Micro-spatial flood risk assessment in Nagaon district, Assam (India) using GIS-based multi-criteria decision analysis (MCDA) and analytical hierarchy process (AHP)

Nagaon is one of the highly flood-prone districts of Assam, India that recurrently experiences devastating floods resulting in the loss of lives and property and wreaking havoc on the district's socioeconomic infrastructure. Identification and mapping of spatial patterns of flood hazards, flood vulnerability, and flood risk zones (FRZs) of the district are, therefore, crucial for flood management and mitigation. The present study, therefore, attempts to delineate the FRZs of more than 930 villages in the Nagaon district by integrating the flood hazard and vulnerability layers in the geospatial environment using the multi-criteria decision analysis and analytical hierarchy process techniques. Here, seven flood hazard and vulnerability indicators are considered to derive each layer separately. The results indicate that about 15.14% of the district's total villages are in the very high FRZ, 27.93% in the high, 46.62% in the moderate, and 10.3% in the low FRZ. Further, bivariate correlation analysis is used to evaluate the results with the percentages of the population, cropland, and animals affected by floods at different temporal scales in order to ensure that the revenue circles with a higher percentage of area under high and very high FRZs genuinely have higher percentages of flood-affected cropland, people, and livestock. The significance of this research is evident in its pragmatic findings that could aid the stakeholders in managing and reducing flood risk at micro-spatial scales.

National Immunization Program Decision Making Using the CAPACITI Decision-Support Tool: User Feedback from Indonesia and Ethiopia

To ensure that limited domestic resources are invested in the most effective interventions, immunization programs in low- and middle-income countries (LMICs) must prioritize a growing number of new vaccines while considering opportunities to optimize the vaccine portfolio, as well as other components of the health system. There is a strong impetus for immunization decision-making to engage and coordinate various stakeholders across the health system in prioritization. To address this, national immunization program decision-makers in LMICs collaborated with WHO to structure deliberation among stakeholders and document an evidence-based, context-specific, and transparent process for prioritization or selection among multiple vaccination products, services, or strategies. The output of this effort is the Country-led Assessment for Prioritization on Immunization (CAPACITI) decision-support tool, which supports using multiple criteria and stakeholder perspectives to evaluate trade-offs affecting health interventions, taking into account variable data quality. Here, we describe the user feedback from Indonesia and Ethiopia, two initial countries that piloted the CAPACITI decision-support tool, highlighting enabling and constraining factors. Potential immunization program benefits and lessons learned are also summarized for consideration in other settings.

Using the Online Elicitation of Personal Utility Functions Approach to Derive a Patient-Based 5-Level Version of EQ-5D Value Set: A Study in 122 Patients With Rheumatic Diseases From Germany

OBJECTIVES

Traditional preference elicitation methods, such as discrete choice experiments or time trade-off, usually require large sample sizes. This can limit their applicability in patient populations, where recruiting enough participants can be challenging. The objective of this study was to test a new method, called the Online elicitation of Personal Utility Functions (OPUF) approach, to derive an EQ-5D-5L value set from a relatively small sample of patients with rheumatic diseases.

METHODS

OPUF is a new type of online survey that implements compositional preference elicitation techniques. Central to the method are 3 valuation steps: (1) dimension weighting, (2) level rating, and (3) anchoring. An English demo version of the OPUF survey can be accessed at https://valorem.health/eq5d5l. From the responses, a personal EQ-5D-5L utility function can be constructed for each participant, and a group-level value set can be derived by aggregating model coefficients across participants.

RESULTS

A total of 122 patients with rheumatic disease from Germany completed the OPUF survey. The survey was generally well received; most participants completed the survey in less than 20 minutes and were able to derive a full EQ-5D-5L value set. The precision of mean coefficients was high, despite the small sample size.

CONCLUSIONS

Our findings demonstrate that OPUF can be used to derive an EQ-5D-5L value set from a relatively small sample of patients. Although the method is still under development, we think that it has the potential to be a valuable preference elicitation tool and to complement traditional methods in several areas.

A multi-criteria decision framework for circular wastewater systems in emerging megacities of the Global South

Lima faces increasing water stress due to demographic growth, climate change and outdated water management infrastructure. Moreover, its highly centralized wastewater management system is currently unable to recover water or other resources. Hence, the primary aim of this study is to identify suitable wastewater treatment alternatives for both eutrophication mitigation and indirect potable reuse (IPR). For eutrophication mitigation, we examined MLE, Bardenpho, Step-feed, HF-MBR, and FS-MBR. For IPR, we considered secondary treatment+UF + RO + AOP or MBR + RO + AOP. These alternatives form part of a WWTP network at a district level, aiding Lima's pursuit of a circular economy approach. This perspective allows reducing environmental impacts through resource recovery, making the system more resilient to disasters and future water shortages. The methods used to assess these scenarios were Life Cycle Assessment for the environmental dimension; Life Cycle Costing for the economic perspective; and Multi-Criteria Decision Analysis to integrate both the quantitative tools aforementioned and qualitative criteria for social and techno-operational dimensions, which combined, strengthen the decision-making process. The decision-making steered towards Bardenpho for eutrophication abatement when environmental and economic criteria were prioritized or when the four criteria were equally weighted, while HF-MBR was the preferred option when techno-operational and social aspects were emphasized. In this scenario, global warming (GW) impacts ranged from 0.23 to 0.27 kg CO2eq, eutrophication mitigation varied from 6.44 to 7.29 g PO4- equivalent, and costs ranged between 0.12 and 0.17 €/m3. Conversely, HF-MBR + RO + AOP showed the best performance when IPR was sought from the outset. In the IPR scenario, GW impacts were significantly higher, at 0.46-0.51 kg CO2eq, eutrophication abatement was above 98 % and costs increased to ca. 0.44 €/m3.

Evaluation of antibody-based preventive alternatives for respiratory syncytial virus: a novel multi-criteria decision analysis framework and assessment of nirsevimab in Spain

BACKGROUND

Respiratory syncytial virus (RSV) is a highly infectious disease that poses a significant clinical and medical burden, as well as social disruption and economic costs, recognized by the World Health Organization as a public health issue. After several failed attempts to find preventive candidates (compounds, products, including vaccines), new alternatives might be available, one being nirsevimab, the first and only option approved for RSV prevention in neonates and infants during their first RSV season. The objective of this study was to develop a novel multi-criteria decision analysis (MCDA) framework for RSV antibody-based preventive alternatives and to use it to assess the value of nirsevimab vs. placebo as a systematic immunization approach to prevent RSV in neonates and infants during their first RSV season in Spain.

METHODS

Based on a pre-established model called Vaccinex, an ad-hoc MCDA framework was created to reflect relevant attributes for the assessment of current and future antibody-based preventive measures for RSV. The estimated value of nirsevimab was obtained by means of an additive linear model combining weights and scores assigned by a multidisciplinary committee of 9 experts. A retest and three sensitivity analyses were conducted.

RESULTS

Nirsevimab was evaluated through a novel framework with 26 criteria by the committee as a measure that adds value (positive final estimated value: 0.56 ± 0.11) to the current RSV scenario in Spain, by providing a high efficacy for prevention of neonates and infants. In addition, its implementation might generate cost savings in hospitalizations and to the healthcare system and increase the level of public health awareness among the general population, while reducing health inequities.

CONCLUSIONS

Under a methodology with increasing use in the health field, nirsevimab has been evaluated as a measure which adds value for RSV prevention in neonates and infants during their first RSV season in Spain.

Optimal site selection for construction and demolition waste disposal using GIS-FAHP: a case study from Kafr El Sheikh City, Egypt

The increasing number of building and demolition projects results in huge amounts of construction and demolition wastes (CDWs) that are illegally dumped. However, these wastes must be disposed of in appropriate legal sites to protect the environment and human health. After reviewing the literature, no prior research examined optimal site selection for dumping or recycling CDW in an Egyptian city. Furthermore, the absence of field surveys did not offer a holistic understanding of the specific criteria used in the model for this region, nor did it permit an assessment of the suitability of existing dumpsites, thereby revealing certain limitations in the final results. In this regard, this research aims to apply a multi-criteria geographic information system (GIS)-based framework to identify an optimal site for CDW disposal in Kafr El Sheikh City. The criteria affecting the site selection are identified and categorized from prior literature, which are further refined using field surveys and focus group to evaluate their applicability in the context of an Egyptian city. After conducting questionnaire surveys, the trapezoidal interval type II fuzzy analytic hierarchy process is applied to compute the weights of the identified criteria from the perspective of each group of experts. The entropy-based aggregation approach is employed to identify the compromise weights taking into account the preferences of different groups. GIS is a powerful tool for geoprocessing and analyzing spatial big data. The result is a scenario map for the optimal site locations with varying suitability scales (i.e., excellent, very good, good, average, poor, and very poor). The proposed methodology provides what-if scenarios based on a selected set of criteria. According to the results of the multi-criteria decision analysis models, the suitability varies based on the weights of the criteria. For the equal-weighted criteria model, the excellent category covers 5.96% of the study area, increasing to 6.48% for the weighted criteria model. These areas primarily lie in the northeast direction. Conversely, the majority of the study area, 41.80% under equal-weighted criteria and 32.39% under weighted criteria, falls within the average and poor suitability categories, respectively. In general, the most suitable areas are located on the outskirts of the city, and the suitability decreases near the central business district. To bridge the gap between research findings and practical applications, a land use analysis employing satellite imagery is conducted to pinpoint suitable locations for CDW disposal. Existing CDW dumpsites predominantly fall within the range of poor to very good for the equal-weighted criteria model, while the weighted criteria model categorizes them into the poor (16.66%) and average (83.33%) categories. The findings demonstrated the applicability of the proposed framework for CDW disposal management and planning.

