Economic evaluation of GnRH-agonist long protocol and GnRH-antagonist protocol in IVT/ICSI among the Chinese population: using pharmacoeconomic models.

OBJECTIVE: This paper uses health economics methods to discuss the cost-effectiveness value of long protocol and antagonist protocol for in vitro fertilisation and embryo transfer (ET) in the Chinese population. DESIGN: Health economic evaluation study. SETTING: The data needed to construct the model for this study were derived from published studies and other secondary sources in China. PARTICIPANTS: No patients participated in the study. MEASURES: The main outcomes were live birth rate (LBR) and cost. From the societal perspective, we considered the direct and indirect costs over the course of the treatment cycles. A cost-effectiveness was measured using the incremental cost-effectiveness ratio and the probability that a protocol has higher net monetary benefit. Sensitivity analysis was carried out to verify the reliability of the simulation results. RESULTS: For the Chinese population, the long protocol resulted in a higher LBR than the antagonist protocol (29.33% vs 20.39%), but at the same time, it was more expensive (ï¿¥29 146.26 (US$4333.17) vs ï¿¥23 343.70 (US$3470.51)), in the case of considering only one fresh ET cycle. It was the same when considering subsequent frozen ET (FET) cycles (51.78% vs 42.81%; ï¿¥30 703.02 (US$4564.62) vs ï¿¥24 740.95 (US$3678.24)). The results of most subgroups were consistent with the results of the basic analysis. However, for certain populations, the long protocol was the inferior protocol (less effective and more expensive). CONCLUSION: For the Chinese population, when the monetary value per live birth was greater than ï¿¥65 420 (US$9726) and ï¿¥66 400 (US$9872), respectively, considering only one fresh cycle and considering subsequent frozen cycles, the long protocol is the preferred protocol. This threshold also varies for women of different ages and ovarian response capacities. For women in POSEIDON (Patient-Oriented Strategies Encompassing IndividualizeD Oocyte Number) group 2, group 3 and group 4, antagonist protocol is recommended as the preferred protocol. The results of this study need to be verified by further large-scale randomised controlled trials.

The impact of digital financial inclusion on bank performance: An exploration of mechanisms of action and heterogeneity.

The use of digital technology by banks and other financial institutions to facilitate financial inclusion is referred to as digital financial inclusion. This fusion of digital finance and traditional banking methods has the potential to impact banks' operational effectiveness. This study uses the panel effects model to examine the link between digital financial inclusion and bank performance in 30 Chinese provinces from 2012 to 2021. This research uses kernel density estimation to examine the spatial-temporal growth patterns of both variables. The mediator variable in examining how digital financial inclusion affects bank performance is risk-taking. Finally, the paper analyses the regional heterogeneity of the impact. It presents the following conclusions: (1) In China, digital financial inclusion and bank performance have constantly increased, with noticeable regional variances in their development levels. This regional inequality has widened gradually since 2018, yet it has not resulted in polarization. (2) The significant positive correlation between digital inclusive finance and banking performance indicates that banking performance tends to increase with the enhancement of digital inclusive finance. (3) Digital financial inclusion impacts bank performance, with risk-taking as a moderator. The spread of digital financial inclusion services enhances banks' willingness to take risks, enhancing overall efficiency. (4) Digital financial inclusion boosts bank performance in the Northwest, South, North, and East regions while lightly inhibiting it in the Central region. Based on the findings, this study makes bank and government suggestions.

Benefits of dapagliflozin in chronic kidney disease for US commercial payers: A cost-offset analysis.

