Multi-criteria Decision Analysis Approach Research Articles

A multi-objective constraint programming approach to address clustering problems in mine planning

PurposeThe mine sequencing problem is NP-hard. Therefore, simplifying it is necessary. One way to do this is to employ clusters as input instead of individual blocks. The mining cut clustering problem has been little addressed in the literature, and the solutions used are almost always heuristic. We solve the mining cut clustering problem, which is NP-hard, through single- and multi-objective optimization, finding results that are local optima in acceptable computational time.Design/methodology/approachWe first elaborate an ILP-based model to address the mining cut clustering problem. We employ a mono-objective approach and two multi-objective approaches, solving all these models by constraint programming. To choose the best solutions generated by multi-objective approaches, we employ two multi-criteria decision analysis approaches, considering different weight configurations. We developed a case study using real data.FindingsWe verified that the approaches based on multi-objective optimization performed better than the mono-objective approach for the economic return criterion. The weighted-sum multi-objective approach presented the best results considering all objective functions used. Once viable solutions were obtained through multi-objective optimization, multi-criteria decision analysis approaches almost always selected the same solution. We obtained solutions that are local optima in acceptable computational time.Research limitations/implicationsThis study solves an instance with 80 blocks. Consequently, it is aimed at short-term mine planning. The methodology has not yet been evaluated in large instances related to medium- and long-term mine planning.Originality/valueThis is the first time that multi-objective optimization has been employed to solve the mining cut custering problem. Even other problems related to mine planning were, at most, solved by goal programming, so that multi-objective optimization is a knowledge that is not widespread among mining researchers. The results are consistent, and the study achieves the objective of finding quality solutions to an NP-hard problem in an acceptable computational time.

Mapping the Potential of Managed Aquifer Recharge in Africa: GIS-based Multi-Criteria Decision Analysis Approach

Africa faces numerous challenges related to rainfall variability, droughts, water scarcity, and climate change. Managed Aquifer Recharge (MAR)- groundwater recharge and underground water storage for later use or environmental support presents a viable alternative for water storage and may provide an effective tool for coping with such challenges. However, the potential area where MAR can be feasibly implemented has not been identified. This study mapped MAR feasibility using a Geographic Information System-based Multi-Criteria Decision Analysis (GIS-MCDA) and assessed MAR potential in Africa. The methodology focused on three key pillars of MAR feasibility: intrinsic suitability based on biophysical parameters, water source availability, and water demand. Maps responding to these pillars were developed and combined to create a composite MAR feasibility map. Results show that 18% of the continental area falls into the low feasibility class, 73% into the moderate feasibility class, and 7% into the high feasibility class. The feasibility map was validated against 17 existing MAR schemes in Africa, demonstrating a good correlation between their locations and areas with MAR potential. Results of sensitivity analysis of criteria weights of the biophysical parameters show that geology is the most influential criterion, followed by slope. In general, this first feasibility assessment shows good potential for MAR implementation in Africa. Therefore, MAR should be considered prominently among other water storage options for resilience building in Africa and policymakers should ensure adequate resource allocation for its implementation. The feasibility map can be used to guide MAR planning and investment decisions.

Future Site Suitability for Urban Waste Management in English Bazar and Old Malda Municipalities, West Bengal: A Geospatial and Machine Learning Approach

