Budget Model Research Articles

Role of intensive mariculture on CO2 absorption and carbon burial, and the carbon sink potential of Sanggou Bay, China

Suspended-raft cultivation of bivalves and seaweed significantly influences carbon transport and transformation pathways in bay ecosystems, ultimately affecting air–sea CO2 flux (FCO2) and sedimentary carbon burial. Previous studies focused on whether bivalve and seaweed individuals are a carbon source or sink, but have not discussed the effects of their large-scale cultivation on carbon dynamics from the perspective of a bay ecosystem. In this study, we compared seasonal and spatial variations in air–sea FCO2 and sedimentary carbon burial flux in seaweed culture, bivalve culture, bivalve–seaweed polyculture, and non-culture areas in Sanggou Bay, China, a bay with a long history of mariculture practices. We found that in spring and summer, the air–sea FCO2 was lowest in the seaweed area; it was lowest in the bivalve area in autumn and winter. Despite this, the seaweed area annually absorbed twice the amount of atmospheric CO2 compared to the bivalve area. The bivalve area had the highest sedimentary carbon burial flux and the non-culture area had the lowest. More inorganic carbon than organic carbon was buried in sediment. Atmospheric CO2 absorption was positively correlated with sedimentary carbon burial. Seaweed culture was the main contributor, absorbing around half of the atmospheric CO2 of the bay, whereas bivalve culture exhibited the highest carbon burial, contributing about 40 % to the bay's sediment. We constructed an annual carbon budget model, and the estimated values for atmospheric absorption, seawater dissolution, and sedimentary burial were 2.09 × 104, 1.02 × 104, and 0.78 × 104 t C a−1, respectively. Taken together, our results indicate that the large-scale mariculture of bivalves and seaweed affect both atmospheric CO2 absorption and sedimentary carbon burial, as well as their relationship. Seawater dissolution is also a substantial carbon sequestration reservoir that cannot be overlooked when assessing the biogeochemical carbon cycle of bay ecosystems.

Comparing freshwater mussel responses to stress using life-history and dynamic energy budget theory

Freshwater mussels are experiencing severe population declines, affecting their critical role in freshwater ecosystems. A thorough assessment of threats posed by various stressors is needed; however, the large number of species to be considered and significant data gaps, especially for listed species, hinder the process. We combined a traits-based approach to represent multiple species grouped into three life-history categories – Equilibrium, Opportunistic, and Periodic – with the Dynamic Energy Budget modeling principles to capture the physiological mechanisms driving individual-level responses. We used the DEB model to simulate individual life cycles and explore relationships between underlying energetics and emerging individual traits of 47 freshwater mussel species and the common toxicity test surrogate, the Eastern oyster (Crassostrea virginica), under control and stressed conditions. Stress was introduced via physiological modes of action related to four key metabolic pathways: energy assimilation, maintenance, growth, and reproduction. We recorded maximum length, age at maturity, and fecundity and compared these endpoints and their stress-induced changes among life-history categories. The life-history differences among freshwater mussels directly emerged from underlying energetics, with high assimilation and maintenance supporting opportunistic traits. Stress imposed on energy assimilation had the strongest effect on all life-history traits, and a 25 % reduction in assimilation rate resulted in an average 25 % and 60 % decrease in maximum length and fecundity, respectively, and a 24 % increase in age at maturity. Equilibrium species suffered the greatest negative effects overall, indicating that this life-history strategy might be the most susceptible to stressors. The Eastern oyster displayed extreme opportunism in its life-history traits, but its responses to stress were generally within the range observed for freshwater mussels. The study provides a much-needed general understanding of stress responses across freshwater mussel life-history categories and contributes to the foundation for developing life-history-driven population models.