BACKGROUND: One in 7 adults have chronic kidney disease (CKD), which is associated with high morbidity and mortality and substantial health care costs, especially in more advanced disease. Our data from a US commercial payer show rising per-member-per-year costs for renal and cardiac complications associated with CKD. OBJECTIVE: To predict the clinical and economic impact of treatment with or without dapagliflozin from the perspective of a US commercial payer using a cost-offset model (COM). METHODS: The COM used real-world cost and member count data from a US employer-sponsored commercial payer and results of the double-blind, randomized, phase 3 Dapagliflozin and Prevention of Adverse Outcomes in CKD clinical trial (NCT03036150) to predict the incidence of clinical events, including a greater than or equal to 50% decline in estimated glomerular filtration rate (eGFR), end-stage kidney disease, and hospitalization for heart failure, and their associated costs over a 3-year period. The COM compared a hypothetical scenario of the experience with or without dapagliflozin in members with CKD stages 2-4, aged younger than 65 years. RESULTS: In the simulated populations of 130 members, the COM projected 9 events of a greater than or equal to 50% decline in estimated glomerular filtration rate for the experience with dapagliflozin vs 15 events for the experience without dapagliflozin (6 fewer events; number needed to treat [NNT] = 20, amounting to estimated cumulative cost offsets of $0.57 million [M] over a 3-year period). The COM projected similar results for end-stage kidney disease (8 events with dapagliflozin vs 14 events without dapagliflozin; NNT = 24, amounting to $1.92 M in cumulative cost offsets) and for hospitalization for heart failure (13 events with dapagliflozin vs 33 events without dapagliflozin; NNT = 7, amounting to $0.79 M in cumulative cost offsets). These projections translated to total mean, cumulative cost offsets of $3.89 M for all clinical events evaluated over the 3-year period (36.6% reduction with dapagliflozin vs without dapagliflozin), and net mean, cumulative cost offsets of $2.58 M over the 3-year period (24.2% reduction with dapagliflozin vs without dapagliflozin) after factoring in a discounted wholesale acquisition cost for dapagliflozin expenditure ($1.31 M over 3 years). Thus, the net mean, cumulative cost offsets were $19,843 per member over 3 years, representing a 197% return on investment for dapagliflozin expenditure. CONCLUSIONS: Results of our COM suggest that dapagliflozin can reduce clinical events and their associated costs over a 3-year period when compared with a scenario without dapagliflozin. Cost offsets increased with each year, indicating that US commercial payers can substantially reduce costs associated with CKD morbidity and mortality.

Silence is golden, but my measures still see-why cheaper-but-noisier outcome measures in large simple trials can be more cost-effective than gold standards.

OBJECTIVE: To assess the cost-effectiveness of using cheaper-but-noisier outcome measures, such as a short questionnaire, for large simple clinical trials. BACKGROUND: To detect associations reliably, trials must avoid bias and random error. To reduce random error, we can increase the size of the trial and increase the accuracy of the outcome measurement process. However, with fixed resources, there is a trade-off between the number of participants a trial can enrol and the amount of information that can be collected on each participant during data collection. METHODS: To consider the effect on measurement error of using outcome scales with varying numbers of categories, we define and calculate the variance from categorisation that would be expected from using a category midpoint; define the analytic conditions under which such a measure is cost-effective; use meta-regression to estimate the impact of participant burden, defined as questionnaire length, on response rates; and develop an interactive web-app to allow researchers to explore the cost-effectiveness of using such a measure under plausible assumptions. RESULTS: An outcome scale with only a few categories greatly reduced the variance of non-measurement. For example, a scale with five categories reduced the variance of non-measurement by 96% for a uniform distribution. We show that a simple measure will be more cost-effective than a gold-standard measure if the relative increase in variance due to using it is less than the relative increase in cost from the gold standard, assuming it does not introduce bias in the measurement. We found an inverse power law relationship between participant burden and response rates such that a doubling the burden on participants reduces the response rate by around one third. Finally, we created an interactive web-app ( https://benjiwoolf.shinyapps.io/cheapbutnoisymeasures/ ) to allow exploration of when using a cheap-but-noisy measure will be more cost-effective using realistic parameters. CONCLUSION: Cheaper-but-noisier questionnaires containing just a few questions can be a cost-effective way of maximising power. However, their use requires a judgement on the trade-off between the potential increase in risk of information bias and the reduction in the potential of selection bias due to the expected higher response rates.

Rationalizing risk aversion in science: Why incentives to work hard clash with incentives to take risks.

