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.

Preferences as fairness judgments: a critical review of normative frameworks of preference elicitation and development of an alternative based on constitutional economics.

Preference elicitation is widely used within health economic evaluations to inform coverage decisions. However, coverage decisions involve questions of social justice and it is unclear what role empirical evidence about preferences can play here. This study reviews the prevalent normative frameworks for using population-based preference elicitation and the criticisms they face, and proposes an alternative based on constitutional economics. The frameworks reviewed include a supposedly value-neutral framework of preferences as predictors of choice, preference utilitarian frameworks that aim to maximize preference satisfaction, and substantive consequentialist frameworks that aim to maximize happiness, health, or capabilities. The proposed alternative implements the idea that indices of social value are tools for conflict resolution, rather than tools for maximization. Preference elicitation is used for validating values generated by multi-criteria decision analysis results within representative processes of stakeholder deliberation.

Exploring health preference heterogeneity in the UK: Using the online elicitation of personal utility functions approach to construct EQ-5D-5L value functions on societal, group and individual level.

A new method has recently been developed for valuing health states, called 'Online elicitation of Personal Utility Functions' (OPUF). In contrast to established methods, such as time trade-off or discrete choice experiments, OPUF does not require hundreds of respondents, but allows estimating utility functions for small groups and even at the individual level. In this study, we used OPUF to elicit EQ-5D-5L health state preferences from a (not representative) sample of the UK general population, and then compared utility functions on the societal-, group-, and individual level. A demo version of the survey is available at: https://eq5d5l.me. Data from 874 respondents were included in the analysis. For each respondent, we constructed a personal EQ-5D-5L value set. These personal value sets predicted respondents' choices in three hold-out discrete choice tasks with an accuracy of 78%. Overall, preferences varied greatly between individuals. However, PERMANOVA analysis showed that demographic characteristics explained only a small proportion of the variability between subgroups. While OPUF is still under development, it has important strengths: it can be used to construct value sets for patient reported outcome instruments such as EQ-5D-5L, while also allowing examination of underlying preferences in an unprecedented level of detail. In the future, OPUF could be used to complement existing methods, allowing valuation studies in smaller samples, and providing more detailed insights into the heterogeneity of preferences across subgroups.

A holistic framework of biochar-augmented cementitious products and general applications: Technical, environmental, and economic evaluation.

In the context of the circular economy, the development of innovative and low-carbon concrete that incorporates different kinds of waste materials is gaining attention among the research community, regulatory agencies, and policymakers. These materials can be incorporated into concrete mixtures as aggregates or as fillers for improvement of product properties. This study aims to identify reliable designs for biochar-augmented cementitious products and general applications through technical, environmental, and economic assessments. The outcomes demonstrate that 5 wt% biochar addition could enhance the compressive strength of the final products. Using biochar, together with other recycled materials, can enormously reduce the environmental impacts, especially for global warming, enabling biochar-augmented cementitious products and general application as carbon-negative resources. The highest GWP reduction reached -720 kg CO2/tonne, equal to a 200% saving. A high quantity of biochar could be included in several specific applications (up to 60 wt%). The economic assessment highlights that the proposed designs are cost-effective and carbon tax can be significantly reduced. Carbon credits can also be earned for some carbon-negative designs. These findings can serve to mitigate GHG emissions and provide decision-makers with a reliable and holistic framework towards the goal of carbon neutrality.

Application of hybrid multi-criteria decision-making approach to analyze wastewater microalgae culture systems for bioenergy production.

Bioenergy generation from microalgae can significantly contribute to climate mitigation and renewable energy production. In this regard, several multi-criteria decision-making method were employed to prioritize appropriate microalgae culture system for bioenergy production. Entropy weight, Criteria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were the employed MCDA method. Fourteen microalgae culture systems were selected as a case study, which contain teen monoculture and four dual-culture. Initially, through ans in-depth review of the literature and expert views, four categories total eight indicators were selected as the evaluation indices of the study, namely 1) Proliferation: Half growth cycle and Max growth rate,2) Biomass output: Bio-crude yield and Lipid yield, 3) Nutrient utilization: residual concentration of total Nitrogen and total Phosphorus, and, 4) Stability: coefficient of variation of Bio-crude yield and Lipid yield. The result indicated that "Pediastrum sp. & Micractinium sp." was identified as the most bioenergy potential microalgae culture system, and the evaluation results of entropy weight method and CRITIC method are similar. It is pertinent to note that 1)the entropy weight method exhibits lower sample size requirements, 2) the critic method excels when dealing with larger sample sizes, and 3) the TOPSIS method necessitates the incorporation of appropriate weighting methods to ensure credible results. In the application stage, the key indicators related to cost can be further included in the evaluation indices.