Spatial differentiation and functional zoning of carbon budget: evidence from Jiangxi Province

Regional carbon budget and compensation are one of the current research hotspots, which is of great practical significance for dealing with climate change and promoting the coordinated development of low carbon. Based on energy consumption and land use data, a carbon budget and carbon compensation measurement model was established to analyze the change characteristics and spatial differentiation of the carbon budget of 11 prefecture-level cities in Jiangxi Province from 2010 to 2020 and carry out functional zoning, and further calculate the carbon compensation value of each prefecture-level city. The results showed that (1) during the study period, the carbon emissions in Jiangxi Province showed an increasing trend, with an average annual growth rate of 6.00 million tons, showing a spatial distribution pattern of “high in the west and low in the east.” The province was mainly represented by net carbon sources. (2) During the study period, the forest land in Jiangxi Province was the main carbon sink. The carbon sink absorption capacity declined from 60.56 million tons in 2010 to 59.69 million tons in 2020. (3) The regional difference in the economic contribution coefficient of prefecture-level cities in Jiangxi Province is relatively tiny. The ecological support coefficient has apparent spatial heterogeneity, showing a spatial distribution feature of “high in the south and low in the north.” (4) The 11 prefecture-level cities in Jiangxi Province could be divided into four regions: the carbon sink functional area, low-carbon optimization area, total carbon control area, and carbon intensity control area. By calculating the carbon compensation value and according to the difference in the carbon compensation value, the 11 prefecture-level cities in Jiangxi province are divided into four high-compensation areas, three low-compensation areas, and four compensated areas. The larger the carbon budget is, the higher the carbon compensation amount; conversely, the smaller the budget, the more carbon compensation amount can be obtained. According to the above conclusions, 11 prefecture-level cities should improve emission reduction mechanisms and strengthen the management of forest land utilization. Meanwhile, Jiangxi Province should formulate differentiated development, and compensation strategies should be developed to promote low-carbon, coordinated, and sustainable development among regions.

Evaluation of a Wisconsin-type bioenergetics model to estimate brook charr (Salvelinus fontinalis) growth and food consumption under two salinity conditions.

In Québec, Canada, brook charr (Salvelinus fontinalis) is the most sought-after species for recreational fisheries, which makes it economically important. To improve population monitoring and better anticipate climate change impacts on brook charr, bioenergetics models can be useful. The objective of this research was to evaluate the performance of a resident brook charr Wisconsin Energy Budget (WEB) model applied to an anadromous strain under two salinity treatments. Growth and food consumption were predicted by the model and compared to the observed values obtained after a 60-day experiment in the laboratory on fish reared in fresh or brackish water. Predictions for fish reared in fresh water better estimated growth rate and consumption than for fish reared in brackish water, for which growth was overestimated and consumption was underestimated. Overall, these results suggest that there is a difference for the WEB model’s predictions depending on the salinity and that observed food consumption is predicted more accurately than growth.

A simulation study of deepwater ventilation in fjords through artificial downwelling

The pumping of less dense surface water into a deep layer, also termed artificial downwelling (AD), has demonstrated its effectiveness in ventilating basin water in a few fjords. Building on a previous experiment in By Fjord, we established a well-calibrated far-field hydrodynamic model to simulate bottom water circulation caused by AD implementation. Our simulations suggest that (1) laterally closed boundaries are crucial for AD to cause spatially uniform compensatory downwelling in the bottom water and that (2) dissolved oxygen delivered through downwelling can be sourced from both surface waters and below the pycnocline to enhance oxygen levels effectively. We propose a physical oxygen budget model to predict the temporal variability of deep-water oxygen levels, offering guidelines on the number of pipes and flow rates required for large-scale oxygenation. For small fjords (∼1 km2), a few pipes (each has a flow rate of 1 m3 s−1) may suffice, while medium-sized basins like Chesapeake Bay (∼1000 km2) may require several hundred pipes.

United States federal indebtedness and fiscal policy trade‐offs

AbstractProjected federal spending and taxes are distributed by birth year, gender, race, and lifetime education, using the Congressional Budget Office's 10‐year budget estimates and the Penn Wharton Budget Models' microsimulation. This enables measurement of conventional federal fiscal imbalance (FI): $162.6 trillion in present value, which is six‐fold larger than current debt held by the public. FI implies a shortfall of 26.1% in federal taxes, alternatively, an excess of 33.4% of federal expenditures. The equi‐proportional shortfall of expenditures plus taxes equals 14.6%. Excluding taxes and transfers of some groups, such as the elderly, increases the measured shortfall.