Scientific research requires taking risks, as the most cautious approaches are unlikely to lead to the most rapid progress. Yet, much funded scientific research plays it safe and funding agencies bemoan the difficulty of attracting high-risk, high-return research projects. Why don't the incentives for scientific discovery adequately impel researchers toward such projects? Here, we adapt an economic contracting model to explore how the unobservability of risk and effort discourages risky research. The model considers a hidden-action problem, in which the scientific community must reward discoveries in a way that encourages effort and risk-taking while simultaneously protecting researchers' livelihoods against the vicissitudes of scientific chance. Its challenge when doing so is that incentives to motivate effort clash with incentives to motivate risk-taking, because a failed project may be evidence of a risky undertaking but could also be the result of simple sloth. As a result, the incentives needed to encourage effort actively discourage risk-taking. Scientists respond by working on safe projects that generate evidence of effort but that don't move science forward as rapidly as riskier projects would. A social planner who prizes scientific productivity above researchers' well-being could remedy the problem by rewarding major discoveries richly enough to induce high-risk research, but in doing so would expose scientists to a degree of livelihood risk that ultimately leaves them worse off. Because the scientific community is approximately self-governing and constructs its own reward schedule, the incentives that researchers are willing to impose on themselves are inadequate to motivate the scientific risks that would best expedite scientific progress.

Climate effects on the diversification strategy of export firms: Evidence from China.

Using a multi-product trade model, this study investigates the impact of temperature on firms' diversification in the export market. Using export and meteorological data of Chinese firms from 2000 to 2016, the empirical results confirm an inverted U-shaped relationship, implying that extreme temperatures significantly reduce firms' export product diversification. The analysis shows that extreme temperatures primarily reduce the variety of both new and existing products, with a less robust effect on product exit strategies. General trade firms are more adaptable to extreme temperatures than processing trade firms, and are likely to maintain diversified strategies. Stronger regional financial markets and higher energy consumption increase the adaptability of local firms to extreme temperatures. Firms have not yet adapted to local climatic norms. Furthermore, extreme temperatures also partly inhibit diversification of export destinations and relationships. The results of the study show that as climate change intensifies, leading to more frequent extreme temperatures, firms will face significant hurdles in pursuing diversified development strategies, pointing to increasing challenges ahead.

Budget impact analysis of introducing fruquintinib for metastatic colorectal cancer previously treated with fluoropyrimidine-, oxaliplatin-, and irinotecan-based chemotherapy and biologics in the United States from the payer perspective.

AIMS: Fruquintinib is a selective small molecule tyrosine kinase inhibitor of vascular endothelial growth factor receptor (VEGFR)-1, -2, and -3 recently approved in the United States (US) for the treatment of adult patients with metastatic colorectal cancer (CRC) who have previously been treated with fluoropyrimidine-, oxaliplatin-, and irinotecan-based chemotherapy, an anti-VEGF biological therapy, and if RAS wild-type and medically appropriate, anti-epidermal growth factor receptor therapy. This study aimed to estimate the 5-year budget impact of fruquintinib from a US payer perspective (commercial and Medicare). MATERIALS AND METHODS: A budget impact model was developed to compare two scenarios: a reference scenario in which patients received regorafenib, trifluridine/tipiracil, or trifluridine/tipiracil with bevacizumab and an alternative scenario in which patients received reference scenario treatments or fruquintinib. Market shares were evenly divided across available options. A 5-year time horizon and a hypothetical health plan of 1 million members was assumed. The model included epidemiological inputs to estimate the eligible population; clinical inputs for treatment duration, progression-free survival, overall survival, and adverse event (AE) frequency; and cost inputs for treatment, AEs, disease management, subsequent therapy, and terminal care costs. Budget impact was reported as total, per member per year (PMPY), and per member per month (PMPM). RESULTS: The model estimated an eligible population of 194 patients (39 per year) over 5 years. In the base case, the estimated 5-year budget impact of fruquintinib was $4,077,073 ($0.82 PMPY and 0.07 PMPM) for a commercial health plan. During the first year, the estimated budget impact was $627,570 ($0.63 PMPY and 0.05 PMPM). Results were robust across sensitivity analyses. PMPM costs from the Medicare perspective were greater than the base-case (commercial) ($0.17 vs. $0.07) due to higher incidence of CRC in that population. CONCLUSIONS: Fruquintinib is associated with a low budget impact for payers based on proposed thresholds in the US.