The rapid urbanization occurring globally has significantly intensified the challenges of waste management in densely populated metropolitan areas. A growing amount of waste has become a major concern for municipal authorities and local governments due to the limited availability of suitable land. Geospatial techniques, such as Geographic Information Systems (GISs) and remote sensing, combined with machine learning, play a crucial role in identifying suitable sites for urban waste management. These techniques assist planners in making well-informed decisions that strike a balance between environmental preservation and urban expansion by examining spatial data on land use, population density, and environmental concerns. Geospatial tools provide a data-driven basis for policy and urban planning, ensuring effective land use, reducing ecological hazards, and promoting sustainable urban growth for municipalities such as English Bazar and Old Malda. It can also pose serious threats to the environment, public health, and communities. Focusing on the English Bazar and Old Malda Municipalities in India, this paper examines the use of geospatial technologies to identify suitable sites for waste disposal. The research aims to address the complex processes of waste generation, collection, and disposal in urban environments. Using GIS and a Multi-Criteria Decision Analysis (MCDA) approach, the study employs the Analytic Hierarchy Process (AHP) alongside the Random Forest (RF) model and a machine learning (ML) technique to identify potential waste disposal sites within the English Bazar and Old Malda Municipalities in the Malda district. Eight key criteria were considered in the site selection process: land elevation; distances from surface water, roads, railways, and urban areas; groundwater depth; land use and land cover; and distance from sensitive and restricted areas. AHP analysis showed that 8%, 26%, and 27% of the sites were categorized as very highly suitable, moderately suitable, and unsuitable, respectively. Meanwhile, 38%, 17%, and 13% of the areas were classified as unsuitable, moderately suitable, and very highly suitable according to the RF model. The overall accuracy and Kappa coefficient indicated that the AHP method (overall capacity of 83.83% and Kappa coefficient of 0.7894) was slightly better than the RF model (overall capacity of 80.61% and Kappa coefficient of 0.7474) for site suitability analysis. This research underscores the broad relevance of geospatial technology in creating resilient and environmentally sustainable cities while offering valuable guidance on effectively allocating waste disposal sites. The findings provide crucial insights for urban planners and decision-makers, facilitating the identification of optimal locations for sustainable waste management in urban settings.

Application of Multicriteria Decision Analysis Approach Managing Solar Prosumer Choices: Implications for Households, Regulatory Authorities, and Contractors

Application of Multicriteria Decision Analysis Approach Managing Solar Prosumer Choices: Implications for Households, Regulatory Authorities, and Contractors

Potential Utilization of Rice Waste in the Construction Sector: A Multi-Criteria Decision Analysis Approach

Effective management of agricultural waste is an important contribution to environmental sustainability and economic development, especially considering the significant volume of agricultural residues produced worldwide. Rice is a widely cultivated crop in Colombia, and its high production results in a high amount of wastes, which is often underutilized due to a lack of knowledge regarding its potential value-added applications. On the other hand, the construction industry has become increasingly aware of the necessity to develop materials with reduced environmental impact. Therefore, this study explores the application of the Analytic Hierarchy Process (AHP) to evaluate various alternatives for utilizing rice waste in construction materials; the alternatives were evaluated based on criteria tailored to the needs of local agricultural communities in the Tolima region of Colombia. The findings highlight the potential of rice husk ash (RHA) as an environmentally responsible alternative in the construction sector, offering a viable solution for waste management while contributing to the economic development of small-scale farmers.

Digitalization and tender evaluation in construction projects: a BIM-integrated MCDA approach supported by Macbeth

The tender evaluation process in the procurement for construction works, aligned with regulations such as the European Directive 2014/24/EU, faces various constraints, increasingly acknowledging the impact of digitalization, particularly through Building Information Modeling (BIM). Therefore, a thorough BIM-integrated multi-criteria decision analysis approach is vital to fairly select the best contractor for the job and ensure project success. Despite its significance, the literature remains scarce, particularly in addressing BIM-related and value-focused constraints for construction tender evaluation. This research introduces a comprehensive and value-focused method integrating BIM criteria through Multicriteria Decision Analysis (MCDA) supported by the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH), which is applicable to both the public and private sectors, serving as a reference guide for contracting authorities to assess and select the best tender for BIM-based construction works contracts. For this purpose, the following methodology was adopted: 1) conducting an extensive literature review; 2) carrying out interviews with construction experts to identify BIM-integrated evaluation criteria and performance descriptors; 3) creating an adapted MCDA construction tender evaluation framework supported by MACBETH; 4) performing a real-world case study to demonstrate the proposed evaluation framework; 5) discussing its application and limitations, along with considerations for future research. The study demonstrated the practicality of the proposed framework through a case study, showing that a value-based approach can significantly improve project outcomes compared to traditional methods. While acknowledging the potential of the BIM methodology, the impact of BIM-specific criteria on contractor selection was found to be less significant than expected. In conclusion, this work addresses current limitations, such as the absence of BIM-integrated assessment guidelines in the European Directive 2014/24/EU and ISO 19650. It outlines a value-focused MCDA approach for evaluating tenders for construction works contracts, supported by MACBETH for structuring the decision problem and building the evaluation model. The contribution to the body of knowledge lies in providing a robust framework that enhances the evaluation process in BIM-based construction works contracts and offers practical insights for contracting authorities.