Spatial multi-criteria decision analysis for the selection of sentinel regions in tick-borne disease surveillance.

BACKGROUND: The implementation of cost-effective surveillance systems is essential for tracking the emerging risk of tick-borne diseases. In Canada, where Lyme disease is a growing public health concern, a national sentinel surveillance network was designed to follow the epidemiological portrait of this tick-borne disease across the country. The surveillance network consists of sentinel regions, with active drag sampling carried out annually in all regions to assess the density of Ixodes spp. ticks and prevalence of various tick-borne pathogens in the tick population. The aim of the present study was to prioritize sentinel regions by integrating different spatial criteria relevant to the surveillance goals. METHODS: We used spatially-explicit multi-criteria decision analyses (MCDA) to map priority areas for surveillance across Canada, and to evaluate different scenarios using sensitivity analyses. Results were shared with stakeholders to support their decision making for the selection of priority areas to survey during active surveillance activities. RESULTS: Weights attributed to criteria by decision-makers were overall consistent. Sensitivity analyses showed that the population criterion had the most impact on rankings. Thirty-seven sentinel regions were identified across Canada using this systematic and transparent approach. CONCLUSION: This novel application of spatial MCDA to surveillance network design favors inclusivity of nationwide partners. We propose that such an approach can support the standardized planning of spatial design of sentinel surveillance not only for vector-borne disease BDs, but more broadly for infectious disease surveillance where spatial design is an important component.

Bottom-up formulations for the multi-criteria decision analysis of oil and gas pipeline decommissioning in the North Sea: Brent field case study.

Many Oil and Gas (O&G) fields in the North Sea have produced their economically recoverable reserves and have entered the decommissioning phase or are close to cessation of production. The subsequent O&G decommissioning process involves a range of stakeholders with specific interests and priorities. This range of inputs to the process highlights the necessity for the development of multi-criteria decision frameworks to help guide the decision-making process. This study presents bottom-up formulations for the economic, environmental, and safety risk criteria to support the multi-criteria decision analysis within the Comparative Assessment (CA) of O&G pipeline decommissioning projects in the North Sea. The approach adapts current guidelines in the O&G industry and considers a range of parameters to provide estimations for the costs, energy usage, greenhouse gas emissions, and safety risks. To verify the effectiveness of the proposed bottom-up formulations, the longest oil export pipeline in the Brent field, PL001/N0501 is selected as a case study. The numerical results revealed the consistency of the results obtained from the proposed approach with those reported in the technical documents by industry. In most cases, the formulations provide estimates with less than 10% differences for the costs, energy usage, emissions, and safety risks. Based on the proposed multi-criteria formulations, the study also presents the use of an immersive decision-making environment within a marine simulator system to help inform the decision-making process by stakeholders.

A comprehensive taxonomy for forest fire risk assessment: bridging methodological gaps and proposing future directions.

Forest fire risk assessment plays a crucial role in the environmental management of natural hazards, serving as a key tool in the prevention of forest fires and the protection of various species. As these risks continue to evolve with environmental changes, the pertinence of contemporary research in this field remains undiminished. This review constructs a comprehensive taxonomic framework for classifying the existing body of literature on forest fire risk assessment within forestry studies. The developed taxonomy categorizes existing studies into 8 primary categories and 23 subcategories, offering a structured perspective on the methodologies and focus areas prevalent in the domain. We categorize a sample of 170 articles to present recent trends and identify research gaps in forest fire risk assessment literature. The classification facilitates a critical evaluation of the current research landscape, identifying areas in need of further exploration. Particularly, our review identifies underrepresented methodologies such as optimization modeling and some advanced machine learning techniques, which present routes for future inquiry. Moreover, the review underscores the necessity for model development that is tailored to specific regional data sets but also adaptable to global data resources, striking a balance between local specificity and broad applicability. Emphasizing the dynamic nature of forest fire behavior, we advocate for models that integrate the burgeoning field of machine learning and multi-criteria decision analysis to refine predictive accuracy and operational effectiveness in fire risk assessment. This study highlights the great potential for new ideas in modeling techniques and emphasizes the need for increased collaboration among research communities to improve the effectiveness of assessing forest fire risks.