Fruquintinib is a treatment for metastatic colorectal cancer that has progressed after or not responded to multiple guideline-recommended therapies. This budget impact analysis was conducted to estimate the added costs a health plan would incur over a 5-year period if it chose to cover this therapy. The analysis found that the per plan member per month cost of covering fruquintinib was $0.07 for a United States commercial health plan and $0.17 for Medicare.

Health and Economic Outcomes of Pembrolizumab in the Treatment of Metastatic Non-small Cell Lung Cancer (mNSCLC) and Melanoma in Italy.

BACKGROUND AND OBJECTIVE: In Italy, the management of metastatic non-small cell lung cancer and melanoma leads to significant healthcare challenges, necessitating cost-effective treatment strategies and offering valuable insights for healthcare policymakers and stakeholders. This study was designed to assess the costs, quality-adjusted life-years (QALYs) and disability-adjusted life-years (DALYs) associated with the health and economic outcomes of (1) pembrolizumab-combined chemotherapy administered as a first-line treatment for metastatic non-squamous and squamous non-small cell lung cancer (NSCLC) where the tumour presents with a programmed death-ligand 1 expression level < 50% and of (2) adjuvant pembrolizumab treatment for stage III melanoma. METHODS: Three cost-effectiveness models developed by MSD were investigated for each treatment indication. A unique model was built to assess the overall effect of pembrolizumab versus chemotherapy or watchful waiting in patients with lung cancer or melanoma, respectively. Theoretical cohorts of patients with metastatic squamous and non-squamous NSCLC were followed over time using a partitioned survival model with weekly cycles. A weekly cycle Markov model was employed for melanoma. The analysis was conducted from the Italian National Health Service perspective, considering a time horizon of 40 years (lifetime). A single closed cohort of treatable patients was followed over time for each indication (4000, 7000 and 900 for NSCLC squamous, non-squamous and melanoma, respectively). The costs evaluated included those for adverse drug events, non-drug disease management, subsequent treatment and terminal care. Drug acquisition and administration costs were excluded. RESULTS: For each treatment indication assessed, pembrolizumab produced downstream direct cost offsets (- €122,498,568, - €133,369,076 and - €32,993,242 for NSCLC squamous, non-squamous and melanoma indications, respectively), increased quality of life (+2088, +5317 and +2307 QALYs for NSCLC squamous, non-squamous and melanoma indications, respectively) and reduced disability (- 2658, - 7202 and - 3029 DALYs for NSCLC squamous, non-squamous and melanoma indications, respectively). Across indications, the total cost offsets of pembrolizumab were - €288,860,885, with 9712 QALYs gained and 12,889 DALYs avoided. CONCLUSIONS: The analysis demonstrated that, compared with chemotherapy, pembrolizumab is more cost effective in Italy as a first-line treatment in patients with metastatic squamous or non-squamous NSCLC and, if compared with watchful waiting, as adjuvant treatment in patients with stage III melanoma. The present analysis suggested that pembrolizumab use could lead to important health benefits for patients while offsetting a portion of cancer care costs.

Unlocking SME growth: Analyzing the government subsidies' impact on financing in China.

Small and medium-sized enterprises (SMEs) were an important part of China's economy, but they faced challenges to growth due to financing difficulties. Government subsidies are considered as a potential way to address this problem. This study aims to assess the effectiveness of the Chinese government's subsidy program aimed at improving the accessibility of financing for SMEs. We analyze a comprehensive dataset of Chinese firms' subsidy programs from 2011 to 2020. We classify subsidies into unconditional and conditional categories and use fixed-effects regression models to control for the effects of time and between-group variation to more accurately assess the effectiveness of government subsidies. In addition, we use a PSM-DID model to reduce the effect of selectivity bias to more accurately estimate the causal effect of subsidies on financing strategies. We also use a mediated effects model to help understand the mechanisms by which different types of subsidies affect financing strategies. The results show that government subsidies can significantly improve SMEs' financing ability, but different types of subsidies produce subtle differences. Conditional subsidies support debt financing mainly through incentives, while unconditional subsidies help SMEs improve their equity financing ability through information effects. Furthermore, we find that over-reliance on a single subsidy type may reduce its effectiveness, suggesting a complex relationship between government intervention and SME financing. Thus, well-designed policies are crucial for promoting SMEs and fostering economic growth.