URBAN FLOOD RESILIENCE: A MULTI-CRITERIA EVALUATION USING AHP AND TOPSIS

Floods are increasingly recognized as one of the most destructive natural disasters, driven by urban expansion, climate change, and unregulated development. This is particularly true in developing countries, where rapid urbanization has increased impervious surfaces, amplifying flood risks in urban areas. This study focuses on Albania, evaluating urban resilience against floods through the lens of water-related disaster data. Using a multi-criteria decision analysis (MCDA) approach, specifically the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the research assesses flood vulnerability and resilience in rapidly urbanizing regions. Integrating AHP and TOPSIS with mixed methods introduces a novel approach, offering a comprehensive evaluation framework for flood risk management. The findings highlight critical vulnerabilities and suggest that targeted urban planning and disaster mitigation efforts can enhance resilience. Future research could incorporate climate projections and granular urban data, supporting a more adaptive flood management strategy.

Into the Jungle of Biological Agents of Foodborne Diseases: Time to Put Some Order for the French Risk Manager.

Consumers can be exposed to many foodborne biological hazards that cause diseases with varying outcomes and incidence and, therefore, represent different levels of public health burden. To help the French risk managers to rank these hazards and to prioritize food safety actions, we have developed a three-step approach. The first step was to develop a list of foodborne hazards of health concern in mainland France. From an initial list of 335 human pathogenic biological agents, the final list of "retained hazards" consists of 24 hazards, including 12 bacteria (including bacterial toxins and metabolites), 3 viruses and 9 parasites. The second step was to collect data to estimate the disease burden (incidence, Disability Adjusted Life Years) associated with these hazards through food during two time periods: 2008-2013 and 2014-2019. The ranks of the different hazards changed slightly according to the considered period. The third step was the ranking of hazards according to a multicriteria decision support model using the ELECTRE III method. Three ranking criteria were used, where two reflect the severity of the effects (Years of life lost and Years lost due to disability) and one reflects the likelihood (incidence) of the disease. The multicriteria decision analysis approach takes into account the preferences of the risk managers through different sets of weights and the uncertainties associated with the data. The method and the data collected allowed to estimate the health burden of foodborne biological hazards in mainland France and to define a prioritization list for the health authorities.

Identifying hidden groundwater reserves: GIS advances and multi-criteria decision analysis for enhanced potential assessment

The aquifer system may become susceptible as a result of excessive groundwater extraction without regard for scientific principles. This study evaluates the Groundwater Potential (G.P.) using multicriteria decision analysis (MCDA) and geospatial modelling. Here in MCDA, the G.P. is measured using Remote Sensing (R.S.) and Geographic Information System (GIS), together with Analytical Hierarchical Process (AHP), Fuzzy Analytical Hierarchical Process (FAHP), and Best Worst Method (BWM). Analysis and model creation took into account 15 groundwater affecting elements that affect the G.P. Groundwater Potential Zones (GPZs) in Cachar District, India varied by the following percentages: 46.97%, 37.41%, and 15.62% for AHP; 46.13%, 40.92%, and 12.95% for FHP; and 50.65%, 36.51%, and 12.84% for BWM, respectively, for low, medium, and high zones. The FAHP and BWM models outperformed the AHP model, according to the results of the qualitative validation. The concerned authorities might identify vulnerable locations and plan sustainable groundwater management with the use of these MCDA approaches combined with GIS.