The development of a novel decision support system for regional land use planning for brownfield land

Digital tools, particularly specialised decision support systems (DSSs), can be utilized to assist in the complex process of brownfield redevelopment. Existing brownfield DSSs typically focus on site-specific, late-stage applications, and socioeconomic factors are often overlooked. In this paper, we present a novel DSS aimed at providing support for early-stage, city region-scale brownfield land use planning and redevelopment. The proposed DSS is a prototype WebGIS application that enables land use planners and other brownfield regeneration professionals to examine a region and a set of sites during the initial planning phase for brownfield redevelopment. The DSS includes three bespoke modules comprising: (1) Land Use Potential (residential, commercial, and public open space), (2) risks posed by contamination and geotechnical hazards, (3) data pertinent to brownfield economic viability assessments. We outline a use case for this DSS, developed through comprehensive user-requirements gathering, and subsequently describe the techniques employed to construct the DSS modules and user interface. Finally, we present the results of user testing, wherein case-study stakeholders assessed the DSS. The feedback obtained during user testing aided in the identification of areas for improvement with regard to the functionality, usability, and effectiveness of the DSS in supporting decision-makers. The feedback was utilized to implement iterative improvements to the DSS and to plan future developments for the prototype DSS.

Establishment of evaluation system for biological remediation on organic pollution in groundwater using slow-release agents

In situ bioremediation through slow-release agents can continuously degrade organic pollutants for a long time and have high application potential in solving problems such as tailing and rebound. However, the existing evaluation system is difficult to reflect the performance of bioremediation through slow-release agents, which is not conducive to the promotion of technology. It is urgent to establish a targeted evaluation system. Therefore, based on the multi-criteria decision-making method (MCDA), a comprehensive evaluation model was established. The evaluation index system was constructed for bioremediation through slow-release agents consisting of 16 indicators including pollutant degradation rate, agent preparation cost, engineering operation and maintenance cost, secondary pollution, long-term degradation stability, slow release time, slow release stability, increase in functional microbial flora, increase in total DNA content, agent particle size, solid agent morphology, liquid agent viscosity, dispersibility in aqueous phase, zeta potential, operability of agent preparation, and engineering operation management difficulty. Then, the weight of the indicators was determined by using the best-worst method (BWM), and evaluation criteria was established based on relevant norms and literature. Both and the indicators aggregation simple additive weighting (SAW) method constitute a quantitative evaluation model. The above content together constitutes a new evaluation system for biological remediation on organic pollution in groundwater using slow-release agents, which was defined as AOBS evaluation system. In order to verify the rationality and scientificity of the evaluation system, a typical bioremediation slow-release agent was evaluated using the established AOBS evaluation system. The results showed that the evaluation system could reasonably and comprehensively evaluate bioremediation through slow-release agents and provide suggestions for agent improvement.

Prioritizing the Best Potential Regions for Brine Concentration Systems in the USA Using GIS and Multicriteria Decision Analysis

We propose a methodology for identifying and prioritizing the best potential locations for brine concentration facilities in the contiguous United States. The methodology uses a geographic information system and multicriteria decision analysis (GIS-MCDA) to prioritize the potential locations for brine concentration facilities based on thermodynamic, economic, environmental, and social criteria. By integrating geospatial data with a computational simulation of a real brine concentration system, an objective weighting method identifies the weights for 13 subcriteria associated with the main criteria. When considering multiple dimensions for decision making, brine concentration facilities centered in Florida were consistently selected as the best location, due to the high second-law efficiency, low transportation cost, and high capacity for supplying municipal water needs to nearby populations. For inland locations, Southeast Texas outperforms all other locations for thermodynamic, economic, and environmental priority cases. A sensitivity analysis evaluates the consistency of the results as the priority of a main criterion varies relative to other decision-making criteria. Focusing on a single subcriterion misleads decision making when identifying the best location for brine concentration systems, identifying the importance of the multicriteria methodology.

Optimized landfill site selection for municipal solid waste by integrating GIS and multicriteria decision analysis (MCDA) technique, Hossana town, southern Ethiopia

Improper solid waste disposal has remained the major bottleneck for the socio-economic development particularly in urban and peri-urban areas of Ethiopia. This study was conducted with the prime aim of identifying an optimum municipal solid waste (MSW) management option subsequently selecting the best landfill site in Hossana town using integrated geographical information systems (GIS) and multicriteria decision analysis (MCDA) techniques. Accordingly, GIS integrated with MCDA was used to analyze the relative weight of each criterion and the overall suitability map where ten criteria were considered within their respective constraints. To create a landfill suitability index, environmental and socioeconomic factors such as distance from settlement, land use and land cover, lineament, slope, road, and wind direction/aspect were weighted. Population growth, waste generation rate, and waste volume/year were used to calculate the required landfill size. The study finding revealed that the town's MSW generation rate was 0.45 kg/cap/day, which was within the range of most of Ethiopian urban areas. On the other hand, the total daily and annual MSW generation was found to be 79.58 and 29,047 tonnes, respectively. Moreover, the study's findings revealed that 20.8 % of the solid waste was found was recyclable and the remaining 79.20 % was non-recyclable. Considering the future trend of waste generation, 19 ha of land in the city's Northern and Southern outskirts was chosen as a candidate landfill site with all the necessary suitability analysis. Therefore, optimized landfill site selection and better management system of MSW in urban and peri-urban areas could be achieved by the conjunctive application of MCDA and GIS.

Identifying and prioritizing sustainability indicators for China's assessing demolition waste management using modified Delphi-analytic hierarchy process method

Addressing the sustainability issues arising from construction and demolition waste management (DWM) has gained little traction due to the lack of incentives, stringent regulations, and systematic guidance. This study aims to empower systematic decision-making concerning DWM alternative selection by developing a sustainability assessment framework by coupling a modified Delphi method with the multicriteria decision analysis technique. First, the study identifies a comprehensive inventory of indicators across three dimensions of sustainability in the context of DWM. Next, the study combines a modified Delphi method with the analytic hierarchy process to validate and prioritize the selected sustainability indicators. For the first time, insights regarding the DWM sustainability indicators from China's construction industry practitioners' perspectives are elicited using a mixed method comprising online semistructured interviews and two rounds of questionnaire surveys. Experts participating in the research are mostly based in Guangzhou and Shenzhen, where local governments exhaust all efforts in promoting carbon-neutral and sustainable development. The findings reveal that eight sustainability indicators were regarded as the determinants for the sustainability performance of DWM, with the global warming potential (32%), energy efficiency (16.1%) and land use (13.5%) receiving the highest preference scores (weights) based on the experts' judgment. Notably, the economic factors like the total cost (6.54%) appeared not highly prioritized by the local experts as typically did in the previous studies from developing countries.

Planning Benefit-Risk Assessments Using Visualizations

A Benefit Risk Assessment Plan (BRAP) describes the assessments planned to determine whether the benefits of an investigational drug outweigh the risks. The plan can have two sections, one with timelines for aligning resources with decision milestones and the other for pre-specifying assessments for decision milestones. Regulatory guidance recommends a proactive planning process over an ad-hoc process. However, very little has been published about proactive plans themselves. This article works through a hypothetical example visualizing a series of assessments across the drug development lifecycle. Based on a regulatory framework, the planning process starts with assessing the medical condition and current treatment options. These early assessments bring out major considerations in assessing the investigational drug.

Cyber risk assessment in small and medium-sized enterprises: A multilevel decision-making approach for small e-tailors

The role played by information and communication technologies in today's businesses cannot be underestimated. While such technological advancements provide numerous advantages and opportunities, they are known to thread organizations with new challenges such as cyberattacks. This is particularly important for small and medium-sized enterprises (SMEs) that are deemed to be the least mature and highly vulnerable to cybersecurity risks. Thus, this research is set to assess the cyber risks in online retailing SMEs (e-tailing SMEs). Therefore, this article employs a sample of 124 small e-tailers in the United Kingdom and takes advantage of a multi-criteria decision analysis (MCDA) method. Indeed, we identified a total number of 28 identified cyber-oriented risks in five exhaustive themes of "security," "dependency," "employee," "strategic," and "legal" risks. Subsequently, an integrated approach using step-wise weight assessment ratio analysis (SWARA) and best-worst method (BWM) has been employed to develop a pathway of risk assessment. As such, the current study outlines a novel approach toward cybersecurity risk management for e-tailing SMEs and discusses its effectiveness and contributions to the cyber risk management literature.