Study on the impact of digital economy on industrial collaborative agglomeration: Evidence from manufacturing and productive service industries.

In the digital era, digital economy has a far-reaching impact on the collaborative agglomeration of manufacturing and service industries. This research aims to examine the economic relationship between digital economy and industrial collaborative agglomeration. Based on a panel data set of 286 Chinese cities, this research employs Tobit model, moderating effect model, and mediating effect model to conduct data analysis. It is found that digital economy has a nonlinear relationship with industrial collaborative agglomeration, and this relationship is a U-shape. Moderating effect analysis reveals that government intervention significantly regulates the role of digital economy in industrial collaborative agglomeration. Mediating effect analysis indicates that digital economy promotes industrial collaborative agglomeration through entrepreneurial activity. Heterogeneity analysis shows that the facilitating effect of digital economy on collaborative agglomeration in high-end industries comes earlier than in middle- and low-end industries. Moreover, this research finds that digital economy plays a significant role in industrial collaborative agglomeration in central and western regions of China but not in the eastern region. To enhance the impact of digital economy on industrial collaborative agglomeration, it is crucial to strengthen the engagement of the government and ensure the availability of digital technology.

Period-aggregated transformer for learning latent seasonalities in long-horizon financial time series.

Fluctuations in the financial market are influenced by various driving forces and numerous factors. Traditional financial research aims to identify the factors influencing stock prices, and existing works construct a common neural network learning framework that learns temporal dependency using a fixed time window of historical information, such as RNN and LSTM models. However, these models only consider the short-term and point-to-point relationships within stock series. The financial market is a complex and dynamic system with many unobservable temporal patterns. Therefore, we propose an adaptive period-aggregation model called the Latent Period-Aggregated Stock Transformer (LPAST). The model integrates a variational autoencoder (VAE) with a period-to-period attention mechanism for multistep prediction in the financial time series. Additionally, we introduce a self-correlation learning method and routing mechanism to handle complex multi-period aggregations and information distribution. Main contributions include proposing a novel period-aggregation representation scheme, introducing a new attention mechanism, and validating the model's superiority in long-horizon prediction tasks. The LPAST model demonstrates its potential and effectiveness in financial market prediction, highlighting its relevance in financial research and predictive analytics.

Differential games in the supply chain of innovative products with consumer purchase regret induced returns.

Innovative products entering the market will cause dynamic changes in market demand, and consumers' purchase regret and their return behavior make the market environment more and more complex, which in turn affects the dynamic decision-making in the supply chain. In this paper, under the situation of discrete decision time, combining with the objective reality, we make discrete modification to the classical Bass diffusion model (Bass model), construct a manufacturer-led, retailer-followed supply chain differential game model, analyze the optimal decision-making of the manufacturer and the retailer by combining with the theory of discrete optimal control, and then verify the conclusions by numerical simulation. The results show that: when retailers purchase directly from the manufacturer and sell in the market, the optimal pricing of the innovative product can make the supply chain as a whole, realizing Pareto optimality; consumer's purchase regret will increase the amount of returns, which will lead to the decrease of product sales and the profits of the manufacturer and the retailer; when the innovative product accounts for a different share of the market, the impact of purchase regret on the wholesale price and the retail price are also different. Therefore, manufacturers need to have an extensive comprehension of the market to minimize the negative effects of consumer regret and returns, and to formulate a reasonable pricing strategy for their products to gain as much profit as possible.

The measurement of China's provincial physical capital stock based on the improved method and indicators.