Towards circular economy indicators: Evidence from the European Union.

The European Union (EU) is moving towards sustainable development, and a key role is played by circular economy (CE) models geared towards reducing pressure on natural resources, generating jobs and fostering economic opportunities. Indicators are able to aggregate a variety of information and their use, through the use of multi-criteria decision analysis (MCDA), allows the performance of alternatives to be monitored. This work aims to calculate the performance of the EU27 in the years 2019 and 2020 according to 15 CE indicators available on Eurostat. The results of the Analytic Hierarchy process show that the greatest impact on circularity is determined by the category 'competitiveness and innovation', which together with the category 'global sustainability and resilience' accounts for two thirds of the overall weight. The MCDA results show that Belgium prevails in both the baseline and alternative scenarios, ahead of Italy and the Netherlands respectively. In general, circular policies see western European countries excel, while the performance of eastern European countries is weaker. The implications of this work highlight the three main barriers to the development of CE models: (i) illegal waste management; (ii) lack of knowledge and low level of investment in circular technologies and (iii) low distribution of value among stakeholders. In this way, resource management based on circularity will enable Europe to meet the challenges of sustainability with less dependence on imported raw materials.

[Clinical comprehensive evaluation of Houyanqing Oral Liquid in treatment of acute pharyngitis].

This study systematically combed the existing evidence of Houyanqing Oral Liquid in the treatment of acute pharyngitis from the "6+1" dimensions of safety, effectiveness, economy, innovation, suitability, accessibility, and characteristics of traditional Chinese medicine(TCM) and carried out qualitative and quantitative analysis of the data from each dimension. The multi-criteria decision analysis(MCDA) model and CSC v2.0 were used to evaluate the clinical value of this drug, so as to provide evidence for the selection of essential drugs in the department of otolaryngology and for medical and health decision-making. The dimensions are graded A, B, C, or D. The adverse reactions of Houyanqing Oral Liquid in the treatment of acute pharyngitis were mainly manifested as abdominal pain, diarrhea, rash, etc., which were relieved after drug withdrawal. In terms of safety, it was considered that Houyanqing Oral Liquid had controllable risk and high safety, which was rated as grade B. Compared with ribavirin aerosol alone, Houyanqing Oral Liquid combined with ribavirin aerosol can significantly improve the total response rate, shorten the time to abatement of fever and di-sappearance of throat pain and mucosal congestion, and alleviate mucosal congestion and cough with sputum. With medium-quality evidence, the effectiveness was rated as grade B. Compared with ribavirin aerosol alone, Houyanqing Oral Liquid combined with ribavirin aerosol had cost-effectiveness advantages in the treatment of acute pharyngitis, and its economy was rated as grade C with the evidence of general quality. For acute pharyngitis, Houyanqing Oral Liquid can shorten the disease course and obviously relieve sore throat. Moreover, it can be used for the treatment of radioactive pharyngitis and oral ulcer, and thus its innovation was rated as grade B. With convenient and simple administration and standard and complete drug information, the suitability of this drug was rated as grade B. Houyanqing Oral Liquid is derived from the folk prescription in Hunan province and has been subjected to real-world studies, and thus the TCM characteristics was rated as grade B. According to the ratings of all the dimensions, the comprehensive value of Houyanqing Oral Liquid in the clinical treatment of acute pharyngitis was determined as grade B, with sufficient evidence and clear results. It is suggested that the results should be conditionally converted into relevant policy of clinical basic drug management according to procedures.

[Benefit-risk assessment of three oral Chinese patent medicines for activating blood and eliminating mass in treating primary liver cancer based on network Meta-analysis and multi-criteria decision analysis].