Insights of dam site selection for rainwater harvesting using GIS: A case study in the Al- Qalamoun Basin, Syria

Today's world is plagued with water shortages, especially in developing countries. The problem is made worse by increasing water demands and decreasing rainfall occurrences in arid and semi-arid areas. Rainwater harvesting (RWH) has the potential to be a viable solution for this issue, as it can augment existing water supplies in the long term. This study aimed to identify suitable areas for RWH using a multi-criteria decision analysis (MCDA) based on the analytic hierarchy process (AHP) method, combined with geographic information system (GIS) and remote sensing (RS) techniques. This study has been carried out in the Al-Qalamoun Basin, the western part of Syria, which has not been studied for rainwater harvesting before. To fill this gap, a potential RWH map was created in the Al-Qalamoun Basin using nine factors, which are land use and land cover (LULC), soil texture, slope, rainfall, curve number (CN), stream order, distance to faults, distance to roads, and distance to residential areas. All thematic layers were allocated appropriate weights and combined using the weighted Overlay process (WOP) in ArcGIS 10.8 to produce a RWH map of the study area. The findings indicated that about 18.1% of the total study area was classified as most suitable and suitable for RWH. Validation of the RWH map with the existing dams indicated that the methodology adopted in this study had a high capacity to identify sites suitable for RWH. The study presents a useful and inexpensive tool for decision-makers to avoid unsuitable sites and focus on the most suitable sites for constructing dams.

Identifying the suitable managed aquifer recharge (MAR) strategy in an overexploited and contaminated river basin

Managed aquifer recharge (MAR) is a promising adaptation measure to reduce vulnerability to climate change and hydrological variability. However, in areas where the basin is highly polluted, densely populated, and intensely cultivated, implementing suitable MAR strategies is a significant challenge. This study used a geographic information system-based multicriteria decision analysis (GIS-MCDA) approach to delineate the MAR potential sites using seven thematic layers describing surface and subsurface features. Further, basin-specific MAR approach was developed using information such as polluted water areas, canal network distribution for water supply, and cropping patterns. The results of this study indicate that only 17% of the area is highly suitable, while 54% and 29% were found moderately suitable and unsuitable for the MAR approach. Since most highly and moderately suitable sites were falling in the agricultural areas, agricultural-based MAR (AgMAR) was considered a preferred option. AquaCrop model for sugarcane was developed considering excess canal water supply during the grand growth stage to understand the AgMAR potential in the study area. It was observed that the potential recharge under normal irrigation scenarios varies from 135.5 to 272 mm/year, which can be increased through AgMAR up to 545 mm/year depending on the water availability for excess irrigations. This study provides an improved understanding of the parameters that should be considered for MAR site selection and post-GIS-MCDA analysis to assess the basin-specific MAR strategy.

Development of a Choice-framework for Covid vaccines in India using a multi-criteria decision analysis approach

BACKGROUND

Vaccines were crucial in controlling the Covid-19 pandemic. As more vaccines receive regulatory approval, stakeholders will be faced with several options and must make an appropriate choice for themselves. We proposed a multi-criteria decision analysis (MCDA) framework to guide decision-makers in comparing vaccines for the Indian context.

METHODS

We adhered to the ISPOR guidance for the MCDA process. Seven vaccine options were compared under ten criteria. Through three virtual workshops, we obtained opinions and weights from citizens, private-sector hospitals, and public health organisations. Available evidence was rescaled and incorporated into the performance matrix. The final score for each vaccine was calculated for the different groups. We performed different sensitivity analyses to assess the consistency of the rank list.

RESULTS

The cost, efficacy and operational score of the vaccines had the highest weights among the stakeholders. From the six scenario groups, Janssen had the highest score in four. This was driven by the advantage of having a single dose of vaccination. In the probabilistic sensitivity analysis for the overall group, Covaxin, Janssen, and Sputnik were the first three options. The participants expressed that availability, WHO approvals and safety, among others, would be crucial when considering vaccines.

CONCLUSIONS

The MCDA process has not been capitalised on in healthcare decision-making in India and LMICs. Considering the available data and stakeholder preference at the time of the study, Covaxin, Janssen, and Sputnik were preferred options. The choice framework with the dynamic performance matrix is a valuable tool that could be adapted to different population groups and extended based on increasing vaccine options and emerging evidence. *ISPOR - The Professional Society for Health Economics and Outcomes Research.

Protein Fitness Prediction Is Impacted by the Interplay of Language Models, Ensemble Learning, and Sampling Methods

Advances in machine learning (ML) and the availability of protein sequences via high-throughput sequencing techniques have transformed the ability to design novel diagnostic and therapeutic proteins. ML allows protein engineers to capture complex trends hidden within protein sequences that would otherwise be difficult to identify in the context of the immense and rugged protein fitness landscape. Despite this potential, there persists a need for guidance during the training and evaluation of ML methods over sequencing data. Two key challenges for training discriminative models and evaluating their performance include handling severely imbalanced datasets (e.g., few high-fitness proteins among an abundance of non-functional proteins) and selecting appropriate protein sequence representations (numerical encodings). Here, we present a framework for applying ML over assay-labeled datasets to elucidate the capacity of sampling techniques and protein encoding methods to improve binding affinity and thermal stability prediction tasks. For protein sequence representations, we incorporate two widely used methods (One-Hot encoding and physiochemical encoding) and two language-based methods (next-token prediction, UniRep; masked-token prediction, ESM). Elaboration on performance is provided over protein fitness, protein size, and sampling techniques. In addition, an ensemble of protein representation methods is generated to discover the contribution of distinct representations and improve the final prediction score. We then implement multiple criteria decision analysis (MCDA; TOPSIS with entropy weighting), using multiple metrics well-suited for imbalanced data, to ensure statistical rigor in ranking our methods. Within the context of these datasets, the synthetic minority oversampling technique (SMOTE) outperformed undersampling while encoding sequences with One-Hot, UniRep, and ESM representations. Moreover, ensemble learning increased the predictive performance of the affinity-based dataset by 4% compared to the best single-encoding candidate (F1-score = 97%), while ESM alone was rigorous enough in stability prediction (F1-score = 92%).

Barriers and facilitators to implementing priority setting and resource allocation tools in hospital decisions: A systematic review

Health care budgets in high-income countries are having issues coping with unsustainable growth in demand, particularly in the hospital setting. Despite this, implementing tools systematising priority setting and resource allocation decisions has been challenging. This study answers two questions: (1) what are the barriers and facilitators to implementing priority setting tools in the hospital setting of high-income countries? and (2) what is their fidelity? A systematic review using the Cochrane methods was conducted including studies of hospital-related priority setting tools reporting barriers or facilitators for implementation, published after the year 2000. Barriers and facilitators were classified using the Consolidated Framework for Implementation Research (CFIR). Fidelity was assessed using priority setting tool's standards. Out of thirty studies, ten reported program budgeting and marginal analysis (PBMA), twelve multi-criteria decision analysis (MCDA), six health technology assessment (HTA) related frameworks, and two, an ad hoc tool. Barriers and facilitators were outlined across all CFIR domains. Implementation factors not frequently observed, such as 'evidence of previous successful tool application', 'knowledge and beliefs about the intervention' or 'external policy and incentives' were reported. Conversely, some constructs did not yield any barrier or facilitator including 'intervention source' or 'peer pressure'. PBMA studies satisfied the fidelity criteria between 86% and 100%, for MCDA it varied between 36% and 100%, and for HTA it was between 27% and 80%. However, fidelity was not related to implementation. This study is the first to use an implementation science approach. Results represent the starting point for organisations wishing to use priority setting tools in the hospital setting by providing an overview of barriers and facilitators. These factors can be used to assess readiness for implementation or to serve as the foundation for process evaluations. Through our findings, we aim to improve the uptake of priority setting tools and support their sustainable use.

Identification and selection of suitable landfill sites using GIS-based multi-criteria decision analysis in the Peshawar District, Pakistan

Managing municipal solid waste (MSW) is indispensable for public health and quality living standards in urban and rural environments. Suitable landfill site selection (LSS) requires the consideration of many diverse criteria. This study uses various environmental, social and economic criteria in a sophisticated multi-criteria decision analysis (MCDA) within the geographical information system (GIS) and aims to provide a scientific basis for the identification of suitable landfill sites which can efficiently be used for MSW in one of the most urbanized cities (Peshawar district) in Pakistan. The methodology involves pairwise comparisons of the selected and ranked criteria using the analytical hierarchy process (AHP). A weighted linear combination (WLC) was applied to generate the most suitable landfill site for MSW disposal within the study area. The results show that approximately 11.4% (14,485.15 ha) and 16.6% (21,211.95 ha) of the total study area are either very highly suitable or highly suitable, 20.8% (26,525.56 ha) area is unsuitable and the remaining areas are either low (27.3%; 34,834.84 ha) or moderately suitable (23.8%; 30,356.84 ha) for the construction of landfill sites. It is recommended that using the proposed landfill sites would have the least consequences of public health risks and environmental degradation.

