Hybrid Systems Science, Modeling and Simulation for Health Policy: Collected Videos, Slides and Example Models

This page provides video explaining the significance of and compelling role played by hybrid systems science dynamic modeling techniques, and then provides a series of sections that survey different compelling ways of combining different systems science methodologies. These sections include videos showing the step-by-step creation of relevant hybrid health science models in the software package AnyLogic 7, as well as links to hybrid models for that software. Additional resources -- including a much more extensive library of hybrid models created by the author -- are provided at the bottom of the page.

To download the models on this page, please right-click (Option Click on Macs) on the link, and indicate that you'd like

Visitors to this page may be interested in the extensive coverage of step-by-step hybrid modeling included in our Agent-Based and Hybrid Modeling Bootcamp & Incubator for Health Researchers 2015, running August 24-29, 2015. Our on-line registration system is now available. Click here for additional information.

Orientation and Motivation

While each Systems Science technique approach can confer great value when applied in isolation, there are significant, textured and varied tradeoffs that obtain between the methods when applying dynamic modeling approaches to particular problems. Associated considerations -- which run the gamut from the capacity to capture longitudinal data, represent situated and localized decision-making, representing aspects network, spatial or multi-level context to communication barriers with stakeholders to performance challenges to human resource and skill sets -- mean that the modeling approach best suited to characterizing one component of a system is sometimes poorly suited to others. Attempting to force-fit a single modeling approach onto the modeling effort can lead to diverse adverse outcomes, including -- but not limited to -- inability to investigate important issues of interest, difficulty in adequately characterizing intervention strategies, and models that are inflexible, or opaque and alienating to stakeholders. Within recent years, advances in modeling technology have opened the door to far more ready creation of hybrid and multi-scale models. In successive problems in diverse domains, such models offer greater capacity to respond to modeler intention, and capable of more precisely addressing research questions involved, as well as more adaptive to changes in modeling priorities and scope in light of model-related learning, easier to understand and communicate, and more flexible and versatile. In many models, the hybrid approach supports understanding in excess of what would be gained with independent and parallel pursuit of modeling in each distinct modeling approach, and sometimes likely greater than the sum of the insights that could be secured collectively from several single-approach investigations.

Introductory Video: Hybrid Systems Science Modeling: Powerful Motivations and Compelling Patterns


Hybrids between Agent-Based Modeling and System Dynamics

Hybrids between ABM and SD commonly include cases where

Individuals flowing from System Dynamics into Agent-Based Model

Models (right-click and indicate "Save" to download)

BuddingHybridSDABMModel

Lectures

Model Name & Video Domain Stylistically Illustrated Key features illustrated Model Link (if available) General notes
Budding ABM System Dynamics Hybrid (System Dynamics stock flowing into agent-based model); laterally connected System Dynamics and Agent-Based model Chronic Disease Stocks flow into agents once a certain point in a risk continuum is reached BuddingHybridSDABMModel Broad tradeoffs
Hybrid Lateral Model between System Dynamics and Agent-Based ("Budding" of agents) Chronic Disease Stocks flow into agents once a certain point in a risk continuum is reached None Broad tradeoffs

Agent-Based modeling drives higher-level System Dynamics flows

Models(right-click and indicate "Save" to download)

BasicHealthEconomicsABMAnyLogic7

Lectures

Model Name & Video Domain Stylistically Illustrated Key features illustrated Model Link (if available) General notes
Hybrid Systems Science Model Capturing Health Economics Concepts Health Economics High-level structure summarizing history of agent population BasicHealthEconomicsABMAnyLogic7 Broad tradeoffs
Basic Health Economics Structures in AnyLogic 1 Health Economics High-level structure for QALYs, LYs, discounted and undiscounted cost, summarizing lower level agent population None Broad tradeoffs
Basic Health Economics Structures in AnyLogic 2 Health Economics None Broad tradeoffs
Basic Health Economics Structures in AnyLogic 3 Health Economics Putting in place mechanisms for computation of incremental cost effectiveness ratio (ICER) on basis of agent-based population and stocks and flows accumulating population-wide quantities None Broad tradeoffs

System Dynamics within Agents

Models (right-click and indicate "Save" to download)

IntroductoryTeachingGDMV4

CTL_State_Variable_UseAnylogic7

EnvironmentalContaminationHybrid

GriddedSystemDynamicsUsingAnylogic7

GriddedSystemDynamicsWithEditBoxtestAnylogic7

Lectures

Model Name & Video Domain Stylistically Illustrated Key features illustrated Model Link (if available) General notes
Hybrid Agent Based Modeling and System Dynamics, System Dynamics Governing Part of Agent Dynamics Continuous dynamics within agents achieved by System Dynamics CTL_State_Variable_UseAnylogic7 Broad tradeoffs
Hybrid Modeling 1: System Dynamics & Agent Based None
More Hybrid System Dynamics & Agent Based None
Hybrid Modeling 1: System Dynamics & Agent Based None
System Dynamics within Agents Building a Hybrid SD-ABM Mobility & Environmental Contamination Model in AnyLogic 7 Environmental Epidemiology and Communicable Illness Dynamics of pathogen reservoirs EnvironmentalContaminationHybrid Broad tradeoffs
Some Additional Hybrid Models: System Dynamics within each patch of an agent-based model Zoonoses; dynamics of reservoir populations