Network Meta-analysis and multi-criteria decision analysis(MCDA) model were performed to evaluate the benefit-risk of Compound Cantharis Capsules, Huisheng Oral Solution, and Jinlong Capsules in the adjuvant treatment of primary liver cancer(PLC). The randomized controlled trial(RCT) of Compound Cantharis Capsules, Huisheng Oral Solution, and Jinlong Capsules in treating PLC were retrieved from CNKI, Wanfang, VIP, Web of Science, PubMed, and Cochrane Library. R 4.2 was employed to conduct a network Meta-analysis, on the basis of which the effect values of the three medicines were obtained by indirect comparison. MCDA was performed to establish the value tree based on the benefit-risk indexes. Hiview 3.2 was used to calculate the benefit values, risk values, and benefit-risk values of the three medicines in treating PLC, and a sensitivity analysis was carried out to evaluate the robustness of the results. Oracle Crystal Ball 11.1 was employed to optimize the evaluation results by Monte Carlo simulation. A total of 39 RCTs were included. The results showed that Compound Cantharis Capsules, Huisheng Oral Solution, and Jinlong Capsules combined with transcatheter arterial chemoembolization(TACE) had the benefit values of 45, 51 and 45, the risk values of 59, 47, and 41, and the benefit-risk values of 52, 49, and 43, respectively. The benefit-risk differences and [95%CI] of Compound Cantharis Capsules vs Huisheng Oral Solution, Compound Cantharis Capsules vs Jinlong Capsules, and Huisheng Oral Solution vs Jinlong Capsules were 3.00[-13.09, 21.82], 9.00[-4.39, 24.62], and 6.00[-8.84, 20.28], respectively. Based on the results of MCDA, Huisheng Oral Solution, Jinlong Capsules, and Compound Cantharis Capsules combined with TACE had the greatest benefit, the greatest risk, and the best overall benefit, respectively. Considering the efficacy and safety, the priority of the three oral Chinese patent medicines combined with TACE for treating PLC followed the trend of Compound Cantharis Capsules, Huisheng Oral Solution, and Jinlong Capsules.

[Clinical comprehensive evaluation of Ruyi Zhenbao Pills in treatment of osteoarthritis].

This study evaluated the clinical effectiveness of Ruyi Zhenbao Pills in the treatment of osteoarthritis, aiming to clarify its clinical advantages and promote rational drug use and related policy transformation. Following the relevant standards in Guidelines for the Comprehensive Evaluation of Drugs in Clinical Practice and Technical Specifications for the Clinical Comprehensive Evaluation of Chinese Patent Medicine, comprehensive research and related data on Ruyi Zhenbao Pills in the treatment of osteoarthritis were collected in the dimensions of safety, effectiveness, economy, innovation, suitability, accessibility, and traditional Chinese medicine(TCM) cha-racteristics(referred to as the "6+1" dimensions). Through evidence-based medicine, questionnaire surveys, health technology assessment, pharmacoeconomic evaluation, and other methods, a multi-criteria decision analysis(MCDA) model and CSC v2.0 software were used to comprehensively evaluate the clinical value of Ruyi Zhenbao Pills. Spontaneous reporting system data on adverse reactions and literature data indicate that the adverse reactions of Ruyi Zhenbao Pills are mostly general adverse reactions, with no reports of se-rious adverse reactions. The known risks are small, and its safety is rated as class A. It has been shown to effectively relieve joint pain and restore joint function in the treatment of osteoarthritis. However, more high-quality, large-sample randomized controlled trials are needed to further validate its effectiveness, which is rated as class B. There is evidence supporting its economic viability, and its economic is rated as class B. It demonstrates good clinical innovation, innovative enterprise service system, and industrial innovation, and innovation is rated as class A. Medical professionals and patients have a favorable perception of the suitability of Ruyi Zhenbao Pills, and further improvement can be made in terms of convenience of administration and promotion to facilitate rational drug use by healthcare professionals and patients. Suitability is rated as class B. The drug has a favorable price level, availability, and affordability, and accessibility is rated as class A. Ruyi Zhenbao Pills are a classic Tibetan medicinal prescription with excellent TCM theoretical characteristics. However, further research is needed on its use in human studies. TCM characteristics are rated as class B. Based on the evaluation results of the "6+1" dimensions, the comprehensive clinical evaluation is rated as grade B. Ruyi Zhenbao Pills have good clinical value in the treatment of osteoarthritis, and it is recommended to undergo the necessary procedures for conditional transformation into a policy for the management of essential clinical drugs.

Synthesis of relevant information around non-core domains to support Multi-Criteria Decision Analysis (MCDA) for decision making.

