OBJECTIVE: We propose a general framework for estimating long-term health and economic effects that takes into account four time-related aspects. We apply it to a reduction in exposure to air pollution in the Canton of Geneva.
METHODS: Methodological developments on the evaluation of long-term economic and health benefits, with an empirical illustration.
METHODS: We propose a unified framework-the comprehensive impact assessment (CIA)-to assess the long-term effects of morbidity and mortality in health and economic terms. This framework takes full account of four time-related issues: cessation lag, policy/technical implementation timeframe, discounting and time horizon. We compare its results with those obtained from standard quantitative health impact assessment (QHIA) in an empirical illustration involving air pollution reduction in the canton of Geneva.
RESULTS: We find that by neglecting time issues, the QHIA estimates greater health and economic benefits than the CIA. The overestimation is about 50% under reasonable assumptions and increases ceteris paribus with the magnitude of the cessation lag and the discount factor. It decreases both with the time horizon and with the implementation timeframe.
CONCLUSIONS: A proper evaluation of long-term health and economic effects is an important issue when they are to be used in cost-benefit analyses, particularly for mortality, which often represents the largest fraction. We recommend using the CIA to calculate more accurate values.

This paper aims to enhance the design and operation of a Combined Cooling, Heating, and Power (CCHP) system utilizing a gas engine as the primary energy source for a residential building in China. An Energy, Exergy, Economic, and Environment (4E) analysis is employed to assess the system\'s performance and impact based on energy, exergy, economic, and environmental criteria. The effectiveness of the DNGO algorithm is evaluated on a case study site and compared with Northern Goshawk Optimization (NGO) and Genetic Algorithm (GA). The findings demonstrate that the DNGO algorithm identifies the optimal gas engine size of 130 kW. The algorithm\'s search capabilities are greatly enhanced by this unique blend, surpassing what traditional methods can offer. The DNGO algorithm brings several advantages, including unparalleled energy efficiency, reduced exergy destruction, and a substantial decrease in C O 2 emissions. This not only supports environmental sustainability but also aligns with global standards. Economically, the algorithm enhances the performance of the CCHP system, evident through a reduced payback period and increased annual profit. Additionally, the algorithm\'s rapid convergence rate allows it to reach the optimal solution faster than its counterparts, making it advantageous for time-sensitive applications. Incorporating innovative methods like chaos theory, the DNGO algorithm effectively avoids local optima, enabling a broader search for the best solution. The utilization of Lévy flight further enhances the algorithm\'s ability to escape local optima and navigate the search space more efficiently. Additionally, swarm intelligence is employed to simulate the collective behavior of decentralized systems, aiding in problem-solving. This research represents a significant advancement in optimization techniques for CCHP systems and offers a fresh perspective to the field of swarm-based optimization algorithms.

Honey bees (Apis mellifera L.) are the premier agricultural pollinators with direct ecological value and are key to some agro-economies. Major factors have negatively impacted honey bee health in the past 2 decades with Varroa (Varroa destructor Anderson and Trueman) infestation rising as a principal predictor of colony mortality. A key strategy deployed in Varroa management is breeding for resistant honey bee populations that can maintain comparable levels of productivity as nonresistant populations. In this study, we examine one such population, Hilo honey bees, within the context of a common garden contrast with a commercial population in a stationary honey production operation. We compare colony survival, health, yield, and profit outcomes to show how this specific breeding population retains a profit value in honey production operations while maintaining higher survival and lower Varroa infestation levels than the commercial population. This information can be used by commercial beekeepers to make best management practice decisions and inspire further work examining what trade-offs, if any, are present in this Varroa-resistant population.