GriddedSystemDynamicsUsingAnylogic7

GriddedSystemDynamicsWithEditBoxtestAnylogic7

Hybrid Agent Based Modeling and System Dynamics, System Dynamics within Geographic Patches as Agent Zoonoses; dynamics of reservoir populations GriddedSystemDynamicsUsingAnylogic7 Poor audio quality
Hybrid Agent Based Modeling and System Dynamics, Agent Population with Aggregate Stocks and Flows
Hybrid Model With System Dynamics in Agents

Agent-Based modeling alongside discrete event modeling

Models

ABMDESMultiClinicModelAdelaide2015

RandomClinicsABMProcessHybrid

HybridABMNetworkModelingUsingAnylogic7

Agents circulate both in population and in discrete event model of a service process

Model Name & Video Domain Stylistically Illustrated Key features illustrated Model Link (if available) General notes
Introduction to AnyLogic Discrete Event Modeling and Hybrid Discrete Event and Agent Based Modeling Epidemiology & Health Services Research
MultiClinic ABM Process Hybrid Epidemiology & Health Services Research

ABMDESMultiClinicModelAdelaide2015

RandomClinicsABMProcessHybrid

Hybrid Model Combining Agent Based Modeling and Discrete Event Simulation Epidemiology & Health Services Research
Hybrid ABM Discrete Event Modeling (could also be called Hybrid ABM Network Modeling, ABM-Process-Oriented Modeling, ABM-Process-Flow Modeling) Epidemiology & Health Services Research
Hybrid ABM Discrete Event Modeling (could also be called Hybrid ABM Network Modeling, ABM-Process-Oriented Modeling, ABM-Process-Flow Modeling) Epidemiology & Health Services Research Hybrid of Agent-Based Modeling and Process Flow modeling, Association of a hospital or healthcare facility with a population, individuals present for care and are treated by health care workers; treatment can yield a 'cure' or adverse health outcomes (here, death); entities are associated with agents, and the agents can be updated in the course of treatment.

Hybrid of simulation modeling (for whatever tradition) and decision analysis for adaptive decision making.

Dynamically complex decision problems strongly encourage adaptive decision making that takes into account complex dynamics of the system. Decision analysis captures space of uncertainties and decisions over time; the simulation model captures the dynamic complexity of the system given a specific sequence of decisions and events over time.

Lectures

Model Name & Video Domain Stylistically Illustrated Key features illustrated Model Link (if available) General notes
Combining Decision Analysis and Dynamic Modeling Dynamically complex decisions problem Hybrid with Decision Analysis
Combining Decision Analysis and Dynamic Modeling Dynamically complex decisions problem Hybrid with Decision Analysis
Hybridizing Decision Analysis and Simulation Dynamically complex decisions problem Hybrid with Decision Analysis
Hybridizing Decision Analysis and Simulation: Another take Dynamically complex decisions problem Hybrid with Decision Analysis
Hybrid Models in AnyLogic 7 Epidemiology & Health Services Research

Tripartite Hybrid Model combining Agent Based Modeling, System Dynamics and Discrete Event Simulation

Models (right-click and indicate "Save" to download)

Tripartite Hybrid Model combining Agent Based Modeling, System Dynamics and Discrete Event Simulation

Lectures

Model Name & Video Domain Stylistically Illustrated Key features illustrated Model Link (if available) General notes
Tripartite Hybrid Model combining Agent Based Modeling, System Dynamics and Discrete Event Simulation Health Economics High-level structure summarizing lower level details None Broad tradeoffs

Understanding Unique Contributions of System Science Dynamic Modeling Methodologies

Interested visitors are recommended to see our page on unique contributions of each of 3 major dynamic modeling approaches (System Dynamics, Agent-Based Modeling, Discrete Event Modeling)


Library of Additional Hybrid Models

Those interested in securing access to additional hybrid systems science models for Health in AnyLogic are recommended to visit our hybrid systems science example models for health page.


Other material of interest

Those interested in example systems science for health models are further recommended to visit our AnyLogic 7 Example Models for Health folder on google drive, which provides dozens such models..

Materials on Agent-Based modeling for health policy using AnyLogic.

Materials from a previous full semester course on System Dynamics modeling for health policy using stock and flow models.

Reuse of Material

I have placed this information online in hopes that it will be of useful to a broader set of people. Users are welcome to distribute links to this page without restriction. I grant rights of non-commercial reuse (including reposting) of the material I have created for educational purposes, as long as it doesn't conflict with the rights of any other individuals.

If you are seeking to reuse this material, just drop me a brief email notification (osgood 'at' cs.usask.ca) to let me know of your planned use, and I request the courtesy of a citation with the repost indicating the original source of materials. I am especially interested in staying in touch with other educators who adopt components of the class material above for use in their own courses. Among other benefits, sending along your address will allow me to notify you of significant updates, of supplemental artifacts (e.g. models) that may be of interest, and could allow for exchange of ideas and suggestions on improving the material.

Please be encouraged to write me if there are any topics on which you feel additional tutorials would be useful.