Countries fundamentally base macro and micro decision making in the field of health on economic considerations, the budgetary impact of technologies being a major criterion. Nevertheless, the value of the technology of interest and its dimensions are more complex if we seek to take decisions based on the value itself. The use of structured and explicit approaches that require the assessment of multiple criteria that reflect the dimensions of this value may significantly improve the quality of the decision making. Multi-criteria decision analysis (MCDA) is a complementary decision-making tool that is able to systematically incorporate dimensions or domains such as ethical, organisational, legal, environmental and social considerations, as well as costs and benefits of medical interventions, together with the distinct perspectives of the interested parties. The objective of this article is to propose the implementation of analysis of non-core domains, in reports of Health Technology Assessment (HTA) agencies/units. To assess the scientific evidence on MCDA techniques a systematic review was conducted using structured searches in biomedical databases and websites of various HTA organisations. A consensus group was held using the nominal group technique and involving users of healthcare services, providers, managers and academics. Complementary, a survey was sent to HTA agencies to ascertain the degree of implementation of MCDA in their methods. 42 articles reporting the use of non-core criteria for the assessment of health technologies were included in the analysis. From these articles, a total of 216 non-core criteria were retrieved and categorised into domains by the researchers, and of these, 56 were classified as socioeconomic, 59 as organisational, 10 as legal, 8 as environmental and 47 as ethical, while 36 were considered to relate to other domains. The consensus group, based on the 216 non-core criteria obtained from the systematic review, proposed, and defined 26 criteria that participants considered necessary for decision making in healthcare. The consensus group did not consider that any of the domains should be given more weight than others or that any individual criteria should dominate. These approaches can serve as a framework of reference for a well-structured systematic discussion concerning the basis of individual criteria and the evidence supporting them.

The application of multi-criteria decision analysis in evaluating the value of drug-oriented intervention: a literature review.

Objectives: Multi-Criteria Decision Analysis (MCDA) has gained increasing attention in supporting drug risk-benefit assessment, pricing and reimbursement, as well as optimization of clinical interventions. The objective of this study was to systematically collect and categorize evaluation criteria and techniques of weighting and scoring of MCDA for drug value assessment. Methods: A systematic review of the literature was conducted across seven databases to identify articles utilizing the MCDA frameworks for the evaluation of drug value. Evaluation criteria mentioned in the included studies were extracted and assigned to 5 dimensions including clinical, economic, innovative, societal and humanistic value. A descriptive statistical analysis was performed on the identified drug value evaluation criteria, as well as the weighting and scoring techniques employed. The more a criterion or technique were mentioned in articles, the more important we consider it. Results: Out of the 82 articles included, 111 unique criteria were identified to evaluate the value of drug. Among the 56 unique criteria (448 times) used to measure clinical value, the most frequently mentioned were "comparative safety/tolerability" (58 times), "comparative effectiveness/efficacy" (56 times), "comparative patient-perceived health/patient reported outcomes" (37 times), "disease severity" (34 times), and "unmet needs" (25 times). Regarding economic value measurement, out of the 20 unique criteria (124 times), the most frequently utilized criteria were "cost of intervention" (17 times), "comparative other medical costs" (16 times), and "comparative non-medical costs" (18 times). Out of the 10 criteria (18 times) for assessing innovative value, "a novel pharmacological mechanism" was the most frequently mentioned criterion (5 times). Among the 22 criteria (73 times) used to measure societal value, "system capacity and appropriate use of intervention" was the most frequently cited criterion (14 times). Out of the 3 criteria (15 times) utilized to measure humanistic value, "political/historical/cultural context" was the most frequently mentioned criterion (9 times). Furthermore, 11 scoring and 11 weighting techniques were found from various MCDA frameworks. "Swing weighting" and "a direct rating scale" were the most frequently used techniques in included articles. Conclusion: This study comprehensively presented the current evaluation dimensions, criteria, and techniques for scoring and weighting in drug-oriented MCDA articles. By highlighting the frequently cited evaluation criteria and techniques for scoring and weighting, this analysis will provide a foundation to reasonably select appropriate evaluation criteria and technique in constructing the MCDA framework that aligns with research objectives.

Development of a decision support tool to compare diagnostic strategies for establishing the herd status for infectious diseases: An example with Salmonella Dublin infection in dairies.