Resource budget model with Duffing oscillator for dynamics of synchronized biennial-bearing olives in the Levant

We develop and analyze a temporally continuous spatially lumped resource budget model to explain the dynamics of synchronized biennial-bearing olives in the Levant, specifically focusing on Syria, the region’s foremost olive-producing country. The model is a time-continuous counterpart of the celebrated resource budget model. It consists of a Duffing oscillator coupled with a dynamical model of pollination with an external force propelling olive growth by photosynthesis. The reference data are obtained from statistical databases of international organizations and our own observation systems in Jordan, a country neighboring Syria, providing a wealth of information to refine the model structure. An intensive review of Syria’s modern history involving significant shifts in agricultural policy and social stability leads to a conclusion that the model should comprehend the anomaly of olive yield interacting with socio-political factors as an autonomous behavior. The conventional mathematical methodology analyzes the model’s characteristics, such as solutions’ non-negativity, boundedness, and stability. The system is stable during pollination off-season but may become unstable and unbounded during pollination on-season, which is a property that the time-discrete resource budget model cannot reproduce. A significant finding is that coupling individual fruit trees by anemophily is not essential in synchronization, overturning earlier studies in the literature. The values of model parameters that best fit the historical data of olive yield in Syria result in bounded chaos. With alternative parameter values, the model could exhibit periodic oscillation, instability, or blowing up, as clearly shown in bifurcation diagrams.

H3NI: Non-target-specific node injection attacks on hypergraph neural networks via genetic algorithm

Node injection attack is widely used in graph neural networks (GNNs) attacks, which misleads GNNs by injecting nodes. Though hypergraph neural networks (HNNs) are an extension of GNNs, node injection attacks have not yet been studied in HNNs. Since each edge of a hypergraph can connect more than two nodes, existing node injection methods designed for GNNs cannot effectively select the hyperedges connected to the injected nodes when applied to hypergraphs. In this paper, we propose a Hypergraph Neural Network Node Injection attack method called H3NI, which utilizes a genetic algorithm and a predefined budget model to implement the first black-box node injection framework designed for HNNs attacks. We conducted experiments on the datasets of Cora co-authorship and co-citation. Experimental results show the effectiveness and superior performance of H3NI in attacking HNNs, which reduces the model accuracy by 18%–20% within 5% of the total injected nodes and achieves a 2-4X improvement compared to existing gradient-based node injection methods.

Phenomenological Study and The Effect of Human Resources Capability and The Implementation of Performance-Based Budgeting (PBB) Model on Institution Performance

The purpose of this study was to analyze the phenomenological study and the effect of human resources capability and the implementation of performance based budgeting (PBB) on institution performance. This study uses mix method. The results of deep interview can concluded that the implementation of PBB at University of Ibn Khaldun Bogor had been carried out but haven’t maximal yet in implementation. The relationship between the human resources capability and the implementation of PBB with institution performance will be tested using multiple linear regression analysis. The independent variables are the human resources capability and the implementation of PBB and the dependent variable is institution performance. The relationship between variabels can be written: Y = 0,467+ 0,183 X1 + 0,798X2. Based on a multiple regression test, only the implementation of performance based budgeting variables have a significant effect on institution performance. The F test showed that all variables can explain the dependent variables. The coefficient of determination of 75,4% means human resources capability and the implementation of performance based budgeting affect institution performance by 75,4%, and the remaining 24,6% is influenced by other factors that are not described in this study.