Physical capital stock is the basic indicator of macroeconomic empirical studies and also an important manifestation of macroeconomic activity capacity. When measuring China's provincial physical capital stock by the perpetual inventory method, the treatment for the depreciation rate and the initial physical capital stock in the existing literature has some defects in reflecting the economic performance. The purpose of this paper is to build the most reliable and reasonable statistical series of China's provincial physical capital stock. We establish a measurement formula in form of the variable depreciation rate and improve the treatment for the depreciation rate and the initial physical capital stock. For the depreciation rate, we measure the benchmark depreciation rate of physical capital and determine the variable depreciation rate according to the economic growth rate, which makes the variable depreciation rate reflect the economic growth. For the initial physical capital stock, we measure the initial physical capital stock according to the capital output ratio, which makes the initial physical capital stock reflect the economic aggregate. Based on these improvements, we measure China's provincial physical capital stock from 1952 to 2022 by the perpetual inventory method. Through analyzing the measurement results, we have a more distinct insight into the temporal and spatial characteristics of China's provincial physical capital stock: The growth rate of physical capital stock at the provincial level has slowed in spite of remaining high; The eastern region is much higher than the central and western regions. According to these two characteristics, it is suggested that policymakers need to improve market mechanisms and adjust investment policies to promote a benign profile of economic growth and a regional optimization of capital formation.

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

OBJECTIVES: To 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 despite its high clinical effectiveness. DESIGN: Data were included for the patients with obesity who were eligible for BaS. We used a decision-tree approach including four distinct steps of the patient pathway to capture all associated resource use. We estimated total costs according to the current capacity (current scenario) and three BaS scaling up strategies over a time horizon of 20 years (projected scenario): maximising NHS capacity (strategy 1), maximising NHS and private sector capacity (strategy 2) and adding infrastructure to NHS capacity to cover the entire prevalent and incident obesity populations (strategy 3). SETTING: BaS centres based in NHS and private sector hospitals in England. MAIN OUTCOME MEASURES: Number of BaS procedures (including revision surgery), cost (GBP) and resource utilisation over 20 years. RESULTS: At current capacity, the number of BaS procedures and the total cost over 20 years were estimated to be 140 220 and £1.4 billion, respectively. For strategy 1, these values were projected to increase to 157 760 and £1.7 billion, respectively. For strategy 2, the values were projected to increase to 232 760 and £2.5 billion, respectively. Strategy 3 showed the highest increase to 564 784 and £6.4 billion, respectively, with an additional 4081 personnel and 49 facilities required over 20 years. CONCLUSIONS: The expansion of BaS capacity in England beyond a small proportion of the eligible population will likely be challenging given the significant upfront economic investment and additional requirement of personnel and infrastructure.

A danish healthcare-focused economic evaluation of first-line cryoballoon ablation versus antiarrhythmic drug therapy for the treatment of paroxysmal atrial fibrillation.

INTRODUCTION: Three randomised controlled trials (RCTs) have demonstrated that first-line cryoballoon pulmonary vein isolation decreases atrial tachycardia in patients with symptomatic paroxysmal atrial fibrillation (PAF) compared with antiarrhythmic drugs (AADs). The aim of this study was to develop a cost-effectiveness model (CEM) for first-line cryoablation compared with first-line AADs for the treatment of PAF. The model used a Danish healthcare perspective. METHODS: Individual patient-level data from the Cryo-FIRST, STOP AF and EARLY-AF RCTs were used to parameterise the CEM. The model structure consisted of a hybrid decision tree (one-year time horizon) and a Markov model (40-year time horizon, with a three-month cycle length). Health-related quality of life was expressed in quality-adjusted life years (QALYs). Costs and benefits were discounted at 3% per year. Model outcomes were produced using probabilistic sensitivity analysis. RESULTS: First-line cryoablation is dominant, meaning it results in lower costs (-€2,663) and more QALYs (0.18) when compared to first-line AADs. First-line cryoablation also has a 99.96% probability of being cost-effective, at a cost-effectiveness threshold of €23,200 per QALY gained. Regardless of initial treatment, patients were expected to receive ∼ 1.2 ablation procedures over a lifetime horizon. CONCLUSION: First-line cryoablation is both more effective and less costly (i.e. dominant), when compared with AADs for patients with symptomatic PAF in a Danish healthcare system.

