Agent-based model
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BACKGROUND: Alzheimer's disease is one of the most common mental illnesses. It is posited that more than 25% of the population is affected by some mental disease during their lifetime. Treatment of each patient draws resources from the economy concerned. Therefore, it is important to quantify the potential economic impact. METHODS: Agent-based, system dynamics and numerical approaches to dynamic modeling of the population of the European Union and its patients with Alzheimer's disease are presented in this article. Simulations, their characteristics, and the results from different modeling tools are compared. RESULTS: The results of these approaches are compared with EU population growth predictions from the statistical office of the EU by Eurostat. The methodology of a creation of the models is described and all three modeling approaches are compared. The suitability of each modeling approach for the population modeling is discussed. CONCLUSION: In this case study, all three approaches gave us the results corresponding with the EU population prediction. Moreover, we were able to predict the number of patients with AD and, based on the modeling method, we were also able to monitor different characteristics of the population.
- MeSH
- Alzheimerova nemoc diagnóza epidemiologie MeSH
- biologické modely MeSH
- lidé MeSH
- systémová analýza * MeSH
- teoretické modely * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: Our purpose is to assess epidemiological agent-based models-or ABMs-of the SARS-CoV-2 pandemic methodologically. The rapid spread of the outbreak requires fast-paced decision-making regarding mitigation measures. However, the evidence for the efficacy of non-pharmaceutical interventions such as imposed social distancing and school or workplace closures is scarce: few observational studies use quasi-experimental research designs, and conducting randomized controlled trials seems infeasible. Additionally, evidence from the previous coronavirus outbreaks of SARS and MERS lacks external validity, given the significant differences in contagiousness of those pathogens relative to SARS-CoV-2. To address the pressing policy questions that have emerged as a result of COVID-19, epidemiologists have produced numerous models that range from simple compartmental models to highly advanced agent-based models. These models have been criticized for involving simplifications and lacking empirical support for their assumptions. METHODS: To address these voices and methodologically appraise epidemiological ABMs, we consider AceMod (the model of the COVID-19 epidemic in Australia) as a case study of the modelling practice. RESULTS: Our example shows that, although epidemiological ABMs involve simplifications of various sorts, the key characteristics of social interactions and the spread of SARS-CoV-2 are represented sufficiently accurately. This is the case because these modellers treat empirical results as inputs for constructing modelling assumptions and rules that the agents follow; and they use calibration to assert the adequacy to benchmark variables. CONCLUSIONS: Given this, we claim that the best epidemiological ABMs are models of actual mechanisms and deliver both mechanistic and difference-making evidence. Consequently, they may also adequately describe the effects of possible interventions. Finally, we discuss the limitations of ABMs and put forward policy recommendations.
Agent-based models (ABMs) are one of the main sources of evidence for decisions regarding mitigation and suppression measures against the spread of SARS-CoV-2. These models have not been previously included in the hierarchy of evidence put forth by the evidence-based medicine movement, which prioritizes those research methods that deliver results less susceptible to the risk of confounding. We point out the need to assess the quality of evidence delivered by ABMs and ask the question of what is the risk that assumptions entertained in ABMs do not include all the key factors and make model predictions susceptible to the problem of confounding.
- MeSH
- COVID-19 epidemiologie MeSH
- lidé MeSH
- pandemie * MeSH
- SARS-CoV-2 fyziologie MeSH
- systémová analýza * MeSH
- teoretické modely MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Clinical microbiology and infection, ISSN 1198-743X Volume 11, supplement 5, October 2005
38 stran : ilustrace, tabulky ; 28 cm
- MeSH
- systémová analýza MeSH
- teoretické modely MeSH
- zdravotnická zařízení - velikost MeSH
- zdravotnické plánování MeSH
- Geografické názvy
- Československo MeSH
Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the-server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models.