This paper explores the theoretical economic outcome of management changes that result in different levels of antimicrobial use (AMU) in two types of UK pig farm. A static farm economic pig production model (FEPM) was used on a representative \'Top-third\' most profitable farm and a representative \'Mid-range\' profitable farm. Three AMU theoretical management scenarios were investigated; (a) management changes leading to a reduction of AMU by 35% (AMU35); (b) more extensive management changes leading to a reduction of AMU by 95% (AMU95); and (c) implementing depopulation of the herd (AMU Depop). A sensitivity analysis was conducted to determine the effect of increases or decreases in pig revenue and feed price on farm gross margin under these scenarios. Over a single year, the AMU35 scenario was estimated to have a small positive impact (+3%) on both farm types. The other two AMU reduction scenarios had higher AMU reduction on farms but required higher variable cost and hence they resulted in lower farm profitability. There was a substantial reduction (up to -50%) in farm gross margin under these two AMU reduction scenarios in the modeled short-term time-period. The impact of the alternative AMU scenarios was slightly higher on a farm representing the \'Top-third\' farm type, reducing farm gross margin further by 7% compared to the \'Mid-range\' farm. Nevertheless, both farm types stay profitable under all three AMU scenarios. The results showed that in the modeled short-term implementing management changes that result in a reduction of on-farm AMU by 35% had a good economic outcome. In practice, the other two scenarios would be considered as longer-term strategies. Although both require higher initial costs to implement, the improved biosecurity and hygiene will benefit from lower disease occurrence for a longer term. Farm gross margins were, however, found to be highly sensitive to changes on market prices especially increasing feed prices. An increase of more than 15% in feed price moved a profitable farm into a loss-making farm. It will be economically challenging for uptakes of these, or similar, AMU reduction scenarios on farms if the market prices become un-favorable to pig farmers.

With the recent advancement in artificial intelligence, there are new opportunities to adopt smart technologies for the sorting of materials at the beginning of the recycling value chain. An automatic bin capable of sorting the waste among paper, plastic, glass & aluminium, and residual waste was installed in public areas of Milan Malpensa airport, a context where the separate collection is challenging. First, the airport waste composition was assessed, together with the efficiency of the manual sorting performed by passengers among the conventional bins: paper, plastic, glass & aluminium, and residual waste. Then, the environmental (via the life cycle assessment - LCA) and the economic performances of the current system were compared to those of a system in which the sorting is performed by the automatic bin. Three scenarios were evaluated: i) all waste from public areas, despite being separately collected, is sent to incineration with energy recovery, due to the inadequate separation quality (S0); ii) recyclable fractions are sent to recycling according to the actual level of impurities in the bags (S0R); iii) fractions are sorted by the automatic bin and sent to recycling (S1). According to the results, the current separate collection shows a 62 % classification accuracy. Focusing on LCA, S0 causes an additional burden of 12.4 mPt (milli points) per tonne of waste. By contrast, S0R shows a benefit (-26.4 mPt/t) and S1 allows for a further 33 % increase of benefits. Moreover, the cost analysis indicates potential savings of 24.3 €/t in S1, when compared to S0.

Chronic RhinoSinusitis with Nasal Polyps (CRSwNP) represents a condition mainly caused by the type 2 inflammation presence and marked by the existence of polyps within the nasal and paranasal sinuses. The standard of care includes intranasal steroids, additional burst of systemic steroids, if needed, and surgery. However, recurrence is common, especially among patients with comorbid type 2 inflammatory diseases. Recently, biological drugs, addressing the underlying cause of the disease, have been approved in Italy (dupilumab, omalizumab, and mepolizumab). A Health Technology Assessment was conducted to define multidimensional impact, assuming Italian NHS perspective and a 12-month time horizon. The EUnetHTA Core Model was deployed, using the following methods to analyze the domains: (i) literature evidence; (ii) administration of semi-structured questionnaires to 17 healthcare professionals; (iii) health economics tools to define the economic sustainability for the system. Evidence from NMA and ITC showed a more favorable safety profile and better efficacy for dupilumab compared with alternative biologics. All the analyses, synthesizing cost and efficacy measures, showed that dupilumab is the preferable alternative. Specifically, the cost per responder analysis for dupilumab, exhibiting a 67.0% response rate at Week 52, is notably economical at 14,209EUR per responder. This presents a more economical profile compared with the cost per responder for omalizumab (36.2% response rate) at 24,999EUR and mepolizumab (28.5% response rate) at 31,863EUR. These results underscore dupilumab\'s potential, not merely in terms of clinical outcomes, but also in terms of economic rationality, thereby solidifying its status as a valid and preferrable alternative in the management of CRSwNP, in the context of the Italian NHS.