Modeling the United Oscillation and Wave of economic policy and urban planning employing spatial population dynamics.

Modern urban dynamics are increasingly shaped by the interplay between economic policy and urban planning, yet often lack an integrated approach. This study bridges this gap by examining the dynamic equilibrium between these two realms using the "Oscillation and Wave Framework." Specifically, we focus on the impact of variations in congestion parameter λ on urban sectoral spatial distribution and population dynamics. Our approach utilizes an advanced agent-based model to simulate interactions within an urban economic landscape, offering a detailed analysis of the relationship between agglomeration economies and congestion diseconomies. The results highlight the significant influence of congestion parameter adjustments on urban patterns, particularly in terms of cluster density and development. Therefore, this study not only provides a deeper understanding of the intricate balance between economic and urban planning factors but also emphasizes the necessity of incorporating these insights into urban planning and policy formulation for sustainable urban development. The findings also have important practical implications for addressing the dynamic complexities of urban environments, especially the interactions between different industries and their role in shaping urban structures.

Estimated reduction in obesity prevalence and costs of a 20% and 30% ad valorem excise tax to sugar-sweetened beverages in Brazil: A modeling study.

BACKGROUND: The consumption of sugar-sweetened beverages (SSBs) is associated with obesity, metabolic diseases, and incremental healthcare costs. Given their health consequences, the World Health Organization (WHO) recommended that countries implement taxes on SSB. Over the last 10 years, obesity prevalence has almost doubled in Brazil, yet, in 2016, the Brazilian government cut the existing federal SSB taxes to their current 4%. Since 2022, a bill to impose a 20% tax on SSB has been under discussion in the Brazilian Senate. To simulate the potential impact of increasing taxes on SSB in Brazil, we aimed to estimate the price-elasticity of SSB and the potential impact of a new 20% or 30% excise SSB tax on consumption, obesity prevalence, and cost savings. METHODS AND FINDINGS: Using household purchases data from the Brazilian Household Budget Survey (POF) from 2017/2018, we estimated constant elasticity regressions. We used a log-log specification by income level for all beverage categories: (1) sugar-sweetened beverages; (2) alcoholic beverages; (3) unsweetened beverages; and (4) low-calorie or artificially sweetened beverages. We estimated the adult nationwide baseline intake for each beverage category using 24-h dietary recall data collected in 2017/2018. Taking group one as the taxed beverages, we applied the price and cross-price elasticities to the baseline intake data, we obtained changes in caloric intake. The caloric reduction was introduced into an individual dynamic model to estimate changes in weight and obesity prevalence. No benefits on cost savings were modeled during the first 3 years of intervention to account for the time lag in obesity cases to reduce costs. We multiplied the reduction in obesity cases during 7 years by the obesity costs per capita to predict the costs savings attributable to the sweetened beverage tax. SSB price elasticities were higher among the lowest tertile of income (-1.24) than in the highest income tertile (-1.13), and cross-price elasticities suggest SSB were weakly substituted by milk, water, and 100% fruit juices. We estimated a caloric change of -17.3 kcal/day/person under a 20% excise tax and -25.9 kcal/day/person under a 30% tax. Ten years after implementation, a 20% tax is expected to reduce obesity prevalence by 6.7%; 9.1% for a 30% tax. These reductions translate into a -2.8 million and -3.8 million obesity cases for a 20% and 30% tax, respectively, and a reduction of $US 13.3 billion and $US 17.9 billion in obesity costs over 10 years for a 20% and 30% tax, respectively. Study limitations include using a quantile distribution method to adjust self-reported baseline weight and height, which could be insufficient to correct for reporting bias; also, weight, height, and physical activity were assumed to be steady over time. CONCLUSIONS: Adding a 20% to 30% excise tax on top of Brazil's current federal tax could help to reduce the consumption of ultra-processed beverages, empty calories, and body weight while avoiding large health-related costs. Given the recent cuts to SSB taxes in Brazil, a program to revise and implement excise taxes could prove beneficial for the Brazilian population.