Review on Potential Urban Development Site Selection Using Geospatial-Based Multi-Criteria Decision Analysis (MCDA) Techniques in the Context of Ethiopia

This review paper provides a comprehensive assessment of the opportunities and challenges in leveraging geospatial-based technologies, particularly Multi-Criteria Decision Analysis (MCDA) techniques, to enhance the effectiveness of urban development site selection in Ethiopia. The overarching findings highlight several critical focus areas for improvement. Firstly, the review emphasizes the need to strengthen the availability, quality, and accessibility of geospatial data through the development of robust data infrastructures and innovative data collection methods. Secondly, it recommends adopting a more inclusive and collaborative approach to stakeholder engagement, coupled with targeted capacity-building initiatives to enhance the technical skills and knowledge of urban planners, GIS experts, and local stakeholders. Thirdly, the paper suggests incorporating advanced spatial modeling and simulation techniques to capture the dynamic nature of urban growth patterns, as well as integrating climate change impact assessments and disaster risk analyses into the decision-making framework. Fourthly, it emphasizes the importance of strengthening institutional and organizational frameworks to promote cross-sectoral collaboration, data sharing, and integrated decision-making processes. Finally, the review underscores the significance of designing user-friendly and customizable Spatial Decision Support Systems (SDSS) that cater to the specific needs and constraints of the Ethiopian urban development context. The review concludes that the use of geospatial-based MCDA approaches holds immense potential in addressing Ethiopia's complex urban development challenges, as it enables a comprehensive evaluation of suitability factors and the exploration of alternative urban development strategies.

Seas the opportunity: multi-criteria decision analysis to identify and prioritise blue carbon wetland restoration sites

IntroductionThe emergence of voluntary carbon markets is creating new opportunities to sustainably finance Natural Climate Solution (NCS) projects. In Australia, the federal government recently enacted the Tidal Restoration of Blue Carbon Ecosystems Methodology Determination 2022 (Tidal Reconnection Method), whereby restoration activities that reintroduce tidal flows to allow the re-establishment of coastal wetland (blue carbon) ecosystems, through the removal or modification of a tidal restriction, can be used to gain and sell Australian carbon credit units. Australia has the highest net blue carbon wealth in the world, with 5%–11% of global carbon stocks, yet there is currently a lack of large-scale feasibility assessments and supporting methodologies to identify and prioritise sites with the greatest potential for NCS project implementation to help inform investment decisions.MethodsIn this study, we applied a spatial Multi-Criteria Decision Analysis (MCDA) to identify, map, and prioritise potential sites for blue carbon coastal wetland restoration in South Australia that meet criteria outlined in the Tidal Reconnection Method. This study compared information on 1) predicted flooding extent following tidal reconnection and under sea level rise (SLR; present-day, 2050 and 2,100); 2) project implementation complexity (e.g. who possesses land tenure); and 3) carbon sequestration potential through predicted area of vegetation change under the above SLR scenarios. ResultsOur results identified 64 sites of interest, of which 32 received an overall “high” prioritisation score of 3 or more out of 5. This equates to approximately 21,114 ha of high priority potential blue carbon restoration sites.DiscussionThe MCDA enables development of a portfolio of viable restoration projects through a rapid “desktop” prioritisation of sites of interest, which can then guide investment in further detailed cost/benefit feasibility assessments. This study demonstrates an adaptable MCDA approach to map potential NCS projects at meaningful spatial scales and in-line with carbon market-based opportunities.

Evaluating alternative technologies to diesel generation in India using multi-criteria decision analysis

Diesel generators (DGs) are widely used in India by business and domestic consumers to provide resilience against unreliable power supplies, but have serious adverse environmental and health impacts. Low carbon alternatives to DGs are becoming more widely available and affordable, though technical and non-technical barriers remain to their widespread adoption. Targeted policy and financial interventions would help accelerate the deployment of these alternatives, where such interventions should be based on local needs. To this end, we use a Multi-Criteria Decision Analysis (MCDA) approach to identify appropriate technology alternatives for DGs in residential, industrial and agricultural applications in India. Within this study, the MCDA framework facilitates evidence-based decision-making through structured discussions with local stakeholders and for evaluating the most suitable option from a variety of available alternatives. Overall, our analysis concluded that a hybrid system combining solar PV and battery storage system are considered most suitable for residential, agricultural as well as industrial applications. This study sets out a pragmatic approach for decision makers considering how to minimise the adverse impacts of DGs while recognising the intricacies of requirements of different applications at a local level. Additionally, our approach showcases how co-creation of potential solutions, and ‘transparency’ in the process, can be accomplished in policy-making, which is critical for wider acceptance of interventions.