Fuzzy PROMETHEE model for public transport mode choice analysis

The importance of public transportation service quality research is significantly increasing in recent years, it is the key to understanding and analyzing passengers' preferences. Different approaches are utilized to explore users' preferences however, dominantly these apply merely subjective scoring of the attributes and alternatives of the mobility. In this paper, we design a specific model for public transportation mode choice which is capable of integrating subjective scoring with scoring by objective measures such as distance or time. Owing to this purpose, we combine the outranking Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) as a method to evaluate passengers' preferences for tangible and intangible criteria with the fuzzy theory, and the Graphical Analysis for Interactive Aid (GAIA) plane to visualize the interactions between attributes as well as to test the robustness of the results via sensitivity analysis. The contribution of this paper is the constructed integrative method that is less subjective than the well-known models but also keeps the freedom of individual evaluators in expressing their preferences. Moreover, another significant issue of mode choice analysis is the group consideration, which is also refined in the new methodology by taking into account not only the mean of group preferences but also their range. A common characteristic of public surveys, the possible vague responses of the layman pattern is solved with the fuzzy approach to reduce the risk of uncertain scoring. The proposed model acts as a great base for the fuzzy inference system that can facilitate mode choice for passengers within a changing environment. The efficiency of the new methodology is demonstrated through a real-world case study of Budapest city, the obtained results are supporting underground mode service quality and highlighting its impact on citizens' behavior in favor of public transport.

Risk ranking of chemical hazards in foods: comparison of aggregating methods using infant formula as an example

The aim of this study was to rank several chemical hazards present in one food item, namely infant formula. We first identified the substances potentially present in infant foods according to the results of the French infant Total Diet Study and to the available scientific literature. Second, we built three criteria to rank the hazards: severity, contribution to the total exposure, and risk characterisation. Each criterion was scored using quantitative or semi-quantitative scales. Third, in order to rank the chemical hazards, two approaches of aggregation of the three criteria were deployed. On the one hand, a multi-criteria decision analysis outranking method and on the other hand a semi-quantitative risk-matrix type method. We then tested these approaches on follow-on formulae for the 7-12 months population, for which contamination data from the French infant Total Diet study were available. The results of both methods showed that the six prioritised substances are the same even if not in the exact same order (acrylamide, inorganic arsenic, furan, chromium VI, lead and PCDD/Fs) demonstrating the robustness of these approaches.

A multicriteria decision analysis framework for developing and evaluating coastal retreat policy

Managed retreat may be a necessity for coastal communities as sea levels rise due to climate change. Selecting the right policy decisions and timing is difficult given the vested interests of communities and stakeholder groups and requires careful balancing of the benefits and risks associated with each management alternative. State and federal agencies often employ single-objective optimization frameworks such as cost-benefit analysis to analyze coastal relocation alternatives, but such methods are limited in their ability to balance competing value considerations and stakeholder demands. The use of a multicriteria decision analysis (MCDA) methodology allows for such considerations to be quantified and evaluated, thereby improving planning and decision-making for coastal retreat policies. This paper provides a strategic MCDA framework to evaluate coastal retreat policy that could be leveraged by at-risk coastal communities. The MCDA is applied to a hypothetical coastal retreat scenario to visualize policy preferences and differing value considerations among stakeholders. This model can be used by government agencies to foster more sound, acceptable, and implementable coastal retreat policies and streamline the incorporation of this climate adaptation mechanism, which may be necessary for the near future. Integr Environ Assess Manag 2023;19:83-98. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Energy efficiency in residential buildings amid COVID-19: A holistic comparative analysis between old and new normal occupancies

Stringent lockdowns have been one of the defining features of the COVID-19 pandemic. Lockdowns have brought about drastic changes in living styles, including increased residential occupancy and telework practices predicted to last long. The variation in occupancy pattern and energy use needs to be assessed at the household level. Consequently, the new occupancy times will impact the performance of energy efficiency measures. To address these gaps, this work uses a real case study, a two-story residential building in the Okanagan Valley (British Columbia, Canada). Further, steady-state building energy simulations are performed on the HOT2000 tool to evaluate the resiliency of energy efficiency measures under a full lockdown. Three-year monitored energy data is analyzed to study the implications of COVID-19 lockdowns on HVAC and non-HVAC loads at a monthly temporal scale. The results show a marked change in energy use patterns and a higher increase in May 2020 compared to the previous two years. Calibrated energy models built on HOT2000 are then used to study the impacts of pre-COVID-19 (old normal occupancy) and post-COVID-19 (new normal occupancy) on energy upgrades performance. The simulations show that under higher occupancy times, the annual electricity use increased by 16.4%, while natural gas use decreased by 7.6%. The results indicate that overall residential buildings following pre-COVID-19 occupancy schedules had higher energy-saving potential than those with new normal occupancy. In addition, the variation in occupancy and stakeholder preferences directly impact the ranking of energy efficiency measures. Furthermore, this study identifies energy efficiency measures that provide flexibility for the decision-makers by identifying low-cost options feasible under a range of occupancy schedules.

Delineation of groundwater potential zones at micro-spatial units of Nagaon district in Assam, India, using GIS-based MCDA and AHP techniques

Groundwater is one of the most precious natural resources in the densely populated regions of the world. The ever increasing population in the developing countries like India and the concurrent growth of industrial and urban centres along with modern agricultural systems have caused tremendous pressure on groundwater. In the present day context of groundwater depletion and degradation, it is necessary to identify and map the groundwater potential zones (GWPZs) of an area to manage and utilize them sustainably. The present study is, therefore, an attempt to employ the GIS-based multi-criteria decision analysis (MCDA) and analytical hierarchy process (AHP) techniques to derive the GWPZs in Nagaon district of the middle Brahmaputra valley agro-climatic region of Assam, India. Here, ten multi-influencing groundwater potential factors, including geology, lineament density, geomorphology, slope, soil texture, LULC, rainfall, drainage density, NDWI, and TWI are considered for the delineation of GWPZs. These criteria are assigned weightages using AHP wherein geology has been given the highest weight, followed by lineament density and the others. Based on these techniques, the GWPZs of the district are classified into four zones, namely, low, moderate, high, and very high which include 20, 301, 218, and 392 villages, respectively. The results are validated with the groundwater levels of 28 tube wells and 5 ring wells distributed throughout the district, and as such, an area under the curve value of 86.9% is found. The results, thus, validated imply that the methodology adopted in deriving the GWPZs is highly reliable, which can help in sustainable utilization, development, and management of groundwater resources in the district. Besides, the identification and mapping of village-wise GWPZs are very essential for the planning of water resource management and water risks mitigation which ultimately help in sustainable rural development.

Fetoscopic laser surgery for twin-to-twin transfusion syndrome in DCTA triplets compared to MCDA twins: collaborative study and literature review

OBJECTIVE

To compare the outcomes of dichorionic triamniotic (DCTA) triplets with that of monochorionic diamniotic (MCDA) twin gestations undergoing fetoscopic laser surgery (FLS) for treatment of twin-to-twin transfusion syndrome (TTTS).

METHODS

Retrospective cohort study of prospectively collected data of consecutive DCTA triplet and MCDA twin pregnancies with TTTS that underwent FLS at two fetal treatment centers between 2012 and 2020. Preoperative, operative and, postoperative variables were collected. Perinatal outcomes were investigated. Primary outcome was survival to birth and to neonatal period. Secondary outcomes were gestational age (GA) at birth and procedure-to-delivery interval. Literature review was conducted in which PubMed, Web of Science, and Scopus were searched from inception to September, 2020.

RESULTS

Twenty four sets of DCTA triplets were compared to MCDA twins during the study period. There were no significant differences in survival (no survivor, single, or double survivors) to birth and to the neonatal period of the MC twin pairs of the DCTA triplets vs MCDA twins. Median GA at delivery was approximately three weeks earlier in DCTA triplets compared to MCDA twins (28.4 weeks vs 31.4 weeks, p = .035, respectively). Rates of preterm birth (PTB) less than 32 and less than 28 weeks were significantly higher in DCTA triplets compared to twins (<32 weeks: 70.8% vs 51.1%, p = .037, respectively, and <28 weeks: 37.5% vs 20.8%, p = .033, respectively).

CONCLUSION

Perinatal survival including fetal and neonatal are comparable between DCTA triplets and MCDA twins. However, this might have resulted from the small sample size of the DCTA triplets. GA at delivery is earlier in triplets, which could be due to the nature of triplet gestation rather than to the laser procedure itself.