Impact of patient’s financial burden of COVID-19 treatment on antiviral prescription rates and clinical and economic outcomes

ABSTRACT Background In Japan, medical expenses for COVID-19 treatment transitioned from full public funding support to out-of-pocket (OOP) payment by patients plus partial public support in October 2023, and public support fully ended in March 2024. This study evaluated the clinical and economic impacts of initiating OOP payments. Research design and methods To assess the impact on prescription rates, we compared the prescription rates of antivirals from the 4-month pre- to post-OOP payment initiation period using a claims database. Subsequently, a budget impact model assessed the impacts of a hypothetical decline in the prescription rates on COVID-19-related hospitalizations, deaths, and direct medical costs for antiviral prescription and hospitalization. Results The antiviral prescription rate per 100 patients decreased from 17.5 for the pre-OOP payment initiation period to 11.5 for the post-OOP payment initiation period, that is, a change of − 34.3%. With prescription rate decreases of 40%, 60%, and 80%, the hospitalizations would increase annually by 22,533 (3.3%), 33800 (5.0%), and 45,066 (6.6%), respectively. The total costs would increase by JPY9.5 billion (USD67.3 million; 0.7%), JPY14.3 billion (USD100.9 million; 1.0%), and JPY19.0 billion (USD134.5 million; 1.3%), respectively. Conclusions Higher OOP payment decreased the antiviral prescription rate, potentially leading to clinical and economic loss.

Acclimation Unifies the Scaling of Carbon Assimilation Across Climate Gradients and Levels of Organisation.

The temperature dependence of carbon assimilation-from leaf photosynthesis to ecosystem productivity-is hypothesised to be driven by the kinetics of Rubisco-catalysed carboxylation and electron transport. However, photosynthetic physiology acclimates to changes in temperature, which may decouple temperature dependencies at higher levels of organisation from the acute temperature sensitivity of photosynthesis. Here, we integrate relative growth rate theory, metabolic theory and biochemical photosynthesis theory to develop a carbon budget model of plant growth that accounts for photosynthetic acclimation to temperature. We test its predictions using a novel experimental approach enabling concurrent measurement of the temperature sensitivity of acute photosynthesis, acclimated photosynthesis and growth rate. We demonstrate for the first time that photosynthetic acclimation mediates how carbon assimilation kinetics 'scale up' from leaf photosynthesis to whole-plant growth. We also find that existing models of photosynthetic acclimation are unable to predict features of growth rate responses to temperature in our system.

PROFITABILITY ANALYSIS OF RICE MILLING AND MARKETING IN BAUCHI STATE, NIGERIA

The study analysed the profitability of rice milling and marketing in Bauchi State, Nigeria. Multi-stage sampling procedure was used for the selection of respondents. The respondents comprised rice processors (millers) and marketers. Data were collected using questionnaire and analysed using descriptive statistics, farm budgeting techniques and multiple regression analysis. The findings revealed that majority (87.5%) of the millers and all (100%) of marketers were male and married with a mean age of 39 and 44 years respectively. However, 43.8% of the millers and 40% of the marketers had a family size of between 6-10 people per household with majority (62.5%) of the millers having tertiary education. The analysis also shows that half (50%) and more than half (53%) of the millers and marketers had a marketing and milling experience of between 11-20 years. The result of the budgeting model revealed that millers had a net income of N714 per bag with a return per naira of N1.46 and marketers had a net income of N1, 672 per bag with a return per naira of N 0.12. The results of the regression analysis revealed that years of milling experience and education level were the factors influencing rice milling while household size and membership of association were significant factors influencing rice marketers’ income. However, high cost of diesel (96.7%) and transportation cost (95%) were the major constraints faced by the millers and marketers in the study area. The study concluded that, milling and marketing of rice is a profitable ventures in the study area. It is therefore, recommended that government together with stakeholders should provide adequate infrastructure and introduce favorable policies to strengthen the rice value chain in the study area.

Reduced CO2 Release from Arctic Soils Due to CO2 Binding to Calcium Forming Aragonite.

Arctic soils are the largest pool of organic carbon compared with other soils globally and serve as a main source for greenhouse gases, especially in the course of the predicted future temperature increase. With increasing temperatures, substantial thawing of the permafrost layer of soils is expected, altering the availability of calcium in those soils, with an increase by ∼5 mg Ca g-1 DW predicted for Alaska. Here we show for two representative soils in Alaska (initially Ca-poor or Ca-rich) that this increase in Ca availability will lead to decreases in CO2 release by 50% and 57%. It is already well-known that the cation bridging of Ca ions to organic carbon renders this carbon unavailable for microbial respiration and that Ca is altering the transformation of Corg by microbes. Here we show that the decrease of the soil CO2 release may be also due to enhanced aragonite formation (by 300% for Ca-poor and 90-200% for Ca-rich soils), as revealed by synchrotron-based scanning transmission X-ray microscopy. We therefore call upon field experiments for validation of this process and inclusion of this process in global and local carbon budget models.

