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Guidance on the use of complex systems models for economic evaluations of public health interventions

HEALTH ECONOMICS 2023年第7期32卷 1603-1625页

作者： Breeze, Penny R. Squires, Hazel Ennis, Kate Meier, Petra Hayes, Kate Lomax, Nik Shiell, Alan Kee, Frank de Vocht, Frank O'Flaherty, Martin Gilbert, Nigel Purshouse, Robin Robinson, Stewart Dodd, Peter J. Strong, Mark Paisley, Suzy Smith, Richard Briggs, Andrew Shahab, Lion Occhipinti, Jo-An Lawson, Kenny Bayley, Thomas Smith, Robert Boyd, Jennifer Kadirkamanathan, Visakan Cookson, Richard Hernandez-Alava, Monica Jackson, Christopher H. Karapici, Amanda Sassi, Franco Scarborough, Peter Siebert, Uwe Silverman, Eric Vale, Luke Walsh, Cathal Brennan, Alan School of Health and Related Research University of Sheffield Sheffield UK British Medical Journal Technology Appraisal Group London UK MRC/CSO Social and Public Health Sciences Unit University of Glasgow Scotland UK School of Geography University of Leeds Leeds UK Department of Public Health LaTrobe University Melbourne Australia Centre for Public Health Queen's University Belfast Belfast UK Population Health Sciences Bristol Medical School University of Bristol Bristol UK NIHR Applied Research Collaboration West (ARC West) Bristol UK Department of Public Health Policy and Systems University of Liverpool Liverpool UK CRESS University of Surrey Guildford UK Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK Business School University of Newcastle Newcastle UK Lumanity-HEOR South Yorkshire Sheffield UK College of Medicine and Health University of Exeter Exeter UK London School of Hygiene & Tropical Medicine London UK Department of Behavioural Science and Health UCL London UK Brain and Mind Centre University of Sydney New South Wales Camperdown Australia United Kingdom Health Security Agency Birmingham UK MRC/CSO Social and Public Health Sciences Unit University of Glasgow Glasgow UK Centre for Health Economics University of York Heslington UK MRC Biostatistics Unit University of Cambridge Cambridge UK NIHR SPHR London School of Hygiene and Tropical Medicine London UK Centre for Health Economics & Policy Innovation Imperial College Business School London UK Nuffield Department of Population Health University of Oxford Oxfordshire Oxford UK Department of Public Health Health Services Research and Health Technology Assessment UMIT TIROL - University for Health Sciences and Technology Hall in Tirol Tyrol Austria Division of Health Technology Assessment and Bioinformatics ONCOTYROL - Center for Personalized Cancer Medicine Innsbruck Austria Center for Health Decision Science Departments of Epidemio

To help health economic modelers respond to demands for greater use of complex systems models in public health. To propose identifiable features of such models and support researchers to plan public health modeling projects using these models. A working group of experts in complex systems modeling and economic evaluation was brought together to develop and jointly write guidance for the use of complex systems models for health economic analysis. The content of workshops was informed by a scoping review. A public health complex systems model for economic evaluation is defined as a quantitative, dynamic, non-linear model that incorporates feedback and interactions among model elements, in order to capture emergent outcomes and estimate health, economic and potentially other consequences to inform public policies. The guidance covers: when complex systems modeling is needed;principles for designing a complex systems model;and how to choose an appropriate modeling technique. This paper provides a definition to identify and characterize complex systems models for economic evaluations and proposes guidance on key aspects of the process for health economics analysis. This document will support the development of complex systems models, with impact on public health systems policy and decision making.

关键词： complex systems economic modeling public health

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The effectiveness of giving students in-game cards as rewards 2nd

The effectiveness of giving students in-game cards as reward...

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2nd International Cognitive Cities Conference, IC3 2019

作者： Chen, Cheng-Li Chang, Maiga Chang, Hung-Yi Lin, Chun-Hung Li, Kuo-Chen Kuo, Rita Wang, Hongxue School of Computing and Information Systems Athabasca University Athabasca Canada Department of Information Management National Kaohsiung University of Science and Technology Kaohsiung Taiwan Center for Teacher Education Chung-Yuan Christian University Taoyuan City Taiwan Department of Information Management Chung-Yuan Christian University Taoyuan City Taiwan Department of Computer Science and Engineering New Mexico Institute of Mining and Technology Socorro United States

ISBN: (纸本)9789811561122

Reward has become an important role to increase students’ motivation in traditional classroom learning. The research team designed an In-game Card as Education Reward (ICER) web-based system which helps teachers give students reward while students have good performance in learning activities such as assignment, presentation, discussion, quiz, and exam. Whenever students complete a learning activity, their teacher can choose different type and rarity in-game cards and deliver the cards to the students by using ICER web-based management system. Students can redeem the reward on ICER website and receive in-game cards in the game. Students can have more fun in the game-play or even show-off the cards that they have to other students. For this reason, students may put more efforts on studying and doing learning activities and may be even actively participated in the discussions in the class for getting better rewards. © Springer Nature Singapore Pte Ltd 2020.