Combining multi-criteria decision analysis with GIS approaches for decentralized organic wastes composting plants site selection in Tiassalé, Southern Côte d'Ivoire

In recent years, decentralized composting appeared as one of the most appropriate treatment options for organic waste valorization in low- and middle-income countries. In Cote d'Ivoire, a pilot project has proved the feasibility of organic municipal solid waste composting for the city of Tiassalé. However, numerous issues still need to be addressed for the establishment of a sustainable decentralized composting system in this city. One of the key issues is site selection. Until now, there is no clear model for such plant site selection. In this study, multi-criteria decision analysis (MCDA) and geographical information system (GIS) approaches were combined to develop an appropriate model for selecting decentralized composting sites in the city of Tiassalé. The methodology used involved two different and complementary phases. First, MCDA and GIS techniques were used to identify the most suitable site areas. Seven criteria clustered in three main factors (environmental, social and economic), and five constraints were considered in the analysis process. Second, five sites were selected within the most suitable areas after a basic field visit and ranked using the Analytic Hierarchy Process. The results showed that the most suitable spaces for decentralized composting plant siting represent only 2.6% of the study area. The investigation yielded on the selection of the two best options for decentralized composting plant siting for the city of Tiassalé. This study proved that the combination of MCDA and GIS is a practical and efficient method to identify suitable sites for decentralized composting plants.

Model to support intervention prioritization for the control of Aedes aegypti in Brazil: a multi-criteria approach

Background

Despite continuous strategic investments to mitigate the complexity involving arboviruses control, it is still necessary to further research methods and techniques to achieve in depth knowledge and shorter response times in the application of intervention activities. Consequently, the current work focused its efforts on the development of a multicriteria decision support model for the prioritization of prompt response activities for Aedes aegypti control, based on a case study in the city of Natal/RN.

Method

The research was carried out in three stages: a) preliminary; b) modelling and choice; and c) finalization; the second stage was made possible by the Flexible and Interactive Tradeoff (FITradeoff) method for ranking problematic. Furthermore, the research encompassed ten actors who were involved in the model construction, eight internal and two external to the Natal Zoonoses Control Center (ZCC-Natal) as well as the observation of four operating scenarios for arboviruses control, based on transmission levels; and, evaluation of eleven alternatives from six different criteria perspectives.

Results

Rankings of the interventions evaluated in each of the four control operation scenarios present in the city of Natal/RN were obtained, considering technical criteria guided by the Pan American Health Organization (PAHO).

Conclusions

As a result, it was developed a structured decision-making model that could help decision makers to minimize the effects and risks associated with the proliferation of the vector.

Use of the incremental cost-effectiveness ratio for decision-making policies-what is the problem? A perspective paper

INTRODUCTION

Drug reimbursement decisions that spark public controversy are potential signals that processes used to reach such decisions do not adequately reflect society's goals. Such controversial decisions appear to be a characteristic of Quality-Adjusted Life Year (QALY)-based Incremental Cost Effectiveness Ratio (ICER)-dominated decision-making systems. QALY-based ICER-heavy systems have several known weaknesses that lead to individual and societal preferences being either ignored or considered in an unsystematic and inconsistent manner.

AREAS COVERED

We reprise some of the key inadequacies of QALY-based ICER analyses and suggest that there are other means including multicriteria decision analysis (MCDA) and cost-benefit analysis based on willingness to pay (WTP) measures by which to partially mitigate these weaknesses.

EXPERT OPINION

For long, the inadequacies of QALY-based ICER-heavy decision-making systems have been rationalized with the answer: 'while the method is a second best, it is the best we currently have.' In light of the equally well-developed and widely utilized alternatives available, this resistance to improve assessment processes should not be accepted by policy makers. Health technology assessment bodies should consider and, with appropriate modifications, adopt these alternatives as they have the potential to result in more comprehensive, systematic, and accountable decision-making.

Assessing the value contribution of bimekizumab for the treatment of moderate-to-severe psoriasis using a multidisciplinary reflective multi-criteria decision analysis

BACKGROUND

Multi-criteria decision analysis (MCDA) was proposed to surmount arbitrary clinical decisions in the field of biological therapies for psoriatic patients. At the same time, MCDA may further highlight the potential of bimekizumab for the treatment of moderate-to-severe psoriasis, compared to placebo, adalimumab, ustekinumab, secukinumab, and even ixekizumab and risankizumab.

RESEARCH DESIGN AND METHODS

The EVIDEM framework was adapted to reflect relevant criteria for the assessment. Estimated values were obtained by means of an additive linear model combining weights and scores assigned by a multidisciplinary committee of 12 experts. Consistency and replicability were evaluated through an alternative weighting method and a re-test.

RESULTS

Bimekizumab was assessed by the committee as an intervention with a positive value contribution for the treatment of moderate-to-severe psoriasis in comparison to any of the alternatives. The drug provides a substantial therapeutical benefits and improves the health results reported by the patients, as it combines a higher level of clearance, rapidity, and persistence with a similar safety and tolerability profile.

CONCLUSIONS

Under a methodology with increasing use in the health field, bimekizumab was evaluated as a drug with a high added value for the treatment of moderate-to-severe psoriasis when compared to six different alternatives.

A multicriteria decision analysis framework to measure equitable healthcare access during COVID-19

The ongoing novel coronavirus (COVID-19) pandemic has highlighted the need for individuals to have easy access to healthcare facilities for treatment as well as vaccinations. The surge in COVID-19 hospitalizations during 2020 also underscored the fact that accessibility to nearby hospitals for testing, treatment and vaccination sites is crucial for patients with fever or respiratory symptoms. Although necessary, quantifying healthcare access is challenging as it depends on a complex interaction between underlying socioeconomic and physical factors. In this case study, we deployed a Multi Criteria Decision Analysis (MCDA) approach to uncover the barriers and their effect on healthcare access. Using a least cost path (LCP) analysis we quantified the costs associated with healthcare access from each census block group in the Los Angeles metropolitan area (LA Metro) to the nearest hospital. Social vulnerability reported by the Centers for Disease Control and Prevention (CDC), the daily number of COVID-19 cases from the Los Angeles open data portal and built environment characteristics (slope of the street, car ownership, population density distribution, walkability, traffic collision density, and speed limit) were used to quantify overall accessibility index for the entire study area. Our results showed that the census block groups with a social vulnerability index above 0.75 (high vulnerability) had low accessibility owing to the higher cost of access to nearby hospitals. These areas were also coincident with the hotspots for COVID-19 cases and deaths which highlighted the inequitable exposure of socially disadvantaged populations to COVID-19 infections and how the pandemic impacts were exacerbated by the synergistic effect of socioeconomic status and built environment characteristics of the locations where the disadvantaged populations resided. The framework proposed herein could be adapted to geo-target testing/vaccination sites and improve accessibility to healthcare facilities in general and more specifically among the socially vulnerable populations residing in urban areas to reduce their overall health risks during future pandemic outbreaks.

Early Access to Medicines: Use of Multicriteria Decision Analysis (MCDA) as a Decision Tool in Catalonia (Spain)

Early access to medicines allows the prescription of a medicine before it is available in the public formulary to patients with severe or rare diseases with high unmet needs who have no authorised therapeutic alternatives available. In this context, consistent decision making is difficult, and a systematic assessment procedure could be useful to tackle complex situations and guarantee the equity of medicines’ access. A multidisciplinary panel (MP) conducted four workshops to develop an early access framework based on a reflective multiple criteria decision analysis (MCDA). A set of 12 criteria was agreed: eight quantitative (severity of disease, urgency, efficacy, safety, internal and external validity, therapeutic benefit and plausibility) and four qualitative (therapeutic alternative, existence of precedents, management impact and costs). Quantitative criteria were weighted using a five-point scale. The relative importance of quantitative criteria had mean weights from 4.7 to 3.6, showing its relevance in the decisions. The framework was tested using two case studies, and reliability was assessed by re-test. The re-test revealed no statistical differences, indicating the consistency and replicability of the framework developed. MCDA may help to structure discussions for heterogeneous treatment requests, providing predictability and robustness in decision making involving sensitive and complex situations.

Priority setting of vaccine introduction in Bangladesh: a multicriteria decision analysis study

OBJECTIVE

To prioritise vaccines for introduction in Bangladesh.

METHODS

Multicriteria decision analysis (MCDA) process was used to prioritise potential vaccines for introduction in Bangladesh. A set of criteria were identified, weighted and assigned scores by relevant stakeholders (n=14) during workshop A. The performance matrix of the data of vaccines against the criteria set was constructed and validated with the experts (n=6) in workshop B. The vaccines were ranked and appraised by another group of stakeholders (n=10) in workshop C, and the final workshop D involved the dissemination of the findings to decision-makers (n=28).

RESULTS

Five criteria including incidence rate, case fatality rate, vaccine efficacy, size of the population at risk and type of population at risk were used quantitatively to evaluate and to score the vaccines. Two other criteria, cost-effectiveness and outbreak potentiality, were considered qualitatively. On deliberation, the Japanese encephalitis (JE) vaccine was ranked top to be recommended for introduction in Bangladesh.

CONCLUSIONS

Based on the MCDA results, JE vaccine is planned to be recommended to the decision-makers for introduction into the national vaccine benefit package. The policymakers support the use of systematic evidence-based decision-making processes such as MCDA for vaccine introduction in Bangladesh, and to prioritise health interventions in the country.