Development of national post-fire restoration system to assess net GHG impacts and salvage biomass availability

In light of the recent unprecedented wildfires in Canada and the potential for increasing burned areas in the future, there is a need to explore post-fire salvage harvest and restoration and the implications for greenhouse gas (GHG) emissions. Salvage logging and replanting initiatives offer a potential solution by regrowing forests more quickly while meeting societal demands for wood and bioenergy.This study presents a comprehensive modeling framework to estimate post-fire salvage biomass and net GHG emissions relative to a ‘do-nothing’ baseline for all of Canada's harvest-eligible forests. Forest ecosystem carbon emissions and removals were modeled at 1-ha spatial resolution for Canadian forests using the Generic Carbon Budget Model (GCBM) from 1990 to 2070 using several forest inventory data sources with future harvest and wildfires.Building upon previous research, our work integrated the Canadian Forest Fire Danger Rating System fire intensity to estimate fire severity of future wildfires. For 2024 to 2070, we assessed the changes in ecosystem carbon, emissions from harvested wood products, and substitution benefits from avoided emissions-intensive materials, relative to a forward-looking baseline. Our prototype system provides a comprehensive framework, configuration files, links to datasets to quantify the net GHG of post-fire restoration, and sample results for validation.•Developed spatially explicit forest carbon modeling system for all of Canada's forests.•Assessed the net GHG reduction from post-fire restoration.•Used system approach to consider forests, wood products and substitution benefits.

High-accuracy and low-disturbance approach for identifying surface water and groundwater interactions in wetlands

Comprehending the hydrological conditions in wetlands is a critical aspect of successfully enhancing wetland conservation. The interaction between wetland surface water and groundwater is a complex process, requiring detailed onsite hydrological and soil surveys, laboratory experiments, and modeling to clarify this relationship. However, conventional investigation methods often cause significant disruptions and thus may affect the natural environment and compromise data reliability. In this study, a high-accuracy and low-environmental-disturbance (LED) approach was proposed involving modified falling head permeability and modified seepage meter tests to elucidate the groundwater characteristics in an ecological reserve. A water balance (WB) calculation method was employed to examine the performance of the proposed LED approach. The results revealed that the LED performed better than conventional methods in hydraulic conductivity and seepage velocity exploration, thereby improving the accuracy of quantifying groundwater flow. Moreover, the experimental findings and ecohydrological observations were used to assess the groundwater flow regime, and the data were consistent with the field survey results. The contradiction between conducting research and protecting ecological reserves can pose difficulties in the sustainable and effective management of wetlands. The LED approach can be applied broadly, especially in areas where significant disturbance should be avoided. The water budget model can thus be developed to help deduce the interaction between groundwater and surface water. We suggest that these innovative methods are effective tools and can assist both scientists and authorities in formulating corresponding habitat management strategies.

Organizational and budget impact model (OBIM) of SAME a new autotransfusion medical device

