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.

An extension of the best-worst method based on the spherical fuzzy sets for multi-criteria decision-making.

The ambiguous information in multi-criteria decision-making (MCDM) and the vagueness of decision-makers for qualitative judgments necessitate accurate tools to overcome uncertainties and generate reliable solutions. As one of the latest and most powerful MCDM methods for obtaining criteria weight, the best-worst method (BWM) has been developed. Compared to other MCDM methods, such as the analytic hierarchy process, the BWM requires fewer pairwise comparisons and produces more consistent results. Consequently, the main objective of this study is to develop an extension of BWM using spherical fuzzy sets (SFS) to address MCDM problems under uncertain conditions. Hesitancy, non-membership, and membership degrees are three-dimensional functions included in the SFS. The presence of three defined degrees allows decision-makers to express their judgments more accurately. An optimization model based on nonlinear constraints is used to determine optimal spherical fuzzy weight coefficients (SF-BWM). Additionally, a consistency ratio is proposed for the SF-BWM to assess the reliability of the proposed method in comparison to other versions of BWM. SF-BWM is examined using two numerical decision-making problems. The results show that the proposed method based on the SF-BWM provided the criteria weights with the same priority as the BWM and fuzzy BWM. However, there are differences in the criteria weight values based on the SF-BWM that indicate the accuracy and reliability of the obtained results. The main advantage of using SF-BWM is providing a better consistency ratio. Based on the comparative analysis, the consistency ratio obtained for SF-BWM is threefold better than the BWM and fuzzy BWM methods, which leads to more accurate results than BWM and fuzzy BWM.

Suitable municipalities for biomass energy use in Colombia based on a multicriteria analysis from a sustainable development perspective.

Using renewable energies is a global strategy to mitigate the acceleration of global warming generated by industrial processes and is a sustainable way to diversify the energy matrix in all countries. Biomass is a renewable energy source that produces biofuels and generates electricity and heat. The primary purpose of this work is to identify the municipalities in Colombia where agricultural, livestock, and urban residual biomass could be suitable for energy generation in a sustainable and renewable way. To that end, we carried out a Geostatistical Multi-Criteria Decision Methodology using Analytical Hierarchy Processes such as Rank-Sum and Weighted Linear Combination, as well as considering a set of sustainable development indicators applied to official Colombian data. Two scenarios are considered for comparison purposes. The first one is according to expert criteria, and the second one considers The Sustainable Development Goals proposed by the United Nations. Under both proposed scenarios, 127 municipalities were found to be suitable for agricultural-urban residual biomass and 162 for livestock-urban residual biomass for energy generation. One of the main limitations for the use of urban biomass is that municipalities need to have sufficient production potential to fulfill their own energy needs. An additional comparison with previous works to evaluate the performance of the Multi-Criteria Decision Methodologies MCDM is also proposed.

Case Studies with the Contiki-NG Simulator to Design Strategies for Sensors' Communication Optimization in an IoT-Fog Ecosystem.

With the development of mobile communications and the Internet of Things (IoT), IoT devices have increased, allowing their application in numerous areas of Industry 4.0. Applications on IoT devices are time sensitive and require a low response time, making reducing latency in IoT networks an essential task. However, it needs to be emphasized that data production and consumption are interdependent, so when designing the implementation of a fog network, it is crucial to consider criteria other than latency. Defining the strategy to deploy these nodes based on different criteria and sub-criteria is a challenging optimization problem, as the amount of possibilities is immense. This work aims to simulate a hybrid network of sensors related to public transport in the city of São Carlos - SP using Contiki-NG to select the most suitable place to deploy an IoT sensor network. Performance tests were carried out on five analyzed scenarios, and we collected the transmitted data based on criteria corresponding to devices, applications, and network communication on which we applied Multiple Attribute Decision Making (MADM) algorithms to generate a multicriteria decision ranking. The results show that based on the TOPSIS and VIKOR decision-making algorithms, scenario four is the most viable among those analyzed. This approach makes it feasible to optimally select the best option among different possibilities.