- MeSH
- ekonomické modely MeSH
- lidé MeSH
- metody pro podporu rozhodování MeSH
- rozhodování * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Využití znalostí ve formě postupů, konkrétně organizačních procesů a formalizovaných lékařských doporučení, může být vhodné pro vytvoření znalostní báze systému pro podporu v rozhodování (DSS) v oblasti poskytování zdravotní péče. Problém nastává v případě, že pro vývoj DSS chceme použít multiagentní přístup z důvodu rozdílů mezi formalizací chováním se agentů a procesním zápisem. V tomto příspěvku pokračujeme v práci na nové multiagentní architektuře a představíme její integraci do stávajícího systému na podporu v rozhodování (K4Care) v oblasti domácí péče. Základní metodou byla analýza dostupné dokumentace ke komplexnímu systému K4Care, na jejímž základě jsme identifikovali společná místa v rámci již existující funkcionality a návrhu nové architektury. Ta dále posloužila jako výchozí body pro vylepšení modelu K4Care s ohledem na novou multiagentní architekturu založenou na procesech. Analýza potvrdila nejen možnost takové integrace, ale také její přímočarost a minimum nutných změn v modelu K4Care díky dostatečně obecnému návrhu multiagentní architektury založené na procesech. Na základě integrace byly identifikovány okamžité vylepšení podporující lidského experta při jeho práci se systémem, jakož i možnosti dalšího rozšíření systému K4Care na základě této integrace. Integrace multiagentní architektury může být přínosná i pro stávající systémy pro podporu v rozhodování a díky ní otevře nové možnosti založené na multiagentním přístupu.
Utilization of procedural knowledge in the form of organizational processes and formalized medical guidelines can be useful in decision support systems (DSSs) in health care domain. The problem of using this form of knowledge arises when a multi-agent paradigm is to be applied in a DSS due to differences in specification of behavioural models of agents and process formalisms. In this work we continue in enhancing a novel process-based multi-agent architecture and demonstrate its integration into an existing DSS (K4care) focused on home care. We analysed available documentation of the complex system K4Care and identified possible mutual common functionalities of implemented multi-agent system with the new architecture. These were the entry points, using which we further enhanced the K4Care platform with respect to the process-based multi-agent architecture. The analysis proved that the integration is not only possible, but thanks to the general design of the process-based multi-agent architecture can be done with only small changes in the existing K4Care model. Immediate improvements in supporting human experts were identified and possible further improvements of the system were discussed. Adopting the process-based multi-agent architecture can be beneficial even for existing DSSs and can open new possible features emerging from the multi-agent paradigm.
- Klíčová slova
- multiagentní systémy, multiagentní architektury, organizační procesy, formalizované lékařské doporučení, zdravotní péče, domácí péče K4Care,
- MeSH
- financování organizované MeSH
- lidé MeSH
- metody pro podporu rozhodování MeSH
- služby domácí péče MeSH
- software MeSH
- systémy podporující rozhodování v léčbě využití MeSH
- systémy pro podporu klinického rozhodování využití MeSH
- zajištění kvality zdravotní péče metody MeSH
- Check Tag
- lidé MeSH
Simul 5 Complex is a one-dimensional dynamic simulation software designed for electrophoresis, and it is based on a numerical solution of the governing equations, which include electromigration, diffusion and acid-base equilibria. A new mathematical model has been derived and implemented that extends the simulation capabilities of the program by complexation equilibria. The simulation can be set up with any number of constituents (analytes), which are complexed by one complex-forming agent (ligand). The complexation stoichiometry is 1:1, which is typical for systems containing cyclodextrins as the ligand. Both the analytes and the ligand can have multiple dissociation states. Simul 5 Complex with the complexation mode runs under Windows and can be freely downloaded from our web page http://natur.cuni.cz/gas. The article has two separate parts. Here, the mathematical model is derived and tested by simulating the published results obtained by several methods used for the determination of complexation equilibrium constants: affinity capillary electrophoresis, vacancy affinity capillary electrophoresis, Hummel-Dreyer method, vacancy peak method, frontal analysis, and frontal analysis continuous capillary electrophoresis. In the second part of the paper, the agreement of the simulated and the experimental data is shown and discussed.