Objectives This study aimed to assess the budget and organizational impact of progressively replacing the intraoperative cell salvage centrifugation-based systems currently installed in French hospitals with the SAME system, a new autotransfusion medical device. Methods An Organizational and Budget Impact Model (OBIM) was developed based on two methodological guidelines issued by the French Health Authority (Haute Autorité de Santé, HAS). The OBIM was also developed based on a pragmatic literature review, hospital data and hospital pharmacists’ expertise. Results Considering an average hospital cohort of 600 cardio-thoracic surgery patients, with 57% experiencing mild hemorrhages, 23% moderate hemorrhages, and 20% massive hemorrhages, and a SAME market share of 33% in Year 1, the implementation of SAME resulted in significant savings. With an average allogeneic transfusion of 4.19 packed red blood cells (RBC) and 0.62 platelet concentrate per patient based on National Hemovigilance Report of the ANSM (French National Agency for the Safety of Medicines and Health Products) and when using SAME system a reduction of 45% of RBC transfusion associated with a reduction of 60% and 90% of platelet use for moderate and massive hemorrhages respectively, the first year annual saving amounted to €44,601 and the cumulated saving over 5 years to €535,206. Discussion This model structure was developed based on overall hospitals’ needs and acknowledged guidelines, with inputs based on French literatures and hospital data, so findings were specifics to a context. Among the inputs, the number of annual SAME procedure is not based on device capability but rather on hospital capability with the number of operating rooms used for cardio-thoracic surgery equipped with the device. Conclusions The results of this OBIM demonstrated the economic and organizational benefits of SAME for hospitals. This benefit results mainly of a reduction in the use of allogeneic blood products (RBCs, platelets).

Hindcasted Body Temperatures Reveal Underestimated Thermal Stress Faced by Intertidal Species

ABSTRACTAimAs global climate changes, there is a clear mismatch between the temporal and spatial characteristics of body temperature and environmental temperature, confounding the assessment of thermal stress for organisms in many ecological studies. Here, we hindcast the hourly body temperatures of intertidal molluscs to explore the differences between them and environmental temperatures (air and water temperatures) in multiple metrics of thermal stress.LocationIntertidal shores in East Asia (0°–45°N, 100°E–140°E).Time Period40 years, 1980 to 2019.Major Taxa StudiedMollusca.MethodsWe collected habitat zonation data and measured the morphological characteristics of 25 intertidal molluscs living in East Asia. For three different types of intertidal molluscs (i.e., bivalves, limpets and snails), we built corresponding heat budget models (HBMs) to hindcast the hourly body temperatures from 1980 to 2019. We analysed the thermal stress of intertidal species faced in three metrics, annual extreme high temperatures (T99), seasonal daily maximum temperatures (DMT) and heatwaves, and compared them with environmental temperatures.ResultsWe found that T99 of body temperatures and their interannual warming rates are significantly higher than those of environmental temperatures. Moreover, there were non‐negligible mismatches between the seasonal thermal pattern and heatwaves of body temperatures and environmental temperatures, suggesting that the deleterious impacts of global warming on intertidal species are underestimated and cannot be directly revealed by environmental temperatures.Main ConclusionsThermal stress patterns of body temperature were significantly different from those of environmental temperature, and the thermal stress faced by intertidal species had been persistently underestimated. These results emphasise that body temperature should be used as the appropriate metric for evaluating and predicting the impacts of global warming and weather extremes in the intertidal biological system.

Environmental Risk Assessment of Time-Variable Toxicant Exposure with Toxicokinetic-Toxicodynamic Modeling of Sublethal Endpoints and Moving Time Windows: A Case Study with Ceriodaphnia dubia.

Toxicokinetic-toxicodynamic (TKTD) modeling has received increasing attention in terms of the regulatory environmental risk assessment of chemicals. This type of mechanistic model can integrate all available data from individual-level bioassays into a single framework and enable refined risk assessments by extrapolating from laboratory results to time-variable exposure scenarios, based, for instance, on surface water exposure modeling (e.g., FOCUS). Dynamic energy budget (DEB) models coupled with TKTD modules (DEB-TKTD) constitute the leading approach to assess and predict sublethal effects of chemicals on individual organisms. However, thorough case studies are rare. We provide a state-of-the-art example with the standard aquatic test species Ceriodaphnia dubia and the fungicide azoxystrobin, including all steps, from bespoke laboratory toxicity tests to model calibration and validation, through to environmental risk assessment. Following the framework proposed in the European Food Safety Authority Scientific Opinion from 2018, we designed bespoke good laboratory practice-compliant laboratory toxicity studies based on test guideline 211 of the Organisation for Economic Co-operation and Development and then identified robust parameter values from those data for all relevant model parameters through model calibration. The DEB-TKTD model, DEBtox2019, then informed the design of the validation experiment. Once validated, the model was used to perform predictions for a time-variable exposure scenario generated by FOCUS. A moving time-window approach was used to perform the environmental risk assessment. This assessment method reduces uncertainty in the risk assessment while maintaining consistency with the traditional measures of risk. Environ Toxicol Chem 2024;43:2409-2421. © 2024 Syngenta Crop Protection AG. ibacon GmbH and The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Budget impact models for lung cancer interventions: A systematic literature review.