To dream or not to dream in Havana: multi-criteria decision-making for material and energy recovery from municipal solid wastes.

Currently, solid waste management strategies in Havana are outdated. This paper aimed to select the most suitable alternative for integrating material recovery facilities (MRF) with waste-to-energy technologies in the city of Havana, Cuba. Seven scenarios were considered: combustion, gasification, and hydrothermal carbonization (HTC) with and without carbon capture, and anaerobic digestion (AD). The selection was based on environmental, techno-economic, and social parameters using an analytic hierarchy process (AHP) as a multi-criteria decision-making tool (MCDM). The MCDM-AHP accounted for qualitative criteria (based on experts' judgments) and quantitative (based on Aspen Plus simulation models). From the MRF, 63% of the input recyclable materials were recovered, representing an energy saving of 256 kW-h/tMSW. The AHP results showed that environmental criteria had the highest priority, resulting in ~63% and ~73% higher than social and techno-economic criteria, respectively. Likewise, from the techno-economic, environmental, and social sub-criteria analysis, investment risk, pollution, and work safety had the major concern compared with the other sub-criteria levels. Overall, MRF+AD was the most suitable scenario (21% preference) for treating Havana's municipal solid waste (MSW), followed by combustion and gasification with carbon capture, respectively. This study confirms that AD is a preference option for emerging economies like Cuba, mainly due to low environmental pollution, high social acceptance, and financial stability in the long term.

Classification of medicines and materials in hospital inventory management: a multi-criteria analysis.

BACKGROUND: In the hospital environment, to achieve an optimum level of operations and service, it is necessary to develop adequate inventory management system. Stocks can be managed, amongst other ways, through inputs classification, which is generally carried out based on a single criterion, such as monetary value, demand or criticality, which does not fully address the complexity of a hospital's inventory management system. Thus, the present study proposes a multi-criteria decision support model to help classify the stock of medicines and materials, enabling a more effective inventory management system for hospitals. METHODS: Methodologically, the study followed 3 stages: (1) preliminary phase; (2) modelling and choice phase; and (3) finalization phase. Each stage had a set of specific steps that were followed. The first stage identified the actors of the process, objectives, criteria and alternatives, establishing 5 criteria and 48 alternatives; the second stage was the choice and execution of the multi-criteria decision method to solve the problem. It was decided to use the Flexible and Interactive Tradeoff method for the sorting problematic. Finally, in the third stage, the sensitivity analysis for the developed model and the validation of the results with decision makers were carried out. In the study, 48 medicines and materials were included to validate the proposed model; however, the model could be used for more items. RESULTS: From the total of 48 medicines and hospital medical materials selected for the study, the classification of 34 of these alternatives to a single class was obtained through modelling and the other 14 alternatives were destined to two possible classes; moreover, the sensitivity analysis performed showed robust results. The items classified in class W should receive special attention by the stock manager; therefore, they should be monitored weekly. Items classified in class B should be monitored biweekly and finally, items classified in class M, should be monitored monthly. CONCLUSIONS: The classification of medicines and materials developed according to the inventory demands allowed more efficient purchasing decisions, optimizing the stock of materials and medicines at the hospital while optimizing the inventory manager's activities, saving time. Consequently, the proposed model can support the development of other multicriteria models in different hospital scenarios.

Feasibility of a Hospital Information System for a Military Public Organization in the Light of the Multi-Criteria Analysis.