Overall aerodynamic performance of the airfoils with different amplitudes via a fuzzy decision making based Taguchi methodology

In this study, the overall aerodynamic performance of the airfoils with variable amplitude geometric structure for lift-type vertical axis wind turbine has been analyzed and optimized using Fuzzy Analytic Hierarchy Process (AHP)-Fuzzy COmbinative Distance-based Assessment (CODAS) based on Taguchi Method. In the design of the experiment, leading edge (LE) tubercle airfoil models, Reynolds number, and angle of attack are utilized as the control factors. Drag, lift, and lift to drag ratio performances by comparing the airfoils according to the baseline model are calculated and the combination of these performances is considered as the overall aerodynamic performance response. The experiments are carried out according to the orthogonal matrix L18. Since the importance of each response is different on lift-type vertical axis wind turbines, the importance weights of these responses were obtained by Fuzzy AHP according to the evaluation of the decision maker. Multiple responses are converted into a single response (the overall aerodynamic performance) via Fuzzy CODAS which enables to model uncertainty in order to overcome the physical effects that may arise in experiments. Thereby, a multi objective Taguchi methodology was applied for the overall aerodynamic performance with a novel Fuzzy logic based multi criteria decision analysis approach. As a result, Model-4, having tubercle design parameters of amplitude of 0.025c and 0.0125c and wavelength of 0.5c and 0.125c, was found to have the best performance with the novel Taguchi approach, which saves time and cost. In addition, it has been determined that the airfoils, Reynolds number and angle of attack are significant and what level of contribution to the overall aerodynamic performance. At this point, the most important control factor has emerged as the angle of attack.

Integrated decision support framework for construction land reduction projects prioritization in China: a multi-criteria decision analysis approach

Integrated decision support framework for construction land reduction projects prioritization in China: a multi-criteria decision analysis approach

Identifying managed aquifer recharge and rain water harvesting sites and structures for storing non-conventional water using GIS-based multi-criteria decision analysis approach

In arid climates, conventional water resources are severely limited and stressed in the face of rapid population growth and future climate change. So, it is necessary to find alternative non-conventional water resources for use in drought situations. Additionally, the non-conventional water resources in these areas are not sufficient to meet future water demand. Therefore, non-conventional water resources can be adopted as a strategic reserve to bridge the gap between water supply and demand in case of emergency and drought events. These resources might include rainwater harvesting, treated wastewater, and desalinated seawater. Managed aquifer recharge (MAR) can be applied to store these resources in the hydrogeological system using Geo information System—Multi Criteria Decision Analysis (GIS-MCDA) approach for determining the suitable MAR location for storage. North-west Kingdom of Saudi Arabia area was chosen for this study because it is extremely arid, has high potential for social and economic development, and it has newly constructed non-conventional water infrastructures distributed throughout the area including water desalination plants, Tertiary Sewage Effluent (TSE) waste water plants, and flash-flood storage dams. To identify the suitable MAR site location and structure, different data related to aquifer hydrogeology, surface hydrology, hydrometeorology, and water quality were applied. Then, GIS-MCDA holistic approach was applied with aid of ordered weighting average (OWA) technique. Finally, two maps were created to show the MAR location and structure type. Potential map indicates that ~ 18.85% of the area is suitable for MAR installations. About 0.17% of the total area exhibited very high potential, where infiltration ponds can be applied, 1.86% had high potential for construction of check dams with diversion channels, and 16.82% had moderate potential for installation of recharge wells. Additionally, 56 MAR structures were proposed and a map showing their locations has been created. Thus, results indicated that the study area is promising for MAR installation. These maps could aid the decision makers to propose a sustainable development plan for the future water resources of the area.