Multiple Cross Displacement Amplification Combined With Real-Time Polymerase Chain Reaction Platform: A Rapid, Sensitive Method to Detect Mycobacterium tuberculosis

In this study, we evaluated the diagnostic accuracy of multiple cross displacement amplification (MCDA) combined with real-time PCR platform in pulmonary tuberculosis (PTB) patients. Total 228 PTB patients and 141 non-TB cases were enrolled. Based on the analysis of the first available sample of all participants, MCDA assay showed a higher overall sensitivity (64.0%), with a difference of more than 10% compared with Xpert MTB/RIF (Xpert) assay (51.8%, P < 0.05) and combined liquid and solid culture (47.8%, P < 0.001) for PTB diagnosis. In particular, MCDA assay detected 31 probable TB patients, which notably increased the percentage of confirmed TB from 57.9% (132/228) to 71.5% (163/228). The specificities of microscopy, culture, Xpert and MCDA assay were 100% (141/141), 100% (141/141), 100% (141/141), and 98.6% (139/141), respectively. Among the patients with multiple samples, per patient sensitivity of MCDA assay was 60.5% (52/86) when only the first available sputum sample was taken into account, and the sensitivity increased to 75.6% (65/86) when all samples tested by MCDA assay were included into the analysis. Therefore, MCDA assay established in this study is rapid, accurate and affordable, which has the potential in assisting the accurate and rapid diagnosis of PTB and speed up initiation of TB treatment in settings equipped with real-time PCR platform.

A practical approach for geographic prioritization and targeting of insecticide-treated net distribution campaigns during public health emergencies and in resource-limited settings

BACKGROUND

The use of data in targeting malaria control efforts is essential for optimal use of resources. This work provides a practical mechanism for prioritizing geographic areas for insecticide-treated net (ITN) distribution campaigns in settings with limited resources.

METHODS

A GIS-based weighted approach was adopted to categorize and rank administrative units based on data that can be applied in various country contexts where Plasmodium falciparum transmission is reported. Malaria intervention and risk factors were used to rank local government areas (LGAs) in Nigeria for prioritization during mass ITN distribution campaigns. Each factor was assigned a unique weight that was obtained through application of the analytic hierarchy process (AHP). The weight was then multiplied by a value based on natural groupings inherent in the data, or the presence or absence of a given intervention. Risk scores for each factor were then summated to generate a composite unique risk score for each LGA. This risk score was translated into a prioritization map which ranks each LGA from low to high priority in terms of timing of ITN distributions.

RESULTS

A case study using data from Nigeria showed that a major component that influenced the prioritization scheme was ITN access. Sensitivity analysis results indicate that changes to the methodology used to quantify ITN access did not modify outputs substantially. Some 120 LGAs were categorized as 'extremely high' or 'high' priority when a spatially interpolated ITN access layer was used. When prioritization scores were calculated using DHS-reported state level ITN access, 108 (90.0%) of the 120 LGAs were also categorized as being extremely high or high priority. The geospatial heterogeneity found among input risk factors suggests that a range of variables and covariates should be considered when using data to inform ITN distributions.

CONCLUSION

The authors provide a tool for prioritizing regions in terms of timing of ITN distributions. It serves as a base upon which a wider range of vector control interventions could be targeted. Its value added can be found in its potential for application in multiple country contexts, expediated timeframe for producing outputs, and its use of systematically collected malaria indicators in informing prioritization.

Multicriteria decision analysis in health care decision in oncology: a systematic review

INTRODUCTION

Multicriteria decision analysis (MCDA) has been used to inform health decisions in health technology assessments (HTA) processes. This is particularly important to complex treatment decisions in oncology.

AREAS COVERED

Five databases (PubMed, EMBASE, LILACS, Web of Science and CRD's NHS Economic Evaluation Database) were searched for studies comparing health technologies in oncology, involving the concept MCDA. The ISPOR MCDA Good Practices Guidelines were used to assess the reporting quality. Study selection, appraisal, and data extraction were performed by two reviewers. Fifteen studies were included. The main decision problem was related to health technology assessment of cancer treatments. Clinicians and public health experts were the most frequent stakeholders. The most frequently included criteria comprised therapeutic benefit, and socio-economic impact. Value measurement approach, direct rating techniques, and additive model for aggregation were used in most studies. Uncertainty analysis revealed the impact of posology and costs on the studies' results. All studies showed some level of overlapping decision criteria.

EXPERT OPINION

There is considerable diversity of methods in MCDA for healthcare decision-making in oncology. The evidence presented can serve as a resource when considering which stakeholders, criteria, and techniques to include in future MCDA studies in oncology.

Safety of Dietary Guanidinoacetic Acid: A Villain of a Good Guy?

Guanidinoacetic acid (GAA) is a natural amino acid derivative that is well-recognized for its central role in the biosynthesis of creatine, an essential compound involved in cellular energy metabolism. GAA (also known as glycocyamine or betacyamine) has been investigated as an energy-boosting dietary supplement in humans for more than 70 years. GAA is suggested to effectively increase low levels of tissue creatine and improve clinical features of cardiometabolic and neurological diseases, with GAA often outcompeting traditional bioenergetics agents in maintaining ATP status during stress. This perhaps happens due to a favorable delivery of GAA through specific membrane transporters (such as SLC6A6 and SLC6A13), previously dismissed as un-targetable carriers by other therapeutics, including creatine. The promising effects of dietary GAA might be countered by side-effects and possible toxicity. Animal studies reported neurotoxic and pro-oxidant effects of GAA accumulation, with exogenous GAA also appearing to increase methylation demand and circulating homocysteine, implying a possible metabolic burden of GAA intervention. This mini-review summarizes GAA toxicity evidence in human nutrition and outlines functional GAA safety through benefit-risk assessment and multi-criteria decision analysis.

New Pythagorean Entropy Measure with Application in Multi-Criteria Decision Analysis

The purpose of this paper is to propose a new Pythagorean fuzzy entropy for Pythagorean fuzzy sets, which is a continuation of the Pythagorean fuzzy entropy of intuitionistic sets. The Pythagorean fuzzy set continues the intuitionistic fuzzy set with the additional advantage that it is well equipped to overcome its imperfections. Its entropy determines the quantity of information in the Pythagorean fuzzy set. Thus, the proposed entropy provides a new flexible tool that is particularly useful in complex multi-criteria problems where uncertain data and inaccurate information are considered. The performance of the introduced method is illustrated in a real-life case study, including a multi-criteria company selection problem. In this example, we provide a numerical illustration to distinguish the entropy measure proposed from some existing entropies used for Pythagorean fuzzy sets and intuitionistic fuzzy sets. Statistical illustrations show that the proposed entropy measures are reliable for demonstrating the degree of fuzziness of both Pythagorean fuzzy set (PFS) and intuitionistic fuzzy sets (IFS). In addition, a multi-criteria decision-making method complex proportional assessment (COPRAS) was also proposed with weights calculated based on the proposed new entropy measure. Finally, to validate the reliability of the results obtained using the proposed entropy, a comparative analysis was performed with a set of carefully selected reference methods containing other generally used entropy measurement methods. The illustrated numerical example proves that the calculation results of the proposed new method are similar to those of several other up-to-date methods.

Multicriteria Decision Analysis and Grouping of Analytical Procedures for Phthalates Determination in Disposable Baby Diapers

This study presents the application of one of the tools from the multicriteria decision analysis set (MCDA), the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Selected green analytical chemistry metrics were used to rank analytical procedures for the phthalate determination in disposable baby diapers. Nine analytical procedures were assessed in order to find one that has the lowest environmental impact and the best analytical figures of merit. Nine different criteria, where weighting was based on the experts’ evaluation, were used in the procedures’ assessment. With the use of TOPSIS, an easy and straightforward technique, selection of the most appropriate procedure was made.

GIS-based COVID-19 vulnerability mapping in the West Bank, Palestine

From the beginning of the COVID-19 pandemic, the world stands idly by in the face of the virus spreading. The prediction of highly vulnerable population and the implementation of proper actions are very important steps to break the infection chain of any virus. This will, in turn, reduce the economic and social impact of this virus outbreak. In this study, the COVID-19 vulnerability map for the West Bank, Palestine was developed. Analytic Hierarchy Process (AHP) was used to develop the COVID-19 vulnerability map. The Geographic Information system (GIS) in combination with multi-criteria decision analysis (MCDA) was adopted to estimate the COVID-19 vulnerability index (CVI) based on some selected potential criteria including population, population density, elderly population, accommodation and food service activities, school students, chronic diseases, hospital beds, health insurance, and pharmacy. The results of this study show that Nablus, Jerusalem, and Hebron governorates are under very high vulnerability. Tulkarm, Ramallah & Al-Bireh and Jenin governorates are high vulnerable to COVID-19. Additionally, 82 % of the West Bank population are under high to very high COVID-19 vulnerability classes. Moreover, 14% and 4 % are medium and low to very low vulnerable, respectively. The obtained results are of high value to help decision-makers to take proper actions as early as possible mainly in the highly COVID-19 vulnerable governorates to control the risk associated with the potential outbreak of the virus and accordingly to protect social life and to sustain economic conditions.