The healthcare environment presents a large volume of personal and sensitive patient data that needs to be available and secure. Information and communication technology brings a new reality to healthcare, promoting improvements, agility and integration. Regarding high-level and complex decision-making scenarios, the Brazilian Navy (BN), concerning its healthcare field, is seeking to provide better management of its respective processes in its hospital facilities, allowing accurate control of preventive and curative medicine to members who work or have served there in past years. The study addresses the understanding, structure and clarifying variables related to the feasibility of technological updating and installing of a Hospital Information System (HIS) for BN. In this scenario, through interviews and analysis of military organization business processes, criteria and alternatives were established based on multi-criteria methodology as a decision aid. As methodological support for research and data processing, THOR 2 and PROMETHEE-SAPEVO-M1 methods were approached, both based on the scenarios of outranking alternatives based on the preferences established by the stakeholders in the problem. As a result of the methodological implementation, we compare the two implemented methods in this context, exposing the Commercial Software Purchase and Adoption of Free Software, integrated into Customization by the Marine Studies Foundation, as favorable actions to be adopted concerning HIS feasibility. This finding generates a comprehensive discussion regarding the BN perspective and changes in internal development in the military environment, prospecting alignment to the culture of private organizations in Information Technology for healthcare management. In the end, we present some conclusions concerning the study, exploring the main points of the decision-making analysis and for future research.

A Multi-Criteria Approach to Assess the Performance of the Brazilian Unified Health System.

Brazil's Unified Health System (SUS) provides universal free access to health services and is considered a model for the rest of the world. One of the tools used by the Brazilian government to assess this system is the Index of Unified Health System Performance (IDSUS). However, this method has a number of limitations, such as disregarding the opinion of healthcare decision makers. Thus, the aim of the present study was to propose a model based on the R-TOPSIS in order to assess the performance of the SUS. Methodologically, the main steps for proposing multi-criteria models were followed, and to validate the model, a real case study with a set of six cities (alternatives) of the state of São Paulo was used. The results provide a clearer picture of the differences in terms of potential and obtained access, as well as the effectiveness of health services in the cities analyzed. Likewise, the proposal of integrating multiple criteria as well as considering healthcare decision makers proved to be decisive for the results obtained, even in comparison with the other approaches. It was concluded that the proposed method provides a robust and adequate analysis of health systems performance.

A Novel Approach to Multi-Provider Network Slice Selector for 5G and Future Communication Systems.

The Network Slice Selection Function (NSSF) in heterogeneous technology environments is a complex problem, which still does not have a fully acceptable solution. Thus, the implementation of new network selection strategies represents an important issue in development, mainly due to the growing demand for applications and scenarios involving 5G and future networks. This work presents an integrated solution for the NSSF problem, called the Network Slice Selection Function Decision-Aid Framework (NSSF DAF), which consists of a distributed solution in which a part is executed on the user's equipment (for example, smartphones, Unmanned Aerial Vehicles, IoT brokers) functioning as a transparent service, and another at the Edge of the operator or service provider. It requires a low consumption of computing resources from mobile devices and offers complete independence from the network operator. For this purpose, protocols and software tools are used to classify slices, employing the following four multicriteria methods to aid decision making: VIKOR (Visekriterijumska Optimizacija i Kompromisno Resenje), COPRAS (Complex Proportional Assessment), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and Promethee II (Preference Ranking Organization Method for Enrichment Evaluations). The general objective is to verify the similarity among these methods and applications to the slice classification and selection process, considering a specific scenario in the framework. It also uses machine learning through the K-means clustering algorithm, adopting a hybrid solution in the implementation and operation of the NSSF service in multi-domain slicing environments of heterogeneous mobile networks. Testbeds were conducted to validate the proposed framework, mapping the adequate quality of service requirements. The results indicate a real possibility of offering a complete solution to the NSSF problem that can be implemented in Edge, in Core, or even in the 5G Radio Base Station itself, without the incremental computational cost of the end user's equipment, allowing for an adequate quality of experience.

Using the FITradeoff Decision Support System to Support a Brazilian Compliance Organization Program.