Suitable Site Selection of Public Charging Stations: A Fuzzy TOPSIS MCDA Framework on Capacity Substation Assessment

The number of electric vehicles (EVs) continues to increase in the automobile market, driven by public policies since they contribute to the global decarbonization of the transportation sector. Still, the main challenge to increasing EV adoption is charging infrastructure. Therefore, the site selection of public EV charging stations should be made very carefully to maximize EV usage and address the population’s range anxiety. Since electricity demand for charging EVs introduces new load shapes, the interrelationship between the location of charging stations and long-term electrical grid planning must be addressed. The selection of the most suitable site involves conflicting criteria, requiring the application of multi-criteria analysis. Thus, a geographic information system-based Multicriteria Decision Analysis (MCDA) approach is applied in this work to address the charging station site selection, where the demographic criteria and energy density are taken into account to formulate an EV increase model. Several methods, including Fuzzy TOPSIS, are applied to validate the selection of suitable sites. In this evaluation, the impact of the EV charging station on the substation capacity is assessed through a high EV penetration scenario. The proposed method is applied in Cuenca, Ecuador. Results show the effectiveness of MCDA in assessing the impact of charging stations on power distribution systems ensuring suitable system operation under substation capacity reserves.

Using a Patient-Centered Multicriteria Decision Analysis to Assess the Value of Multiple Sclerosis Treatments in the US: A Study Protocol.

The engagement of patients and family caregivers in value assessment is pivotal since they provide valuable contributions to assessment acceptability and relevance. The proposed study aims to use patient-centered techniques and multicriteria decision analysis (MCDA) to evaluate the values of disease-modifying therapies (DMTs) for multiple sclerosis (MS) from the perspectives of patients and family caregivers living in three 'Deep South' States of the US-Alabama, Louisiana, and Mississippi. This study will follow guidance from the Patient-Centered Outcomes Research Institute (PCORI) for patient engagement and two best practice reports for MCDA from the Professional Society for Health Economics and Outcomes Research (ISPOR) to complete value assessment. Throughout the study, we will engage multiple stakeholders, including patients, family caregivers,healthcare providers, and payers. Forty patients with MS and their family caregivers from Alabama, Louisiana, and Mississippi will be invited to participate in this study. We will intensively train them for value assessment knowledge and MCDA before we engage them in MCDA to determine the value of DMTs for MS. Our approach differs from common MCDA since we incorporated a patient-centered framework in this study. Unlikeprevious studies only briefly inform or prepare participants before the MCDA process, in this study, we will provide basicvalue assessment trainings forpatients and family caregivers to ensure they can effectively engage throughout the patient-centeredMCDAprocess. We expect this study will demonstrate that the patient-centered MCDA approach is feasible and likely leads to improved patients' and family caregivers' engagementin value assessment.

Assessing Borneo’s tropical forests and plantations: a multi-sensor remote sensing and geospatial MCDA approach to environmental sustainability

The assessment of environmental sustainability is of utmost importance for the forests and plantations in Borneo, given the critical need for environmental protection through the identification and mitigation of potential risks. This study was conducted to assess the environmental sustainability of tropical forest and plantations landscape, a case study in northern Sabah, Malaysian Borneo. Applications of the latest high-resolution multi-sensor remote sensing and geospatial MCDA are cost-effective and useful for large-scale environmental sustainability assessment. The land use land cover (LULC) of the study area was mapped with synergistic use of Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 optical and high-resolution PlanetScope satellite imageries, resulting in overall accuracy of 87.24%. Five sustainability indicator layers: slope erosion protection, river buffer, landscape connectivity and quality, high conservation value (HCV), and water turbidity were developed from the LULC map, ancillary datasets of SRTM, and forest operation basemap with reference to standards from the Environment Protection Department (EPD), Roundtable on Sustainable Palm Oil (RSPO), and Forest Management Plan (FMP) for the analysis using multi-criteria decision analysis (MCDA) model. The results revealed that overall, the study areas are in the high sustainability category at 61%, medium at 31%, and low at only 8%. We analyzed the environmental sustainability of five land use boundaries, and the results showed that Industrial Tree Plantations (ITP) and Village Reserve are mostly in the high category. Meanwhile, oil palm plantations, rubber plantations, and forest reserve (FR) are the majority in the medium category. Both oil palm and rubber plantations are a majority in the medium class due to monocropping land use type having low landscape connectivity and quality individual sustainability indicator layer. The study presented the concept of use of multi-sensor remote sensing for LULC mapping with geospatial MCDA for environmental sustainability assessment useful to stakeholders for improving the management plan also contributing toward the progress of achieving UNSDGs and addressing REDD+.