关键词： Students

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Quantifying the unfairness of the 2018 FIFA World Cup qualification

arXiv

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arXiv 2020年

作者： Csató, László Laboratory on Engineering and Management Intelligence Research Group of Operations Research and Decision Systems Budapest Hungary Department of Operations Research and Actuarial Sciencesn Budapest Hungary

This paper investigates the fairness of the 2018 FIFA World Cup qualifying competition via Monte Carlo simulations. The qualifying probabilities are calculated for 102 nations, all teams except for African and European countries. A method is proposed to quantify the degree of unfairness. Although the qualifications within four FIFA confederations are constructed fairly, serious differences are found between the continents: for instance, a South American team could have tripled its chances by playing in Asia. Choosing a fixed matchup in the inter-continental play-offs instead of the current random draw can reduce the unfairness of the competition. The move of Australia from the Oceanian to the Asian zone is shown to increase its probability of participating in the 2018 FIFA World Cup by about 65%. Our results provide important insights for the administrators on how to reallocate the qualifying *** Codes 62F07, 68U20 Copyright © 2020, The Authors. All rights reserved.

关键词： Sports

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Theory and Implementation of Sensitivity Analyses Based on Their Algebraic Representation in the Graph Model

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Journal of systems Science and systems engineering 2019年第5期28卷 580-601页

作者： Jinshuai Zhao Haiyan Xu Keith W.Hipel Baohua Yang College of Economics and Management Nanjing University of Aeronautics and Astronautics Nanjing 211106 China College of Computer Science and Technology Jiangsu Normal University Xuzhou 221116 China Department of Systems Design Engineering University of Waterloo Waterloo Canada School of Business Jiangsu Normal University Xuzhou 221116 China

Sensitivity analyses based on an algebraic representation in the graph model for conflict resolution (GMCR) are generalized for ascertaining the robustness of stability results by varying decision makers' preference *** ordinal preferences in GMCR are advantageous to carry out sensitivity analyses with respect to systematically identifying the influence of preference alterations upon the four basic stabilities consisting of Nash stability,general metarationality,symmetric metarationality and sequential *** proposed algebraic representation of the four basic stabilities is not only effective and convenient for computer implementation of sensitivity analysis,but also makes it easier to understand the meaning of the four stabilities when compared with the existing matrix ***,these sensitivity analyses results are embedded into the latest version of the decision support system NUAAGMCR,which can be used to study real-world *** illustrate how these contributions to sensitivity analyses can be applied in practice and provide valuable strategic insights,they are used to investigate the civil war conflict in South Sudan.

关键词： Sensitivity analyses algebraic expression graph model ordinal preference conflict resolution

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Deep Neural Network Framework for Predicting Cardiovascular Diseases from ECG Signals

Recent Advances in Computer Science and Communications

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Recent Advances in Computer Science and Communications 2025年

作者： Soni, Tanishq Gupta, Deepali Uppal, Mudita Juneja, Sapna Gulzar, Yonis Ghafoor, Kayhan Zrar Chitkara University Institute of Engineering and Technology Chitkara University Punjab India KIET Group of Institutions Ghaziabad India Department of Management Information Systems College of Business Administration King Faisal University Al Ahsa 31982 Saudi Arabia Department of Information and Communication Technology Eng Erbil Polytechnic University Iraq

Introduction: Cardio Vascular Disease (CVD), a primary cause of death worldwide, includes a variety of heart-related disorders like heart failure, arrhythmias, and coronary artery disease (CAD), where plaque buildup narrows the heart muscle's blood vessels and causes angina or heart attacks. Genetics, congenital anomalies, bad diet, lack of exercise, smoking, and chronic diseases including hypertension and diabetes can cause cardiac disease. Method: The symptoms can range from chest pain and shortness of breath to exhaustion and palpitations and diagnosis usually involves a medical history, physical examination, and electrocardiograms (ECGs), and stress testing. Lifestyle adjustments, medicines, angioplasty, and bypass grafts or heart transplants are possible treatments. Preventive measures include healthy living, risk factor management, and frequent checkups, which are few measures, whereas advanced algorithms can analyze massive volumes of ECG and MRI data to find patterns and anomalies that humans may overlook. Results: The deep learning models increase arrhythmia, coronary artery disease, and heart failure diagnosis accuracy and speed. They enable predictive analytics, early intervention, and personalized treatment programs, increasing cardiac care results. The proposed DNN model consists of a 3-layer architecture having input, hidden, and output layers. In the hidden layer, 2 layers, namely, the dense layer and batch normalization layer are added to enhance its accuracy. Conclusion: Three different optimizers namely Adam, AdaGrad, and AdaDelta are tested on 50 epochs and 32 batch sizes for predicting cardiovascular disease. Adam optimizer has the highest accuracy of 85% using the proposed deep neural network. © 2024 Bentham Science Publishers.