The technology can support multi-criteria decision-making processes, allowing managers to identify efficient solutions to complex problems in a structured and rational way. Specially, in time of crises, the use of Decision Support System (DSS) is useful since these situations demand greater accuracy in the decision-making process. Therefore, this study shows the usefulness of the Decision Support System constructed for the FITradeoff method in a practical context involving a decision-making in time of crisis. In special, in this study, the applicability of the FITradeoff DSS is discussed to solve an important problem involving a Brazilian Company. The FITradeoff DSS was employed for a compliance-program problem, in which a company sought to improve its performance in relation to the program. This problem is particularly significant in Brazil where the search for compliance programs has been increasing since the adoption of the anticorruption law. Thus, twenty-eight alternatives were created, and these alternatives were evaluated against five criteria. As a result, most of the alternatives in the top of the ranking are related to Internal Communication aspect. Hence, the DM considered that these alternatives are sufficient to direct the efforts to execute the Compliance Program, and in special this theme can be the focus in this company. Furthermore, in view of recurring crises around the world, companies must identify ways to ensure their internal processes support the sustainability of their business. For decision making in times of crisis, the DSS of the FITradeoff method is an effective tool allowing decision makers to handle complex decisions.

A Meta-Analytic Framework for Developing Protocols to Attend Child and Adolescent Victims of Sexual Violence.

Violence against children and adolescents is a global public health problem. In Brazil, there are challenging boundaries for professionals in the protection network in general and for health professionals in particular. Moreover, among other factors, there is the challenge of referral, due to weaknesses in decision making, given the nature of sexual violence and how it is managed by healthcare services. This study aims to propose a Meta-Analytic framework to support the referral of young victims of sexual violence, considering levels of severity, independent of factors such as how protection systems are structured and managed and the local laws in force. We propose a Meta-Analytic approach, developed using the fundamentals of Delphi and DPSIR (Drivers, Pressures, State, Impact, and Response Model of Intervention), from the perspective of Value-Focused Thinking. The Delphi method was structured in two stages: the first stage aimed to identify and classify typical cases of sexual violence; the second stage used the DPSIR model, with the aim of identifying the decision criteria for typical cases that occur in a given municipality. The main outcomes are: (i) the application of the modified Delphi participatory method within the context of local social policies; (ii) the construction of a value tree based on Value-Focused Thinking; and (iii) the identification and systematization of criteria that most interfere with the evaluation of cases of sexual violence, which can be used for multi-criteria decision making.

Qualitative evaluation of pharmaceuticals and metabolites in hospital effluent: Influence of sample preparation technique and outranking by environmental risk using the ELECTRE method.

The presence of pharmaceuticals and metabolites in effluents has become a serious environmental problem, so it is essential to be able to monitor these microcontaminants using qualitative approaches, as well as to assess the potential environmental risks that such compounds may present. Therefore, in this study, suspect screening analysis was performed of 2030 pharmaceuticals and metabolites in hospital effluent samples, applying different sample preparation techniques. Additionally, a pioneering association of (Q)SAR assessment of identified contaminants with the ELECTRE multi-criteria decision analysis technique made it possible to prioritize analytes according to their environmental risk, in order to enable their inclusion in environmental monitoring programs. The results showed that the most advantageous alternative sample preparation technique consisted of cleanup (100 mg of silica/alumina sorbent) + dispersive liquid-liquid microextraction (7.5 of aqueous matrix, 325 µL of chloroform (extracting solvent), and 500 µL of acetonitrile as dispersing solvent). This procedure resulted in the identification of 70 pharmaceuticals and metabolites in the composite sample tested. The suspect screening analysis found a total of 105 microcontaminants, 28 of them being "confirmed compounds" and 77 being "suspect compounds". Of the compounds identified, 87% were pharmaceuticals and 13% were metabolites. The compounds identified were subsequently evaluated using different open access software packages, considering eight endpoints: mobility, persistence, estrogen receptor binding, wastewater treatment plant total removal, biodegradability, PBT (persistent, bioaccumulation and toxic), mutagenicity, and carcinogenicity. The (Q)SAR prediction results were used as input data for the ELECTRE outranking method. Categorization of the identified compounds by ELECTRE resulted in the kernel (priority compounds) and a further 19 groups. ELECTRE sensitivity evaluation indicated that for all the cases, the kernel and the following two groups coincided. The categorization provided by the ELECTRE method constitutes a highly intuitive decision and choice tool, which can assist in the selection of compounds if subsequent quantitative analysis is to be carried out.

