuals by race and ethnicity. Therefore, subsequent analyses were restricted to US-born individuals. Relative to White individuals, Black and Hispanic individuals had a higher risk of not completing tuberculosis treatment (adjusted relative risk 1·27, 95% CI 1·19-1·35; 1·22, 1·11-1·33, respectively). In multiple mediator analysis, the eight measured mediators explained 67% of the disparity for Black individuals and 65% for Hispanic individuals. The biggest contributors to these disparities for Black individuals and Hispanic individuals were concomitant end-stage renal disease, concomitant HIV, census tract-level racialised economic segregation, and census tract-level poverty. Our findings underscore the need for initiatives to reduce disparities in tuberculosis outcomes among US-born individuals, particularly in highly racially and economically polarised neighbourhoods. Mitigating the structural and environmental factors that lead to disparities in the prevalence of comorbidities and their case management should be a priority. US Centers for Disease Control and Prevention National Center for HIV, Viral Hepatitis, STD, and Tuberculosis Prevention Epidemiologic and Economic Modeling Agreement.

The application of fractional calculus in economic growth modelling: An approach based on regression analysis

This paper establishes a fractional-order economic growth model to model the gross domestic product (GDP). The fractional-order model consists of a differential equation of integer and fractional orders, where the GDP is a function of several exploratory variables. An empirical application is adopted using Malaysia's GDP data from 1956 to 2018, incorporating exploratory variables such as total population, crude death rate, production of logs, gross fixed capital formation, exports of goods and services, general government final consumption expenditure, private final consumption expenditure, and the impact of investment. Extensive comparisons were carried out to evaluate the modelling performance of the full and reduced fractional-order multiple linear regression models with the benchmark models, namely full and reduced integer-order multiple linear regression models. Results indicate that the reduced fractional-order model with six exploratory variables, excluding the crude death rate and production of logs, predominates other models for the in-sample model fitting based on the Akaike information criterion, coefficient of determination and other criteria. Furthermore, the fractional-order model offers the best-of-sample forecasts evaluated based on the root mean square forecast error and mean absolute forecast error. The application of the Diebold–Mariano test also serves to confirm the superior performance of the suggested fractional-order model, revealing a significant difference in forecasting ability between the fractional-order and integer-order models.

Benefits of population-level interventions for dementia risk factors: an economic modelling study for England

Individual-level interventions for dementia risk factors could reduce costs associated with dementia and some are cost-effective. We aimed to estimate the cost-effectiveness of population-level interventions for tackling dementia risk factors. In this economic modelling study, we included recommended population-based interventions from a previously published review article for which there was consistent and robust evidence of effectiveness in tackling a dementia risk factor (tobacco smoking, excess alcohol use, hypertension, obesity, air pollution, and head injury). We only included interventions if they had not been introduced in England or were in place but could be extended. The interventions studied were increases in tobacco pricing, minimum pricing for alcohol, raising alcohol price, salt reduction policies, sugar reduction policies, low emission zones, and compulsory helmet use for cycling by children (aged 5-18years). We used published intervention effect sizes and relative risks for each risk factor and a Markov model to estimate progression to dementia in populations with and without the intervention, looking at lifetime risk, in the population of England. We estimated that reductions in excess alcohol use through minimum unit pricing would lead to cost-savings of £280million and 4767 quality-adjusted life-years (QALYs) gained over an indefinite succession of age cohorts. Reformulation of food products to reduce salt would lead to cost-savings of £2·4billion and 39 433QALYs gained and reformulation to reduce sugar would lead to cost-savings of £1·046billion and 17 985QALYs gained. Reducing dementia risk from air pollution by introducing low emission zones in English cities with a population of 100 000or more (that do not already impose restrictions) would lead to £260million cost-savings and 5119QALYs gained. Raising cigarette prices by 10% to reduce dementia risk from smoking would lead to 2277QALYs gained and cost-savings of £157million. Making bicycle helmets compulsory for children (aged 5-18years) to reduce dementia risk from head injury would lead to cost-savings of £91million and 1554QALYs gained. Population-level interventions could help tackle life course dementia risk and save costs. UK National Institute for Health and Care Research Three Schools dementia research programme.

Assessing economic investment required to scale up bariatric surgery capacity in England: a health economic modelling analysis

ObjectivesTo quantify the economic investment required to increase bariatric surgery (BaS) capacity in National Health Service (NHS) England considering the growing obesity prevalence and low provision of BaS in England...