关键词： Personalized medicine

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Multi-Objective Model for End-of-Life Tires Reverse Logistics: Enhancing Sustainability through a Techno-Political Framework

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Expert systems with Applications 2025年

作者： Ignacio Castañeda-Rodríguez Andrea Teresa Espinoza Pérez organization=University of Santiago of Chile (USACH) Faculty of Engineering Program for the development of sustainable production systems (PDSPS) city=Santiago country=Chile organization=University of Santiago of Chile (USACH) Faculty of Engineering Industrial Engineering Department addressline=Av. Víctor Jara 3769 city=Santiago postcode=9170124 state=Estación Central country=Chile Université de Lorraine ERPI Nancy F-54000 France University of Technology Sydney 61 Broadway Str Sydney NSW 2007 Australia

The management of End-of-Life Tires (ELT) presents a growing concern about environmental pollution that has led to a tightening of legislation worldwide. One approach gaining attention is Extended Producer Responsibility (EPR), which makes producers responsible for the life-cycle management of their products. This work introduces a multi-objective optimization model that supports decision-making through the integration of a techno-political framework to enhance traditional sustainability assessment, studying the impact of introducing collection goals, valuation quotas and emerging valorization technologies. A Chilean case study is presented considering the implementation of pyrolysis plants for the recycling of ELT under the regulatory framework of the EPR Law. The results show that introducing political and technological parameters and variables into economic, environmental, and social objectives facilitates convergence towards a solution, despite the initial opposition of the objectives. Applying the ϵ -constraint method allows to find profitable alternatives for this project. However, those solutions that further reduce the gap and achieve a balance between the three objectives tend to produce negative economic outcomes, suggesting that fully sustainable scenarios may not be economically feasible. Sensitivity analyses highlight the trade-offs involved in balancing economic feasibility in sustainable scenarios with technological and regulatory measures. Considering all the above, it is necessary to strengthen regulatory policies that support reverse logistics, ELT recovery technologies, and the development of decentralized ELT management systems. Lastly, modifications in the collection goals, robust optimization for dealing with uncertainty, and multiple recycling technologies assessment are suggested as future guidelines.

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The role of inter-island transmission in full decarbonisation scenarios for Indonesia’s power sector

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Environmental Research: Energy 2024年第2期1卷 025006-025006页

作者： Jannis Langer Francesco Lombardi Stefan Pfenninger Harkunti P Rahayu Muhammad Indra Al Irsyad Kornelis Blok Department of Engineering Systems and Services Delft University of Technology Faculty of Technology Policy and Management Jaffalaan 5 2628 BX Delft The Netherlands Institute Technology of Bandung School of Architecture Planning and Policy Development Bandung Indonesia National Research and Innovation Agency Jakarta Indonesia

Indonesia has large renewable energy resources that are not always located in regions where they are needed. Sub-sea power transmission cables, or island links, could connect Indonesia's high-demand islands, like Java, to large-resource islands. However, the role of island links in Indonesia's energy transition has been explored in a limited fashion. Considering Indonesia's current fossil fuel dependency, this is a critical knowledge gap. Here we assess the role of island links in Indonesia's full power sector decarbonisation via energy system optimisation modelling and an extensive scenario and sensitivity analysis. We find that island links could be crucial by providing access to the most cost-effective resources across the country, like onshore photovoltaics (PV) and hydropower from Kalimantan and geothermal from Sumatera. In 2050, 43 GW of inter-island transmission lines enable 410 GW_p of PV providing half of total generation, coupled with 100 GW of storage, at levelised system costs of 60 US$(2021)/MWh. Without island links, Java could still be supplied locally, but at 15% higher costs due to larger offshore floating PV and storage capacity requirements. Regardless of the degree of interconnection, biomass, large hydro, and geothermal remain important dispatchable generators with at least 62 GW and 23% of total generation throughout all tested scenarios. Full decarbonisation by 2040 mitigates an additional 464 MtCO₂e compared to decarbonisation by 2050, but poses more challenges for renewables upscaling and fossil capacity retirement.

