Hybrid Simulation in Healthcare: New Concepts and New Tools Sally C. Brailsford

Until relatively recently, developing hybrid simulation models using more than one simulation paradigm was a challenging task which required a degree of ingenuity on behalf of the modeler. Generally speaking, such hybrid models either had to be coded from scratch in a programming language, or developed using two (or more) different off-the-shelf software tools which had to communicate with each other through a user-written interface. Nowadays a number of simulation tools are available which aim to make this task easier. This paper does not set out to be a formal review of such software, but it discusses the increasing popularity of hybrid simulation and the rapidly developing market in hybrid modeling tools, focusing specifically on applications in health and social care and using experience from the Care Life Cycle project and elsewhere.
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Towards a Guide to Domain-specific Hybrid Simulation Anatoli Djanatliev, Reinhard German

The advantages of combined simulation techniques have been already frequently discussed and are well-covered by the recently published literature. In particular, many case studies have been presented solving similar domain-specific problems by different multi-paradigm simulation approaches. Moreover, a number of papers exist focusing on theoretical and conceptual aspects of hybrid simulation. However, it still remains a challenge to decide, whether combined methods are appropriate in certain situations and how they can be applied. Therefore, domain-specific user guides for multi-paradigm modeling are required combining general concepts and best practices to common steps. In this paper, we particularly outline three major processes targeting to define structured hybrid approaches in domain-specific contexts, and we focus on some practical issues aiming to a sustainable model development. Finally, an example hybrid methodology for problems in healthcare will be presented.
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Agent-based population model used to identify and evaluate dog population management strategies L. Kisiel, A. Jones-Bitton, A.L. Greer; Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON Canada; CEFUTREMA

Developing countries are faced with finding novel and humane ways to permanently reduce and control their dog population. Agent-based models developed to describe dog populations represent a unique, platform for using computer based simulation to identify control strategies with the greatest potential for success, aid in the design of more effective control measures, and provide a means to evaluate the success of different interventions.
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The Effect of Cellular Interactions on Cancer Cell Growth Using Evolutionary Game Theory Mihir Paithane, Student, Science, Technology, Engineering, and Math (STEM) Center at Mills E. Godwin High School

In this experiment, game theory was used to assess the interactions between three cell phenotypes usually found in cancer. The three defined cells were autonomous growth cells, invasive and motile malignant cells, and cells that performed anaerobic glycolysis. Based on preset variables in the payoff matrix, analytical equations were deduced that allowed for the analysis of the proportion of autonomous growth and malignant cells in a tumor. AnyLogic was also used to simulate the interactions between cancerous and normal cells.
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Partial Paradigm Hiding and Reusability in Hybrid Simulation Modeling Using the Frameworks Health-DS and I7-Anyenergy A. Djanatliev, P. Bazan, R. German, University of Erlangen-Nuremberg. Winter Simulation Conference, 2014.

Many complex real-world problems which are difficult to understand can be solved by discrete or continuous simulation techniques, such as Discrete-Event-Simulation, Agent-Based-Simulation or System Dynamics. In recently published literature, various multilevel and large-scale hybrid simulation examples have been presented that combine different approaches in common environments.
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A Tripartite Hybrid Model Architecture for Investigating Health and Cost Impacts and Intervention Tradeoffs for Diabetic End-stage Renal Disease Amy Gao, Nathaniel D. Osgood, Wenyi An, Roland F. Dyck. Winter Simulation Conference, 2014.

Like most countries, Canada faces rising rates of diabetes and diabetic ESRD, which adversely affect cost, morbidity/mortality and quality of life. These trends raise great challenges for financial, human resource and facility planning and place a premium on understanding tradeoffs between different intervention strategies. We describe here our hybrid simulation model built to inform such efforts.
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Reflections on Two Approaches to Hybrid Simulation in Healthcare Joe Viana, University of Southampton. Winter Simulation Conference, 2014.

Hybrid simulation, the combination of simulation paradigms to address a problem is becoming more popular as the problems we are presented with become more complex. This is evidenced by an increase in the number of hybrid papers published in specific domains and the number of hybrid simulation frameworks being produced across domains.
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Towards Closed Loop Modeling: Evaluatng The Prospects for Creating Recurrently Regrounded Aggregate Simulation Models Using Particle Filtering Nathaniel Osgood, Juxin Liu, University of Saskatchewan 106 Wiggins Road, University of Saskatchewan Saskatoon. Winter Simulation Conference, 2014

Public health agencies traditionally rely heavily on epidemiological reporting for notifiable disease control, but increasingly apply simulation models for forecasting and to understand intervention tradeoffs. Unfortunately, such models traditionally lack capacity to easily incorporate information from epidemiological data feeds.
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An Agent-Based Explanation for 20th Century Living Situation Changes in America’s Severely and Persistently Mentally Ill Population Kyle L. Johnson, Dr. Dimitris Alevras, IBM Global Business Services; Dr. John Docherty, Dr. Erin Falconer, Otsuka Medical Affairs. AnyLogic Conference 2014

The largest public mental health facility in the United States is not a hospital; it is the Los Angeles County Jail. This paper describes an agent-based approach to explaining why prisons and jails house so many of America’s most seriously mentally ill. It traces this fact to the differing ways in which various housing situations react to mental illness and to legislation passed in the 1960’s, which allocated public funding away from state mental hospitals.
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Comparison between Individual-based and Aggregate Models in the context of Tuberculosis Transmission Tian, Y. and Osgood, N., Proceedings, The 29 th International conference of the System Dynamics Society. July 2011, Washington, D.C.

The desire to better understand the transmission of infectious disease in the real world has motivated the representation of epidemic diffusion in the context of quantitative simulation. In recent decades, both individual-based (such as Agent-Based) models and aggregate models (such as System Dynamics) are widely used in epidemiological modeling. This paper compares the difference between system dynamics models and agent-based models in the context of Tuberculosis (TB) transmission, considering smoking as a risk factor.
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