A Novel Integration of IF-DEMATEL and TOPSIS for the Classifier Selection Problem in Assistive Technology Adoption for People with Dementia.

The classifier selection problem in Assistive Technology Adoption refers to selecting the classification algorithms that have the best performance in predicting the adoption of technology, and is often addressed through measuring different single performance indicators. Satisfactory classifier selection can help in reducing time and costs involved in the technology adoption process. As there are multiple criteria from different domains and several candidate classification algorithms, the classifier selection process is now a problem that can be addressed using Multiple-Criteria Decision-Making (MCDM) methods. This paper proposes a novel approach to address the classifier selection problem by integrating Intuitionistic Fuzzy Sets (IFS), Decision Making Trial and Evaluation Laboratory (DEMATEL), and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The step-by-step procedure behind this application is as follows. First, IF-DEMATEL was used for estimating the criteria and sub-criteria weights considering uncertainty. This method was also employed to evaluate the interrelations among classifier selection criteria. Finally, a modified TOPSIS was applied to generate an overall suitability index per classifier so that the most effective ones can be selected. The proposed approach was validated using a real-world case study concerning the adoption of a mobile-based reminding solution by People with Dementia (PwD). The outputs allow public health managers to accurately identify whether PwD can adopt an assistive technology which results in (i) reduced cost overruns due to wrong classification, (ii) improved quality of life of adopters, and (iii) rapid deployment of intervention alternatives for non-adopters.

Evaluation of the performance of a collaborative proposal of multiple access in cognitive radio networks.

Cognitive radio networks (CRN) allow for an increase in spectral efficiency and performance of today's wireless networks. Currently, multiple proposals exist in the area of spectral decision-making and mobility; however, very few evaluate the impact of collaboration between secondary users and the performance of spectrum access by many secondary users. Unlike existing works, this article provides a comprehensive quantitative analysis of the performance of CRN taking into account access to the spectrum simultaneously by multiple users and decision making based on collaboration through the exchange of information between nearby secondary users. This proposal is developed through the implementation of four modules: Input Module, Multi-user Module, Collaborative module and Decision-making module, where the results are evaluated comparatively through the handoff rate generated with two multicriteria techniques: Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Multi-Criteria Optimization and Compromise Solution (VIKOR). The evaluation is carried out taking into account three levels of collaboration, three multi-user access scenarios, and two multi-criteria techniques for a total of 18 simulation scenarios. The results obtained show the importance of implementing collaboration strategies, as for multi-user access, the number of handoffs increases as the number of serial users increases. TOPSIS presented the best results in 76 % of the analyzed cases where VIKOR generated a smaller number of handoffs; TOPSIS maintained good performance with differences not exceeding 90 handoffs.

A Decision Support Tool For Water Pollution and Eutrophication Prevention In Groundwater-dependent Shallow Lakes From Periurban Areas Based On The DPSIR Framework.

The deterioration of water quality worldwide is a serious environmental problem. Water managers still need operational tools to assess water issues and to inform water planning and decision-making. The aim of this article is to propose a 3-step methodological framework for assessing water pollution problems by combining a conceptual modeling tool (DPSIR) with the development of a quantitative model (Multi-Criteria Decision Model). This contribution provides a practical and flexible evaluation tool for conducting an integrated assessment of eutrophication and agrochemicals delivered to groundwater-dependent shallow lakes. It lays out action guidelines for decision-making environmental managers within the context of intermediate cities in developing countries. Forty-one indicators were identified to characterize the D-P-S-I compartments and for the multi-criteria model conceptualization. In this work, response options analysis consisted of evaluating and choosing water management instruments via a decision support tool. Two lake watersheds located in the peri-urban of two middle-size cities, in Argentina, were chosen to illustrate this methodological approach. The ensuing results allowed establishing a ranking of areas to prioritize, identifying a criteria and sub-criteria to focus on in order to set out action guidelines to minimize water pollution and eutrophication. These action guidelines are urgently needed in emerging countries, where financial, human resources and infrastructure are limited. The scarcity of such causes important implications regarding policy solutions for environmental issues. The implemented decision support tool in both lake watersheds provided a common basis for the understanding of the ongoing water pollution problems and a quantitative ranking (i.e., decision scores) for defining specific actions (responses) for human-induced stresses on such natural systems.