Quantifying factors which influence the value of approved biologic treatments in SLE a Multi-Criteria Decision Analysis (MCDA) approach in Spain

Objective: The objective of the present study is to assess the value contribution of belimumab compared with anifrolumab in the treatment of adult patients with systemic lupus erythematosus (SLE) in Spain using reflective Multi-Criteria Decision Analysis (MCDA). Methodology: A literature review was conducted to complete the criteria included in the EVIDEM MCDA framework. A multidisciplinary panel of eight experts, including two rheumatologists and one internist specialized in managing patients with SLE, two regional decision-makers, and three hospital pharmacists scored each criterion of the MCDA framework used. The study was developed following the MCDA methodology, including criteria scoring, aggregate scoring, value determination, and discussion of findings. Performance scores provided by experts were analysed quantitatively and qualitatively. Results: SLE was considered a potentially severe and heterogeneous disease, with important unmet needs affecting a considerably sized population. Experts considered the absence of curative therapy, the adverse effects of conventional treatments, constitutive manifestations such as fatigue and organ damage accrual as relevant unmet needs in the management of SLE. Belimumab was perceived to have a slightly higher efficacy profile, with better safety profile and to provide improved Patient Reported Outcomes (PROs) than anifrolumab. Experts considered that belimumab and anifrolumab do not differ in terms of cost of intervention; however, belimumab’s advantage lies in its potential to generate savings by reducing both direct and indirect costs. Overall, belimumab’s therapeutic impact on patients with SLE is considered high and supported by high-quality evidence. Conclusion: Based on reflective MCDA methodology, belimumab is perceived as a value-added option for the treatment of adult patients with SLE when compared with anifrolumab. Nevertheless, it is important to consider the lack of head-to-head comparations and long-term data for anifrolumab regarding these conclusions. These findings underscore the potential benefits of belimumab for patients and the healthcare system, emphasizing its role as an add-on therapy in improving outcomes for individuals with SLE. Keywords: belimumab, systemic lupus erythematous, anifrolumab, autoimmune disease, multi-criteria decision analysis (MCDA).

A Framework Analyzing Climate Change, Air Quality and Greenery to Unveil Environmental Stress Risk Hotspots

Rapid urbanization has resulted in increased environmental challenges, compounding worries about deteriorating air quality and rising temperatures. As cities become hubs of human activity, understanding the complex interplay of numerous environmental elements is critical for developing effective mitigation solutions. Recognizing this urgency, a framework to highlight the hotspots with critical environmental issues emerges as a comprehensive approach that incorporates key criteria such as the surface urban heat island intensity (SUHII), heat index (HI) and air quality index (AQI) to assess and address the complex web of environmental stressors that grip urban landscapes. Employing the multicriteria decision analysis approach, the proposed framework, named the environmental risk hotspot mapping framework (ERHMF), innovatively applies the analytic hierarchy process at a sub-criteria level, considering long-term heat island trends with recent fluctuations in the HI and AQI. Climate change impact has been symbolized through rising temperatures, as reflected by surface urban heat island intensity trends over two decades. The robustness and correctness of the weights have been assessed by computing the consistency ratio, which came out as 0.046, 0.065 and 0.044 for the sub-criteria of the SUHII, AQI and HI, respectively. Furthermore, the framework delves into the nexus between environmental stressors and vegetation cover, elucidating the role of green spaces in mitigating urban environmental risks. Augmented by spatial and demographic data, the ERHMF adeptly discerns high-risk areas where environmental stress converges with urban development, vulnerable population concentrations and critical vegetation status, thereby facilitating targeted risk management interventions. The framework’s effectiveness has been demonstrated in a regional case study in Italy, underscoring its ability to pinpoint risk hotspots and inform specific policy interventions. The quantitative study undertaken at the sub-administrative level revealed that approximately 6,000,000 m2 of land in Bologna are classified as being under high to extremely high environmental stress, with over 4,000,000 m2 lying only within the extremely high stress group (90–100). Similarly, 1,000,000 m2 of land in Piacenza and Modena have high levels of environmental stress (80–90). In conclusion, the ERHMF presents a holistic methodology for delineating high-risk urban hotspots, providing essential insights for policymakers, urban planners and stakeholders, with the potential to enhance overall urban resilience and foster sustainable development efforts.