The CAPACITI Decision-Support Tool for National Immunization Programs

OBJECTIVES

Immunization programs in low-income and middle-income countries (LMICs) are faced with an ever-growing number of vaccines of public health importance recommended by the World Health Organization, while also financing a greater proportion of the program through domestic resources. More than ever, national immunization programs must be equipped to contextualize global guidance and make choices that are best suited to their setting. The CAPACITI decision-support tool has been developed in collaboration with national immunization program decision makers in LMICs to structure and document an evidence-based, context-specific process for prioritizing or selecting among multiple vaccination products, services, or strategies.

METHODS

The CAPACITI decision-support tool is based on multi-criteria decision analysis, as a structured way to incorporate multiple sources of evidence and stakeholder perspectives. The tool has been developed iteratively in consultation with 12 countries across Africa, Asia, and the Americas.

RESULTS

The tool is flexible to existing country processes and can follow any type of multi-criteria decision analysis or a hybrid approach. It is structured into 5 sections: decision question, criteria for decision making, evidence assessment, appraisal, and recommendation. The Excel-based tool guides the user through the steps and document discussions in a transparent manner, with an emphasis on stakeholder engagement and country ownership.

CONCLUSIONS

Pilot countries valued the CAPACITI decision-support tool as a means to consider multiple criteria and stakeholder perspectives and to evaluate trade-offs and the impact of data quality. With use, it is expected that LMICs will tailor steps to their context and streamline the tool for decision making.

A framework for designing medical devices resilient to low-resource settings

Background

To date (April 2021), medical device (MD) design approaches have failed to consider the contexts where MDs can be operationalised. Although most of the global population lives and is treated in Low- and Middle-Income Countries (LMCIs), over 80% of the MD market share is in high-resource settings, which set de facto standards that cannot be taken for granted in lower resource settings. Using a MD designed for high-resource settings in LMICs may hinder its safe and efficient operationalisation. In the literature, many criteria for frameworks to support resilient MD design were presented. However, since the available criteria (as of 2021) are far from being consensual and comprehensive, the aim of this study is to raise awareness about such challenges and to scope experts’ consensus regarding the essentiality of MD design criteria.

Results

This paper presents a novel application of Delphi study and Multiple Criteria Decision Analysis (MCDA) to develop a framework comprising 26 essential criteria, which were evaluated and chosen by international experts coming from different parts of the world. This framework was validated by analysing some MDs presented in the WHO Compendium of innovative health technologies for low-resource settings.

Conclusions

This novel holistic framework takes into account some domains that are usually underestimated by MDs designers. For this reason, it can be used by experts designing MDs resilient to low-resource settings and it can also assist policymakers and non-governmental organisations in shaping the future of global healthcare.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12992-021-00718-z.

Case studies for implementing MCDA for tender and purchasing decisions in hospitals in Indonesia and Thailand

Background

A multi-criteria decision analysis (MCDA) approach has been suggested for helping purchasers in low- and middle-income countries in an evidence-based assessment of multi-source pharmaceuticals to mitigate potential adverse consequences of price-based decisions on patient access to effective medicines. Six workshops for developing MCDA-instruments for purchasing were conducted in Indonesia, Kazakhstan, Thailand, and Kuwait in 2017–2020. In Indonesia and Thailand, two pilot-initiatives aimed to implement the instruments for hospital drug purchasing decisions.

Objective

By analysing and comparing the experiences and progress from the MCDA-workshops and the two case-examples for hospital implementation in Indonesia and Thailand, we aim to gain insights, which will support future implementation.

Methods

The selection of criteria and their average weight were compared quantitatively across the MCDA-instruments developed in all four countries and settings. Implementation experiences from two case-examples were studied, which included (1) testing the instrument across a variety of drugs in seven hospitals in Thailand and (2) implementation in one specialty hospital in Indonesia. Semi-structured interviews were conducted via web-conferences with four diverse stakeholders in the pilot implementation projects in Thailand and Indonesia. The open responses were evaluated through qualitative content analysis and synthesis using grounded theory coding.

Results

Drivers for implementation were making ‘better’ decisions, achieving transparency and a rational selection process, reducing drug shortages, and assuring consistent quality. Challenges were seen on the technical level (definition or of criteria, scoring methods, access to data) or change-related challenges (resistance, perception of increased workload, lack of competencies or capabilities, lack of resources). The comparison of the MCDA instruments revealed high similarity, but also clear need for local adaptations in each specific case.

Conclusion

A set a of measures targeting challenges related to utility, methodology, data requirements, capacity building and training as well as the broader societal impact can help to overcome challenges in the implementation. Careful planning of implementation and organizational change is recommended for ensuring commitment and fit to local context and culture. Designing a collaborative change program for each application of MCDA-based purchasing will enable healthcare stakeholders to maximally benefit in terms of quality and effectiveness of care and access for patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40545-021-00333-8.

A framework for the evaluation and selection of shoreline surface washing agents in oil spill response

The shorelines frequently suffer adverse impacts from oil spill accidents. As one important technique of shoreline cleanup, the application of surface washing agents (SWAs) can help achieve high oil removal from shoreline substrates with less damage to affected zone. In this study, a framework for evaluation and selection of SWAs in oil spill incidents was constructed to better understand and apply this technique. A decision tree was firstly developed to illustrate all possible scenarios which are appropriate to use SWAs in consideration of oil collectability, shoreline character, types and amount of stranded oil, and cleanup requirement. Based on literature review, theoretical modeling, and experts' suggestions, an integrated multi-criteria decision analysis (MCDA) method was then come up to select the most preferred SWA from five aspects of toxicity, effectiveness, minimal dispersion, demonstrated field test, and cost. Its suitability and rationality were proved by a hypothetical case. In addition, sensitivity analysis was performed by changing the weight of each criterion independently to check the priority rank of alternatives, and it also verified the robustness and stability of this model. The presented framework has significant implications for future research and application of SWAs in the shoreline cleanup.

Developing a new national MDMA policy: Results of a multi-decision multi-criterion decision analysis

BACKGROUND

Ecstasy (3,4-methylenedioxymethamphetamine (MDMA)) has a relatively low harm and low dependence liability but is scheduled on List I of the Dutch Opium Act ('hard drugs'). Concerns surrounding increasing MDMA-related criminality coupled with the possibly inappropriate scheduling of MDMA initiated a debate to revise the current Dutch ecstasy policy.

METHODS

An interdisciplinary group of 18 experts on health, social harms and drug criminality and law enforcement reformulated the science-based Dutch MDMA policy using multi-decision multi-criterion decision analysis (MD-MCDA). The experts collectively formulated policy instruments and rated their effects on 25 outcome criteria, including health, criminality, law enforcement and financial issues, thematically grouped in six clusters.

RESULTS

The experts scored the effect of 22 policy instruments, each with between two and seven different mutually exclusive options, on 25 outcome criteria. The optimal policy model was defined by the set of 22 policy instrument options which gave the highest overall score on the 25 outcome criteria. Implementation of the optimal policy model, including regulated MDMA sales, decreases health harms, MDMA-related organised crime and environmental damage, as well as increases state revenues and quality of MDMA products and user information. This model was slightly modified to increase its political feasibility. Sensitivity analyses showed that the outcomes of the current MD-MCDA are robust and independent of variability in weight values.

CONCLUSION

The present results provide a feasible and realistic set of policy instrument options to revise the legislation towards a rational MDMA policy that is likely to reduce both adverse (public) health risks and MDMA-related criminal burden.

Exploring physicians and patients' perspectives for current interventions on thyroid nodules using a MCDA method

BACKGROUND

The detection of thyroid cancer has rapidly increased over last few decades without an increase in disease specific mortality. Several studies claim that the diagnose of thyroid nodules through routine ultrasound imaging is often the trigger for cascade effects leading to unnecessary follow-up over many years or to invasive treatment. The objective of this study was to explore physicians' and patients' insights and preferences regarding the current interventions on thyroid nodules.

METHODS

An online survey was developed using a comprehensive multi-criteria decision analysis (MCDA) framework, the EVIdence based Decision-Making (EVIDEM). The EVIDEM core model used in this study encompassed 13 quantitative criteria and four qualitative criteria. Participants were asked to provide weights referring to what matters most important in general for each criterion, performance scores for appraising the interventions on thyroid nodules and their consideration of impact of contextual criteria. Normalized weights and standardized scores were combined to calculate a value contribution across all participants, additionally differences across physicians and patients' group were explored.

RESULTS

48 patients and 31 physicians were included in the analysis. The value estimate of the interventions on thyroid nodules reached 0.549 for patients' group and 0.5 was reported by the physicians' group, compared to 0.543 for all participants. The highest value contributor was 'Comparative effectiveness' (0.073 ± 0.020). For the physicians' group, 'Comparative safety' (0.050 ± 0.023) was given with higher value. And for the patients' group, 'Type of preventive benefits' (0.059 ± 0.022) contributed more positively to the value estimation. 51% participants considered 'Population priorities and access' having a negative impact on the interventions of nodules.66% participants thought that the 'system capacity' had a negative impact.