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Neural architecture search with an efficient multiobjective evolutionary framework

arXiv

引用

arXiv 2020年

作者： Baldeon Calisto, Maria G. Lai-Yuen, Susana K. Department of Industrial and Management Systems Engineering University of South Florida 4202 E. Fowler Ave. TampaFL33620 United States

Deep learning methods have become very successful at solving many complex tasks such as image classification and segmentation, speech recognition and machine translation. Nevertheless, manually designing a neural network for a specific problem is very difficult and time-consuming due to the massive hyperparameter search space, long training times, and lack of technical guidelines for the hyperparameter selection. Moreover, most networks are highly complex, task specific and over-parametrized. Recently, multiobjective neural architecture search (NAS) methods have been proposed to automate the design of accurate and efficient architectures. However, they only optimize either the macro- or micro-structure of the architecture requiring the unset hyperparameters to be manually defined, and do not use the information produced during the optimization process to increase the efficiency of the search. In this work, we propose EMONAS, an Efficient MultiObjective Neural Architecture Search framework for the automatic design of neural architectures while optimizing the networḱs accuracy and size. EMONAS is composed of a search space that considers both the macro- and micro-structure of the architecture, and a surrogate-assisted multiobjective evolutionary based algorithm that efficiently searches for the best hyperparameters using a Random Forest surrogate and guiding selection probabilities. EMONAS is evaluated on the task of 3D cardiac segmentation from the MICCAI ACDC challenge, which is crucial for disease diagnosis, risk evaluation, and therapy decision. The architecture found with EMONAS is ranked within the top 10 submissions of the challenge in all evaluation metrics, performing better or comparable to other approaches while reducing the search time by more than 50% and having considerably fewer number of parameters. Copyright © 2020, The Authors. All rights reserved.

关键词： Multiobjective optimization

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Prediction of adverse events in Afghanistan: regression analysis of time series data grouped not by geographic dependencies.

arXiv

引用

arXiv 2020年

作者： Fiok, Krzysztof Karwowski, Waldemar Wilamowski, Maciej University of Central Florida Department of Industrial Engineering and Management Systems OrlandoFL United States University of Warsaw Faculty of Economic Sciences Warsaw Poland

The aim of this study was to approach a difficult regression task on highly unbalanced data regarding active theater of war in Afghanistan. Our focus was set on predicting the negative events number without distinguishing precise nature of the events given historical data on investment and negative events per each of predefined 400 Afghanistan’s districts. In contrast with previous research on the matter, we propose an approach to analysis of time series data that benefits from non-conventional aggregation of these territorial entities. By carrying out initial exploratory data analysis we demonstrate that dividing data according to our proposal allows to identify strong trend and seasonal components in the selected target variable. Utilizing this approach we also tried to estimate which data regarding investments is most important for prediction performance. Based on our exploratory analysis and previous research we prepared 5 sets of independent variables that were fed to 3 machine learning regression models. The results expressed by mean absolute and mean square errors indicate that leveraging historical data regarding target variable allows for reasonable performance, however unfortunately other proposed independent variables doesn’t seem to improve prediction quality. Copyright © 2020, The Authors. All rights reserved.

关键词： Time series

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Dynamic hesitant fuzzy linguistic group decision-making from a reliability perspective

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Journal of systems engineering and Electronics 2018年第5期29卷 1009-1021页

作者： MA Zhenzhen PONNAMBALAM Kumaraswamy ZHU Jianjun ZHANG Shitao College of Economics and Management Nanjing University of Aeronautics and Astronautics Department of Systems Design Engineering University of Waterloo School of Mathematics & Physics Science and Engineering Anhui University of Technology

A dynamic hesitant fuzzy linguistic group decisionmaking(DHFLGDM) problem is studied from the perspective of information reliability based on the theory of hesitant fuzzy linguistic term sets(HFLTSs). First, an approach is applied to transform the dynamic HFLTSs(DHFLTSs) into a set of proportional linguistic terms to eliminate the time dimension. Second, expert reliability is measured by considering both group similarity and degree of certainty, and an optimization method is employed to quantify the linguistic terms by maximizing the group similarity. Third, through computing the attribute stability as well as its reliability, a combination rule which considers both reliability and weight is proposed to aggregate the information, and then the aggregated grade values and degree of stability are used to make a selection. Finally,the application and feasibility of the proposed method are verified through a case study and method comparison.

关键词： dynamic decision-making hesitant fuzzy linguistic term sets(HFLTSs) proportional linguistic terms group similarity degree of certainty

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