Estimation of lifetime costs for patients receiving a transplant: the case of liver transplantation related to hepatitis B in Italy.

Introduction: In Italy, post-liver transplant (LT) hepatitis B virus (HBV) reinfection prophylaxis is frequently based on a combined regimen of anti-HBV immunoglobulin (HBIG) and oral antivirals. However, little information is available at the national level on the cost of LT and the contribution of HBV prophylaxis. This study aimed to quantify the direct healthcare cost for adult patients undergoing LT for HBV-related disease over a lifetime horizon and from the perspective of a National Healthcare Service. Methods: A pharmaco-economic model was implemented with a 4-tiered approach consisting of 1) preliminary literature research to define the research question; 2) pragmatic literature review to retrieve existing information and inform the model; 3) micro-simulated patient cycles; and 4) validation from a panel of national experts. Results: The average lifetime healthcare cost of LT for HBV-related disease was €395,986. The greatest cost drivers were post-transplant end-stage renal failure (31.9% of the total), immunosuppression (20.6%), and acute transplant phase (15.8%). HBV reinfection prophylaxis with HBIG and antivirals accounted for 12.4% and 6.4% of the total cost, respectively; however, lifetime HBIG prophylaxis was only associated with a 6.6% increase (~€422 k). Various sensitivity analyses have shown that discount rates have the greatest impact on total costs. Conclusion: This analysis showed that the burden of LT due to HBV is not only clinical but also economic.

Economic utility of Colombian Romosinuano cattle.

The objective of this study was to quantify the economic utility in Romosinuano production systems by developing a bioeconomic model assumed cow-calf, cow-calf plus stocker (CCPS), and complete cycle operations. Each system produced males for sale and females for replacement. Input parameters were established from breed data collected by AGROSAVIA. Revenues were estimated using the official cattle price, and production costs were quantified per activity. In the results, for cow-calf operations, the maximum economic utility was 244.12 USD. CCPS, yielded 231.86 USD, and Complete cycle, 268.94 USD. The genetic progress per generation for W240, W480, W24 and CI was + 3.8 kg, + 5 kg, + 5.9 kg, and -1 d, respectively. The price of livestock was the sensitized variable with the greatest impact on maximum economic utility (± 118.64 USD to ± 155.44 USD), followed by mineral supplementation (16.31 USD to ± 37.34 USD). The sensitized variables with the lowest impact were food (± 1.62 USD to ± 1.8 USD) and health plan supplies (± 6.03 USD to ± 9.13 USD). It is concluded that economic utility defined as a composite trait influenced by the characteristics that shape it favors genetic progress and the identification of animals with optimal performance in different bovine production systems.

The implementation of Public-Private Partnership in China: A sustainable pathway?

The organizational forms of infrastructure in China are divided into two categories, the traditional Public Procurement Model (PUB) model and Public-Private Partnership(PPP) model. The main difference is the separation or binding of the construction and operation phases. A systematic understanding is needed of how Chinese local governments choose between these two models. In this paper, we take public capital congestion and local government objectives as the entry point to study the effects of both on PPP choice. Firstly, by constructing an endogenous economic growth model under the PPP model, and comparing it with the model under the PUB model, this paper initially explains how the rise in public capital congestion affects the choice of the PPP by growth-oriented local governments. Then the data from prefecture-level cities from 2009-2018 are utilized to conduct empirical tests. We find that urban economic growth pressures have a positive effect on the choice of PPP when the congestion of public capital increases. Furthermore, the implementation of PPP is indeed conducive to economic performance, and its core mechanism is to provide more infrastructure (like roads) rather than tax competition. The PPP model is more sustainable. We are the first to employ both modeling approach and the empirical research to address the implementation of Public-Private Partnership in China. And we have systematically analyzed the conditions and results of PPP selection by local governments. It formulates the Chinese PPP theory.