The diagnosis of infectious diseases at herd level can be challenging as different stakeholders can have conflicting priorities. The current study proposes a "proof of concept" of an approach that considers a reasonable number of criteria to rank plausible diagnostic strategies using multi-criteria decision analysis (MCDA) methods. The example of Salmonella Dublin diagnostic in Québec dairy herds is presented according to two epidemiological contexts: (i) in herds with no history of S. Dublin infection and absence of clinical signs, (ii) in herds with a previous history of infection, but absence of clinical signs at the moment of testing. Multiple multiparty exchanges were conducted to determine: 1) stakeholders' groups; 2) the decision problem; 3) solutions to the problem (options) or diagnostic strategies to be ordered; 4) criteria and indicators; 5) criteria weights; 6) the construction of a performance matrix for each option; 7) the multi-criteria analyses using the visual preference ranking organization method for enrichment of evaluations approach; 8) the sensitivity analyses, and 9) the final decision. A total of nine people from four Québec's organizations (the dairy producers provincial association along with the DHI company, the ministry of agriculture, the association of veterinary practitioners, and experts in epidemiology) composed the MCDA team. The decision problem was "What is the optimal diagnostic strategy for establishing the status of a dairy herd for S. Dublin infection when there are no clinical signs of infection?". Fourteen diagnostic strategies composed of the three following parameters were considered: 1) biological samples (bulk tank milk or blood from 10 heifers aged over three months); 2) sampling frequencies (one to three samples collection visits); 3) case definitions to conclude to a positive status using imperfect milk- or blood-ELISA tests. The top-ranking diagnostic strategy was the same in the two contexts: testing the bulk tank milk and the blood samples, all samples collected during one visit and the herd being assigned a S. Dublin positive status if one sample is ELISA-positive. The final decision favored the top-ranking option for both contexts. This MCDA approach and its application to S. Dublin infection in dairy herds allowed a consensual, rational, and transparent ranking of feasible diagnostic strategies while taking into account the diagnostic tests accuracy, socio-economic, logistic, and perception considerations of the key actors in the dairy industry. This promising tool can be applied to other infectious diseases that lack a well-established diagnostic procedure to define a herd status.

An ecotourism suitability index for a world heritage city using GIS-multi criteria decision analysis techniques.

The concept of ecotourism has experienced a significant surge in popularity over the past two decades, primarily driven by the multitude of adverse impacts associated with mass tourism. The objective of the study was to develop a comprehensive ecotourism suitability index to guide policymakers in implementing tourism development policies. Given the considerable appeal of the study area to both local and international tourists, it is essential to conduct a systematic evaluation to pinpoint suitable areas for ecotourism development. This necessity arises from the study area's placement within a fragile ecosystem and its proximity to a UNESCO World Heritage site. We employed a Geographic Information Systems (GIS) integrated environment coupled with a fuzzy Multi-Criteria Decision Analysis (MCDA) methodology. The GIS-MCDA integrated framework leverages the Analytic Hierarchy Process (AHP) and a weighted linear combination that seeks to amalgamate many features and criteria to assess ecotourism potential by integrating 20 criteria into six separate categories: landscape, topography, accessibility, climate, forest and wildlife, and negative factors. Weights were allocated to each criterion and factor based on the expert's opinions of their impact on the development of ecotourism. The final ecotourism suitability index comprised five unique classes: very high, high, moderate, less, and not suitable. Results reveal that out of the total areas, 45.4 % (259 km2) are within the high and very high suitable classes. The sensitivity analysis suggested that ecotourism potentials are more favorable to forest and accessibility variables. The generated index can be utilized as a road map since validation verified a 64 % accuracy. Given the dearth of earlier research, this study provides vital support for the development of sustainable ecotourism projects in the study area.

Application of Multi-Criteria Decision Analysis (MCDA) to Prioritize Real-World Evidence Studies for Health Technology Management: Outcomes and Lessons Learned by the Canadian Real-World Evidence for Value of Cancer Drugs (CanREValue) Collaboration.

Multi-criteria decision analysis (MCDA) is a value assessment tool designed to help support complex decision-making by incorporating multiple factors and perspectives in a transparent, structured approach. We developed an MCDA rating tool, consisting of seven criteria evaluating the importance and feasibility of conducting potential real-world evidence (RWE) studies aimed at addressing uncertainties stemming from initial cancer drug funding recommendations. In collaboration with the Canadian Agency for Drugs and Technologies in Health's Provincial Advisory Group, a validation exercise was conducted to further evaluate the application of the rating tool using RWE proposals varying in complexity. Through this exercise, we aimed to gain insight into consensus building and deliberation processes and to identify efficiencies in the application of the rating tool. An experienced facilitator led a multidisciplinary committee, consisting of 11 Canadian experts, through consensus building, deliberation, and prioritization. A total of nine RWE proposals were evaluated and prioritized as low (n = 4), medium (n = 3), or high (n = 2) priority. Through an iterative process, efficiencies and recommendations to improve the rating tool and associated procedures were identified. The refined MCDA rating tool can help decision-makers prioritize important and feasible RWE studies for research and can enable the use of RWE for the life-cycle evaluation of cancer drugs.

