An introduction to agent-based models for public health
Complexity and agent-based modelling
Dr Corinna Elsenbroich, University of Glasgow
Agent-based modelling is a computational method that can simulate social processes by replicating behaviours of individuals in silico. This webinar, presented by Dr Corinna Elsenbroich, explores the ways agent-based models can help us explore the complexity of the social world.
Justified Stories: formalising “what if?” for policy modelling
Dr Jen Badham, Durham University
Dr Jennifer Badham presents JuSt-Social, an agent-based model developed to support local planners in North East England in the first year of the COVID-19 pandemic. The presentation focuses on the changing way in which policymakers used the model as the epidemic developed and the role of agent-based models as a tool for thinking.
Understanding agent-based models for public health
Dr Ricardo Colasanti, University of Glasgow
Dr Ricardo Colasanti discusses different types of agent-based models and demonstrates how these can be applied to address a variety of public health challenges using interactive case study examples.
Agent-based models for health improvement
Using simulations to inform tobacco control policies
Tobacco Town: Applying Agent-based Modeling to Tobacco Regulatory Science
Dr Ross Hammond, Brown School at Washington University in St. Louis
Social contagion models for tobacco control
Dr Valerio Restocchi, University of Edinburgh
Modelling the interactions between urban development and physical activity
Synergies between large-scale urban changes for physical activity promotion and the UN Sustainable Development Goals
Dr Leandro Garcia, Queen’s University Belfast
ABM-based land use-transport interaction simulation: Healthier urban development and healthier travel behaviour
Dr Heeseo Rain Kwon, University College London
Employment, welfare and health: insights from agent-based models
NCDESim: An agent-based model of health and employment
Dr Patryk Bronka, University of Essex
Growing a semi-artificial population for social and public health simulations: an application to informal social care provision
Dr Umberto Gostoli, University of Glasgow
What can simulation models tell us about the risk factors for cardiovascular disease?
Cardiovascular disease epidemiology and prevention
Prof. Simon Capewell, University of Liverpool
Prevention of NCD: understanding how powerful prevention can be
Prof. Martin O’Flaherty, University of Liverpool
Modelling the spread of multiple behavioural risk factors for cardiovascular disease in social networks using an agent-based model
Prof. Nathan Griffiths, University of Warwick
Using agent-based models to explore food behaviour and food advertising in obesity research
Capturing eating behaviours in agent-based models: innovative methods and data limitations
Prof. Philippe Giabbanelli, Miami University
Exploring the relationship between food advertising and consumption of foods high in fat, salt and sugar in England: an agent-based model
Dr Charlotte Buckley, University of Sheffield
Apologies for the audio issues for the first two minutes of the recording. This is due to a faulty microphone. Please note that the audio improves for the presentations.
Early Career Researcher Seminar: Agent-based models for public health
MOTIVATE: Incorporating social norms into a configurable agent-based model of the decision to perform commuting behaviour
Robert Greener, London School of Hygiene and Tropical Medicine
Robert talks about “MOTIVATE”, a configurable agent-based model used to simulate how changing social norms affect interventions, such as car-free days, in a case-study of Waltham Forest, a North-Eastern London Borough. In the model, manipulating habits and norms allow us to destabilise the convention of commuting by car, demonstrating its utility as a simulator of potential policies that may affect commuting-related norms.
Developing an agent-based model for collective patterns and income inequalities of leisure-time physical activity
Sophie Jones, Queen’s University Belfast
Sophie talks about an agent-based model developed as part of a PhD project at Queen’s University Belfast, aiming to explore collective patterns and income inequalities of leisure time physical activity in adults. The presentation focusses on demonstrating the model’s purpose, design, and development.
Simulating human mobility patterns for public health research with agent-based models
Hyesop Shin, University of Glasgow
Hyesop demonstrates how he has used agent-based models to simulate human mobility patterns, with examples of mobility in air pollution exposure and children’s physical activity in various playground shapes. He also discusses the perceptual differences between geographic information systems (GIS) and statistical researchers in order to facilitate mutual understanding and foster collaboration.
Social Simulation Week Webinar: Opportunities and challenges of modelling complex health behaviour
Thursday 17 September 2020
As part of Social Simulation Week 2020, hosted by ESSA and Behave Lab, PHASE hosted a webinar to discuss potential applications of ABM to address public health challenges and highlight key considerations when developing models of public health. Drawing on examples of ABM for adult social care and contact tracing, speakers examined issues such as model specification and obtaining suitable data for model calibration and sensitivity analysis, and discussed the role of cross-disciplinary partnerships involving health practitioners and decision makers in developing effective and useful models of public health and the ways in which PHASE aims to support these collaborations. You can see videos of all the sessions from Social Simulation Week 2020 on the Behave Lab website.