Healthcare waste management assessment: Challenges for hospitals in COVID-19 pandemic times.

With the spread of the new Coronavirus, there was an increase in the generation of contaminated waste. Thus, healthcare waste management (HCWM) became even a greater challenge in hospitals due to Coronavirus easily spread. In this context, it was necessary to create tools that could aid healthcare facilities in evaluating their HCWM. Therefore, the objective of this article was to elaborate a support tool that helps in identifying the shortcomings of hospitals' HCWM. For this purpose, the Health Service Waste Management Index was developed based on the selection of indicators in the area. The index was applied to six hospitals in the state of Minas Gerais, Brazil. Its application meet the purpose of this research, since the results in the form of an index objectively summarize the reality of the HCWM in healthcare facilities. From the six hospitals investigated, four were classified as highly efficient. However, even though most of them were well evaluated, they still have difficulties with properly training their employees, which can be even a worse problem during a pandemic, when every precaution is extremely important to reduce the spread of the disease. Therefore, beyond this article contribution related to sustainability by demanding the hospitals to check which points of HCWM should be improved, it also adds academically by developing a tool with indicators that evaluate operational, human, economic and environmental factors in an innovative way.

Performance Appraisal of Select Nations in Mitigation of COVID-19 Pandemic using Entropy based TOPSIS Method / Avaliação de desempenho de nações selecionadas na mitigação de pandemia de COVID-19 usando método TOPSIS baseado em entropia

Abstract The present study was an effort to assess the mitigation interventions carried out, so far, by the nations to fight the pandemic COVID-19. The novelty of the study was that it had considered the issue of pandemic mitigation strategy as a decision making problem. The performances of the twenty nations were to be ranked. The problem considered in the study was essentially a Multi-Criteria Decision Analysis (MCDA) problem. The available alternatives were the 20 countries and the 8 traits were the criteria. The Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) was used in the present study. The study used Entropy method for assignment of weights to all the criteria. The performance score obtained in respect of the countries considered in the study and the corresponding ranks indicated the relative performances of the countries in their efforts to mitigate the COVID-19 pandemic. The results show that New Zealand is the best performing country and India is the worst one. Brazil ranked 17th, while the rank of UK was 15. The performance of the USA stood at 18th position.

Resumo O presente estudo foi um esforço para avaliar as intervenções de mitigação realizadas, até o momento, pelas nações para combater a pandemia COVID-19. A novidade do estudo é que considerou a questão da estratégia de mitigação da pandemia como um problema de tomada de decisão. As performances das vinte nações deveriam ser classificadas. O problema considerado no estudo era essencialmente um problema de Análise de Decisão Multi-Critério (MCDA). As alternativas disponíveis eram os 20 países e as 8 características eram os critérios. A Técnica de Similaridade de Preferência de Pedido com a Solução Ideal (TOPSIS) foi utilizada no presente estudo. O estudo utilizou o método da Entropia para atribuição de pesos a todos os critérios. A pontuação de desempenho obtida em relação aos países considerados no estudo e as classificações correspondentes indicaram os desempenhos relativos dos países em seus esforços para mitigar a pandemia COVID-19. Os resultados mostram que a Nova Zelândia é o país com melhor desempenho e a Índia o pior. O Brasil ficou em 17º, enquanto o Reino Unido ficou em 15. O desempenho dos EUA ficou na 18ª posição.

Sanitary landfill site selection using multi-criteria decision analysis and analytical hierarchy process: A case study in Azuay province, Ecuador.