CONCLUSION

Our study shows participants' preferences on each criterion, i.e., physician indicated keeping the interventions safe and effective more important, patients indicated quality of life after receiving interventions more important. Through comparison among participants, differences have been highlighted, which can make better communication between physicians and patients. This study provides a supportive decision-making for healthcare providers when they explored the interventions on thyroid nodules.

Development and Practical Application of a Multiple-Criteria Decision Analysis Framework on Respiratory Inhalers: Is It Always Useful in the MOH Malaysia Medicines Formulary Listing Context?

Objectives. The current health technology assessment used to evaluate respiratory inhalers is associated with limitations that have necessitated the development of an explicit formulary decision-making framework to ensure balance between the accessibility, value, and affordability of medicines. This study aimed to develop a multiple-criteria decision analysis (MCDA) framework, apply the framework to potential and currently listed respiratory inhalers in the Ministry of Health Medicines Formulary (MOHMF), and analyze the impacts of applying the outputs, from the perspective of listing and delisting medicines in the formulary. Methods. The overall methodology of the framework development adhered to the recommendations of the ISPOR MCDA Emerging Good Practices Task Force. The MCDA framework was developed using Microsoft Excel 2010 and involved all relevant stakeholders. The framework was then applied to 27 medicines, based on data gathered from the highest levels of available published evidence, pharmaceutical companies, and professional opinions. The performance scores were analyzed using the additive model. The end values were then deliberated by an expert committee. Results. A total of eight main criteria and seven subcriteria were determined by the stakeholders. The economic criterion was weighted at 30%. Among the noneconomic criteria, "patient suitability" was weighted the highest. Based on the MCDA outputs, the expert committee recommended one potential medicine (out of three; 33%) be added to the MOHMF and one existing medicine (out of 24; 4%) be removed/delisted from the MOHMF. The other existing medicines remained unchanged. Conclusions. Although this framework was useful for deciding to add new medicines to the formulary, it appears to be less functional and impactful for the removal/delisting existing medicines from the MOHMF. The generalizability of this conclusion to other formulations remains to be confirmed.

A Multicriteria Decision Analysis Comparing Pharmacotherapy for Chronic Neuropathic Pain, Including Cannabinoids and Cannabis-Based Medical Products

Background:

Pharmacological management of chronic neuropathic pain (CNP) still represents a major clinical challenge. Collective harnessing of both the scientific evidence base and clinical experience (of clinicians and patients) can play a key role in informing treatment pathways and contribute to the debate on specific treatments (e.g., cannabinoids). A group of expert clinicians (pain specialists and psychiatrists), scientists, and patient representatives convened to assess the relative benefit–safety balance of 12 pharmacological treatments, including orally administered cannabinoids/cannabis-based medicinal products, for the treatment of CNP in adults.

Methods:

A decision conference provided the process of creating a multicriteria decision analysis (MCDA) model, in which the group collectively scored the drugs on 17 effect criteria relevant to benefits and safety and then weighted the criteria for their clinical relevance.

Findings:

Cannabis-based medicinal products consisting of tetrahydrocannabinol/cannabidiol (THC/CBD), in a 1:1 ratio, achieved the highest overall score, 79 (out of 100), followed by CBD dominant at 75, then THC dominant at 72. Duloxetine and the gabapentinoids scored in the 60s, amitriptyline, tramadol, and ibuprofen in the 50s, methadone and oxycodone in the 40s, and morphine and fentanyl in the 30s. Sensitivity analyses showed that even if the pain reduction and quality-of-life scores for THC/CBD and THC are halved, their benefit–safety balances remain better than those of the noncannabinoid drugs.

Interpretation:

The benefit–safety profiles for cannabinoids were higher than for other commonly used medications for CNP largely because they contribute more to quality of life and have a more favorable side effect profile. The results also reflect the shortcomings of alternative pharmacological treatments with respect to safety and mitigation of neuropathic pain symptoms. Further high-quality clinical trials and systematic comprehensive capture of clinical experience with cannabinoids is warranted. These results demonstrate once again the complexity and multimodal mechanisms underlying the clinical experience and impact of chronic pain.

Facilitating the Decision-Making Process After a Nuclear Accident: Case Studies in the Netherlands and Slovakia

Nuclear accidents do not occur frequently, but their biological, psychosocial, and/or economic consequences may be severe. Hence, a thorough preparation for nuclear emergencies is needed to provide appropriate actions. During the transition phase of an accident, it is vital to include stakeholders in the decision-making process in order to gain support for the recovery strategy to be implemented as well as to share different perspectives, knowledge, and views on the decision problem. Because nuclear accidents are complex, involving many relevant factors that range from technical aspects such as health effects and costs to nontechnical issues such as social acceptance, a multicriteria decision analysis (MCDA) may facilitate the decision-making process. The aim of this study was to investigate the usefulness of MCDA in the transition phase of a nuclear accident. To this end, an MCDA tool, which uses the weighted sum of a set of normalized criteria, was explored in exercises carried out in panel meetings with a selected set of (largely) governmental stakeholders. The panel meetings were performed in the Netherlands and the Slovak Republic. The exercises were based on a fictitious case study that affected the urban environment of a small city. Prior to the meetings, a set of 8 possible recovery strategies was identified. The use of the MCDA tool showed that it facilitated the decision-making process because it allowed for a structured and transparent approach in which stakeholders with diverse backgrounds can express their opinions and perspectives and reach consensus on the most appropriate recovery strategy. As such, it could be applied to a broader field of research involving any chemical release that necessitates an extended recovery strategy. Future research is needed in order to incorporate psychosocial effects of a nuclear accident as well as a broader group of stakeholders in exercises. Integr Environ Assess Manag 2021;17:376-387. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Can We Incorporate Societal Values in Resource Allocation Decisions Among Disease Categories? An Empirical Approach

OBJECTIVES

Historically, resource allocation decisions in healthcare are based on univariate approaches, inevitably overlooking value dimensions that are essential from a societal welfare maximization perspective. This article aims to present a wider perspective on decision making that incorporates societal values when prioritizing future resource allocation among disease areas.

METHODS

Sociotechnical application of multiple-criteria decision analysis with a set of criteria (value judgments) that are based on positive as well as normative dimensions of resource allocation. We use Greece as a case study. Societal value judgments were sourced via a multidisciplinary panel of experts who collectively provided criteria weights and scores for each alternative (16 disease categories, classified according to the Global Burden of Disease study) against each criterion. An additive value function provided the total value in priority preference for each alternative.

RESULTS

The criteria that were deemed relevant to the decision-making process and their respective relative weights were burden of disease (0.245), capacity to benefit (0.190), direct cost and projected changes in the next 5 years (0.160), indirect cost (0.132), intensity of unmet needs (0.109), incidence of catastrophic expenditure (0.091), and caring externalities (0.073). The additive value function revealed that the top 5 priorities in highest total value scores were neoplasms, circulatory diseases, injuries, neurologic diseases, and musculoskeletal diseases.

CONCLUSIONS

Incorporation of societal value criteria in resource allocation decisions can highlight priorities and lead to different sets of planning decisions than solely demand-driven allocation.

Prioritisation for future surveillance, prevention and control of 98 communicable diseases in Belgium: a 2018 multi-criteria decision analysis study

Background

National public health agencies are required to prioritise infectious diseases for prevention and control. We applied the prioritisation method recommended by the European Centre for Disease Prevention and Control to rank infectious diseases, according to their relative importance for surveillance and public health, to inform future public health action in Belgium.

Methods

We applied the multi-criteria-decision-analysis approach. A working group of epidemiologists and statisticians from Belgium (n = 6) designed a balanced set of prioritisation criteria. A panel of Belgian experts (n = 80) allocated in an online survey each criteria a weight, according to perceived relative importance. Next, experts (n = 37) scored each disease against each criteria in an online survey, guided by disease-specific factsheets referring the period 2010–2016 in Belgium. The weighted sum of the criteria’s scores composed the final weighted score per disease, on which the ranking was based. Sensitivity analyses quantified the impact of eight alternative analysis scenarios on the top-20 ranked diseases. We identified criteria and diseases associated with data-gaps as those with the highest number of blank answers in the scoring survey. Principle components of the final weighted score were identified.

Results

Working groups selected 98 diseases and 18 criteria, structured in five criteria groups. The diseases ranked highest were (in order) pertussis, human immunodeficiency virus infection, hepatitis C and hepatitis B. Among the five criteria groups, overall the highest weights were assigned to ‘impact on the patient’, followed by ‘impact on public health’, while different perceptions were identified between clinicians, microbiologists and epidemiologists. Among the 18 individual criteria, ‘spreading potential’ and ‘events requiring public health action’ were assigned the highest weights. Principle components clustered with thematic disease groups. Notable data gaps were found among hospital-related diseases.

Conclusions

We ranked infectious diseases using a standardised reproducible approach. The diseases ranked highest are included in current public health programs, but additional reflection for example about needs among risk groups is recommended. Cross-reference of the obtained ranking with current programs is needed to verify whether resources and activities map priority areas. We recommend to implement this method in a recurrent evaluation cycle of national public health priorities.