Help! Public health needs ABM [2:17-16:22]
Prof. Richard Mitchell, University of Glasgow
In this brief talk, I will use the current Covid-19 pandemic to illustrate why public health desperately needs ABMs to help understand and tackle the complex interactions between people and their environment. These interactions are crucial for infectious disease and for the bigger challenge; non-infectious disease. I’ll consider why public health hasn’t used ABM much before now and explore the kinds of questions that could be asked and answered.
Help, all my mechanisms are missing [22:13-49.05]
Dr Jennifer Badham, Visiting Scholar, Queen’s University Belfast
In this talk, I will argue that a key barrier to widespread adoption of agent-based modelling in public health is that mechanisms are missing from major behaviour theories. A mechanism focus could also help bridge disciplinary gaps.
ABM for Social Care Policy [55:47-1:18:41]
Dr Eric Silverman and Dr Umberto Gostoli, University of Glasgow
In this talk, we will present a model of social care provision which we have been developing in the last three years, with the aim to show how ABM can help us to develop models of societies characterized by a complex interaction between demographic, epidemiological and economic factors. We will show how, even in a situation of scarce data, these kinds of models can still be a valuable tool for policy makers to test social and economic policies in order to assess spill-over effects and unintended consequences before these policies are implemented in the real world.
An agent-based model of COVID-19 and the effectiveness of smartphone-based contact tracing [1:23:40-1:52:54]
Dr Jonatan Almagor and Dr Stefano Picascia, University of Glasgow
Using an agent-based model we simulate the transmission of COVID-19 in a population of agents on an urban scale to assess the feasibility of a smartphone-based track-and-trace strategy to mitigate the COVID-19 epidemic.
The Population Health Agent-based Simulation nEtwork (PHASE) [1:53:36-2:10:30]
Prof. Laurence Moore, Network Director, University of Glasgow
This talk will provide an introduction to the network vision and aims, followed by discussion session about research priorities and network activities.
Modelling Protocols and Standards
ODD (Overview, Design concepts, and Details) Protocol
The ODD protocol is a standard format for describing agent-based models. Since the protocol was introduced in 2006, several updates have been provided that aim to make it easier to use ODD and make model descriptions more useful and coherent.
A standard protocol for describing individual-based and agent-based models
V. Grimm, U. Berger, F. Bastiansen, et al.
Ecological Modelling 2006
The ODD protocol: A review and first update
V. Grimm, U. Berger, D.L. De Angelis, J.G. Polhill, S.F. Railsback
Ecological Modelling, 2010
Describing human decisions in agent-based models – ODD+D, an extension of the ODD protocol
B. Müller, F. Bohn, G. Dreßler, et al.
Environmental Modelling & Software, 2013
The ODD Protocol for Describing Agent-Based and Other Simulation Models: A Second Update to Improve Clarity, Replication, and Structural Realism
V. Grimm , S.F. Railsback , C.E. Vincenot, et al.
Journal of Artificial Societies and Social Simulation, 2020
TRACE (TRAnsparent and Comprehensive model Evaludation) Framework
Framework to support modellers to “trace” the iterative modelling process and document model development, testing and analysis.
Towards better modelling and decision support: documenting model development, testing, and analysis using TRACE
V. Grimm, J. Augusiak, A. Focks, et al.
Ecological modelling, 2014
Keeping modelling notebooks with TRACE: good for you and good for environmental research and management support
D. Ayllón, S.F.Railsback, C. Gallagher, et al.
Environmental modelling & Software, 2021
Community Standards for Modelling Science
Community standards coordinated through the Open Modelling Foundation that promote the creation and use of more reusable, replicable, interoperable, and reliable models. Standards cover model discoverability and accessibility; documentation; reusability and replicability; and interoperability.
CoMSES Net host community curated information on agent based modeling software frameworks, documentation standards, educational materials, and guides to good practice for developing and documenting computational models for reuse and reproducibility.
NetLogo is a free software tool that provides a multi-agent programmable modelling environment.
Complexity Explorer delivers a range of online courses, tutorials, and resources essential to the study of complex systems, including tutorials on NetLogo and agent-based simulation. Complexity Explorer is an education project of the Santa Fe Institute.
CECAN is working on methods and tools to improve the design and evaluation of policies related to the food, energy, water and environment ‘nexus’, and within areas where these issues interconnect in complex ways. They provide a range of resources around modelling of complex systems and policies, including some specific to agent-based modelling.
On-Line Guide for Newcomers to Agent-Based Modeling in the Social Sciences
Robert Axelrod and Leigh Tesfatsion