Despite environmental regulations in Ecuador, particularly in the Province of Azuay, the solid waste final disposal management is still a socio-environmental problem, worsened by weak governance processes. The province has three sanitary landfills with almost expired service lives. The site selection was based on circumstantial reasons, which makes landfills more likely to cause environmental pollution and, therefore, have negative implications for public health. The largest landfill serves Cuenca and also leases service to other small cities. The remaining two are small and, accordingly, have limited technology and fewer resources. In this context, the main aim of this study is to evaluate the terrain of the province to find the most suitable area for landfill siting. A multi-criteria decision analysis, integrated with a geographical information system and analytical hierarchy process methodology, was conducted. Fourteen factors and seven constraints were simultaneously analysed, divided into technical, environmental, social, and economic categories; 15 of these criteria were from the Ecuadorian Unified Text of the Secondary Legislation of the Environmental Ministry. According to the results, 76.17% of the territory is not suitable for landfill implementation, and the unrestricted area represents the remaining 23.83%. The highest landfill suitability index (70-81%) is located in the south of the province in Santa Isabel, Oña, and Nabón cantons, which are dry and clay-rich areas.

Methodological proposal for the allocation of water quality monitoring stations using strategic decision analysis.

In order to fill a gap in the monitoring of water quality in Brazil, the objective of this study was to propose a methodology to support the allocation of water quality monitoring stations in river basins. To achieve this goal, eight criteria were selected and weighted according to their degree of importance. It was taken into account the opinion of water resources management experts. In addition, a decision support system was designed so that the methodology could be used in the allocation of water quality monitoring stations by researchers and management bodies of water resources, to be fully implemented in geographic information system environment. In order to demonstrate the potential of the proposed methodology, which can be used in places that have or not existing monitoring networks, it has been applied in the Minas Gerais portion of the Doce river basin. Because the area already has a monitoring network with 65 stations in operation under the responsibility of the Minas Gerais Water Management Institute (IGAM), an expansion of the network was suggested and a simulation of a scenario was performed considering that the study area did not have an established network. The results of the analyses consisted of maps of suitability, indicating the locations with greater and lesser suitability for the establishment of the stations. With the application of the methodology, seven new sites were proposed so that the study area had the density recommended by the National Water Agency (ANA), and it was verified that the Caratinga River Water Resources Management Unit (UGRH5 Caratinga) has the most deficiency of stations among the six units evaluated in the Minas Gerais portion of the Doce river basin. In the simulated scenario considering the non-existence of a network, the adequacy map obtained was compared with the existing monitoring network and it was possible to classify the stations according to the purpose for which they were established, such as monitoring environments under anthropic activities or establishing benchmarks for the water bodies. Overall, the proposed methodology proved itself robust, and although the results were specific to one basin, the criteria and decision support system used are fully applicable to other areas of study.

International experiences in multicriteria decision analysis (MCDA) for evaluating orphan drugs: a scoping review.

Introduction: Orphan diseases are low-prevalence conditions with chronically debilitating or life-threatening consequences. Their treatments are generally called orphan drugs (OD). Health-technology assessment processes have traditionally considered cost-effectiveness analysis (CEA), when making reimbursement and pricing decisions for health-care plans. Valuing OD with standard CEA raises important issues due to uncertain evidence, inability to meet cost-effectiveness thresholds for reimbursement and high budget impact, among others. Multi-criteria decision analysis (MCDA) allows to overcome these issues and improve the technical and ethical quality of decisions regarding prioritization, coverage, and reimbursement of OD. Areas covered: A scoping review was conducted in order to characterize MCDA frameworks for assessing OD and implementation experiences. We reviewed electronic databases (Medline, Embase, Cochrane Library, EBSCO, CINAHL, EconLit, Web of Science, LILACS, Google Scholar) key journals (Orphanet Journal of Rare Diseases and Value in Health) and organization repositories. Expert opinion: The theoretical framework for MCDA considers areas related to characteristics of orphan diseases and their technologies' clinical and economic impact. Participation processes are critical in incorporating societal values in weighting different dimensions and constructing decision rules. Local implementation pilots considering different stakeholders are necessary in order to pinpoint specific barriers and opportunities.