Budget impact models (BIMs) forecast the financial implications of adopting new technologies and the potential need for budget reallocation, thus playing a crucial role in reimbursement decisions. Despite the importance of accurate forecasts, studies indicate large discrepancies between estimates and reality. We are developing an artificial intelligence-based clinical decision tool to identify patients with non-small cell lung cancer who are most likely to benefit from immunotherapy. To evaluate the budgetary implications and describe a systematic literature review of published lung cancer BIMs. We searched PubMed and EMBASE for studies published between 2010 and 2023 that include BIMs that describe lung cancer interventions. Forward and backward reference searches were performed for all qualifying studies. We extracted author and publication year, country, interventions, disease stages, time horizon, analytical perspective, modeling methods used, types of costs included, sensitivity analyses conducted, and data sources used. We then evaluated adherence to the Professional Society for Health Economics and Pharmacoeconomics Research best-practice guidelines. A total of 25 BIMs were identified, spanning 14 different countries. Model structure could not be ascertained definitively for nearly half of the models. The cost calculator approach was most common among the others. Time horizons ranged from 1 to 5 years, in line with recommendations. Most models compared drugs, 4 compared nondrug interventions, and 7 compared diagnostic technologies. Assumptions about market uptake were poorly documented and poorly motivated. Inclusion of cancer-related costs was rare. Adherence to best practices was variable and did not appear to improve over time. The number of published BIMs for lung cancer exceeded expectations. There were modest trends toward publication frequency and model quality over time. Our analysis revealed variability across the models, as well as their adherence to best practices, indicating substantial room for improvement. Although none of the models were individually suitable for the purpose of evaluating an artificial intelligence-based treatment selection tool, some models provided valuable insights.

Developing a dynamic energy budget model to project potential effects of deep-sea mining plumes on the Atlantic deep-sea mussel, Bathymodiolus azoricus

Due to the consistent lack of Environmental Risk Assessment (ERA) for deep-sea mining scenarios, the potential impacts of this industry on marine ecosystems remain largely unknown. In order to fill this gap, a Dynamic Energy Budget (DEB) model was developed to study the consequences of toxic sediment plumes derived from deep-sea mining on the energy budget of the Atlantic deep-sea mussel, Bathymodiolus azoricus. Model calibration was based on environmental conditions observed at the Menez Gwen (MG) vent field (Mid-Atlantic Ridge- MAR), assuming a B. azoricus lifespan of 10 years and a maximum shell length of 119 mm. Scenario simulations were conducted to mimic the effects of increased concentrations of toxic sediment plumes on mussel filtration rates, the absorption of reduced substrates by their endosymbionts, and the energetic costs associated with metal toxicity. Data were sourced from B. azoricus and, when necessary, from proxy species. One disturbance scenario (EF1) incorporated measured rates and realistic parameters, while the other (EF2) was intentionally designed to encompass cumulative effects and uncertainties, representing a potential worst-case scenario. Both disturbance scenarios were initiated at three different timings (0, 1200 and 2400 days) to accommodate the mining effects at different stages of the mussels' life cycle. Results indicate that B. azoricus is significantly impacted by toxic sediment plumes, particularly during earlier life stages, potentially leading to severe growth impairment and mortality. These results were integrated into a food web model of the MG vent field, revealing that disruptions to the energetic balance of the vent mussel have widespread consequences for the entire ecosystem. Overall, we argue that this numerical framework offers a valuable tool for conducting ERA and Environmental Impact Assessments (EIA) in the context of industrial deep-sea mining.