BACKGROUND: Concerns that annual mass administration of ivermectin, the predominant strategy for onchocerciasis control and elimination, may not lead to elimination of parasite transmission (EoT) in all endemic areas have increased interest in alternative treatment strategies. One such strategy is moxidectin. We performed an updated economic assessment of moxidectin- relative to ivermectin-based strategies.
METHODS: We investigated annual and biannual community-directed treatment with ivermectin (aCDTI, bCDTI) and moxidectin (aCDTM, bCDTM) with minimal or enhanced coverage (65% or 80% of total population taking the drug, respectively) in intervention-naive areas with 30%, 50%, or 70% microfilarial baseline prevalence (representative of hypo-, meso-, and hyperendemic areas). We compared programmatic delivery costs for the number of treatments achieving 90% probability of EoT (EoT90), calculated with the individual-based stochastic transmission model EPIONCHO-IBM. We used the costs for 40 years of program delivery when EoT90 was not reached earlier. The delivery costs do not include drug costs.
RESULTS: aCDTM and bCDTM achieved EoT90 with lower programmatic delivery costs than aCDTI with 1 exception: aCDTM with minimal coverage did not achieve EoT90 in hyperendemic areas within 40 years. With minimal coverage, bCDTI delivery costs as much or more than aCDTM and bCDTM. With enhanced coverage, programmatic delivery costs for aCDTM and bCDTM were lower than for aCDTI and bCDTI.
CONCLUSIONS: Moxidectin-based strategies could accelerate progress toward EoT and reduce programmatic delivery costs compared with ivermectin-based strategies. The costs of moxidectin to national programs are needed to quantify whether delivery cost reductions will translate into overall program cost reduction.

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Biogas production via anaerobic digestion is highly attractive for microalgae. The technology of microalgae cultivation has profound impacts on biogas production system as it is the most energy-consuming process. However, a comprehensive evaluation of the environmental and economic benefits of different cultivation systems has yet to be sufficiently conducted. Here, life-cycle and economic assessments of open raceway ponds, photobioreactors and biofilm systems were investigated. Results showed greenhouse gas emissions of all systems were positive because more than two-thirds of carbon in fuel gas was lost and the fixed carbon in product gas and solid fertilizer was less than the emitted carbon during energy input. Particularly, biofilm system achieved the least greenhouse gas emissions (9.3 g CO2-eq/MJ), net energy ratio (0.7) and levelized cost of energy (0.9 $/kWh), indicating the optimum cultivation system. Open raceway ponds and photobioreactors failed to achieve positive benefits because of low harvesting efficiency and biomass concentration.

Chemical recycling of complex plastic waste via pyrolysis can reduce fossil resource dependence of the plastics value chain and greenhouse gas emissions. However, economic viability is crucial for its implementation, especially considering challenging waste streams with high shares of engineering plastics that have lower pyrolysis product quality than standard thermoplastics waste. Thus, this study conducts a techno-economic assessment determining the profitability factors of pyrolysis plants for automotive plastic waste in Germany including different plant capacities and calculating cost-covering minimum sales prices for the resulting pyrolysis oil. Main findings are that due to economies of scale, the cost-covering minimum sales prices vary between 1182 €/Mg pyrolysis oil (3750 Mg input/year) and 418 €/Mg pyrolysis oil (100,000 Mg input/year). The pyrolysis technology employed must be robust and scalable to realize these economies of scale. Large plant capacities face challenges such as feedstock availability at reasonable costs, constant feedstock quality, and pyrolysis oil quality, affecting pyrolysis oil pricing. Due to the limited yield and quality of pyrolysis oil produced from these technically demanding feedstocks, policy implications are that additional revenue streams such as gate fees or subsidies that are essential to ensure a positive business case are necessary. Depending on the assessed plant capacity, additional revenues between 720 and 59 €/Mg pyrolysis oil should be realized to be competitive with the price of the reference product heavy fuel oil. Otherwise, the environmental potential of this technology cannot be exploited.