Forest fire risk zoning based on fuzzy logic and analytical network process.

Forest fires have a significant impact on human life, property safety, and ecological environment. Deve-loping high-quality forest fire risk maps is beneficial for preventing forest fires, guiding resource allocation for firefighting, assisting in fire suppression efforts, and supporting decision-making. With a multi-criteria decision analysis (MCDA) method based on geographic information systems (GIS) and literature review, we assessed the main factors influencing the occurrences of forest fires in Youxi County, Fujian Province. We analyzed the importance of each fire risk factor using the analytic network process (ANP) and assigned weights, and evaluated the sub-standard weights using fuzzy logic assessment. Using ArcGIS aggregation functions, we generated a forest fire risk map and validated it with satellite fire points. The results showed that the areas classified as level 4 or higher fire risk accounted for a considerable proportion in Youxi County, and that the central and northern regions were at higher risk. The overall fire risk situation in the county was severe. The fuzzy ANP model demonstrated a high accuracy of 85.8%. The introduction of this novel MCDA method could effectively improve the accuracy of forest fire risk mapping at a small scale, providing a basis for early fire warning and the planning and allocation of firefighting resources.

Incorporating Prior Data in Quantitative Benefit-Risk Assessments: Case Study of a Bayesian Method.

BACKGROUND: Multiple criteria decision analysis (MCDA) and stochastic multi-criteria acceptability analysis (SMAA) in their current implementation cannot incorporate prior or external information on benefits and risks. We demonstrate how to incorporate prior data using a Bayesian mixture model approach while conducting quantitative benefit-risk assessments (qBRA) for medical products. METHODS: We implemented MCDA and SMAA in a Bayesian framework. To incorporate information from a prior study, we use mixture priors on each benefit and risk attribute that mixes information from a previous study with a vague prior distribution. The degree of borrowing is varied using a mixing proportion parameter. RESULTS: A demonstration case study for qBRA using the supplementary New Drug Application (sNDA) filing for Rivaroxaban for the indication of reduction in the risk of major thrombotic vascular events in patients with peripheral artery disease (PAD) was used to illustrate the method. Net utility scores, obtained from the randomized controlled trial data to support the sNDA, from the MCDA for Rivaraxoban and comparator were 0.48 and 0.56, respectively, with Rivaroxaban being the preferred alternative only 33% of the time. We show that with only 30% borrowing from a previous RCT, the MCDA and SMAA results are favorable for Rivaroxaban, accounting for the seemingly aberrant results on all-cause death in the trial data used to support the sNDA. CONCLUSION: Our method to formally incorporate prior data in MCDA and SMAA is easy to use and interpret. Software in the form of an RShiny App is available here: https://sai-dharmarajan.shinyapps.io/BayesianMCDA_SMAA/ .

Setting a shared development agenda: prioritizing the sustainable development goals in the Dominican Republic with fuzzy-LMAW.

The sustainable development goals (SDGs) were established by the United Nations as an international call to eradicate poverty, safeguard the environment, and guarantee that everyone lives in peace and prosperity by 2030. The SDGs aim to balance growth and sustainability in three dimensions: social, economic and environmental. However, in the post-pandemic era, when resources for public development policies are scarce, nations face the problem of prioritizing which SDGs to pursue. A lack of agreement is one of the determinants of low performance levels of the SDGs, and multicriteria decision analysis tools can help in this task, which is especially relevant in developing countries that are falling behind in achieving the SDGs. To test the feasibility and appropriateness of one of these tools, the Fuzzy Logarithm Methodology of Additive Weights, we apply it to prioritize the SDGs in the Dominican Republic, to see if the priorities established are consistent. Seventeen experts were surveyed, and the main result was that Decent work and economic growth was the most important goal for the country. Our findings, consistent with the literature, show the path to similar applications in other developing countries to enhance performance levels in the achievement of the SDGs.