PHASE: The Population Health Agent based Simulation nEtwork
Lead Research Organisation:
University of Glasgow
Department Name: MRC Social & Public Health Services Unit
Abstract
Ideas that seemed like science fiction only a few years ago are now reality. Modern computers are powerful enough to simulate a city with millions of citizens inside a virtual world. We can learn how to improve health in the real world by studying "simulated populations" like this, and identifying how individual citizens, or "agents", within this virtual world interact with each other and how their health behaviours change when aspects of the simulated environment change.
The Population Health Agent-based Simulation nEtwork (PHASE) will bring together scientists, computer software developers, government workers, charity sector staff, and University researchers who are interested in improving the health of the population. By supporting different groups to work together, the UK will become a world leader in simulation methods for health, and will aim to tackle key public health issues like obesity, tobacco and alcohol use, and physical activity and exercise.
The PHASE network aims to:
1. Teach people how simulating individual and environmental factors and their influence on population health can improve our understanding of how to prevent non-communicable diseases.
2. Build stronger teams: putting together people that can create population simulations with scientific experts and those on the front line working in communities to improve public health.
3. Move science fiction to science fact: To get people around the UK talking about simulation methods for health, so that research funders, Universities, health workers and the public understand more about this 21st Century approach to improving health.
To achieve these aims, the network will hold meetings to get people talking about simulation methods and how these can be applied to public health problems, make new connections and build new teams. Training in simulation methods will be delivered through the network and expert network members will write reports and guidelines so a wide range of people can learn about the best way to use the simulation methods.
The network staff will develop an interactive website and online registry where people can find out:
Who is in the network and how to join?
What are the key health improvement issues?
What simulations are already developed and how can I use them?
In the long term, the PHASE network will increase the number of people across the UK who know about and understand simulation methods for health, and build a community of experts working in health improvement using these methods. Through network events and training we hope to build expert teams from a range of different backgrounds, working together to use simulations to tackle some of the major public health challenges facing us today.
The Population Health Agent-based Simulation nEtwork (PHASE) will bring together scientists, computer software developers, government workers, charity sector staff, and University researchers who are interested in improving the health of the population. By supporting different groups to work together, the UK will become a world leader in simulation methods for health, and will aim to tackle key public health issues like obesity, tobacco and alcohol use, and physical activity and exercise.
The PHASE network aims to:
1. Teach people how simulating individual and environmental factors and their influence on population health can improve our understanding of how to prevent non-communicable diseases.
2. Build stronger teams: putting together people that can create population simulations with scientific experts and those on the front line working in communities to improve public health.
3. Move science fiction to science fact: To get people around the UK talking about simulation methods for health, so that research funders, Universities, health workers and the public understand more about this 21st Century approach to improving health.
To achieve these aims, the network will hold meetings to get people talking about simulation methods and how these can be applied to public health problems, make new connections and build new teams. Training in simulation methods will be delivered through the network and expert network members will write reports and guidelines so a wide range of people can learn about the best way to use the simulation methods.
The network staff will develop an interactive website and online registry where people can find out:
Who is in the network and how to join?
What are the key health improvement issues?
What simulations are already developed and how can I use them?
In the long term, the PHASE network will increase the number of people across the UK who know about and understand simulation methods for health, and build a community of experts working in health improvement using these methods. Through network events and training we hope to build expert teams from a range of different backgrounds, working together to use simulations to tackle some of the major public health challenges facing us today.
Technical Summary
Major population health challenges including non-communicable diseases are not a product of simple, linear causal relationships, but of numerous interdependent and interacting processes, operating at multiple levels. In this context, population health research is increasingly adopting the complex systems perspective - a whole-system view centered on modelling the interactions between individuals and their social and physical environments. Agent-based modelling (ABM) is a complex systems simulation methodology that models individuals embedded in a physical and social environment, with their actions determined by simple decision rules. ABMs can model both individual health behaviours and their upstream determinants, enabling us to better understand the tangled web of processes that drive health and generate inequalities at the population level.
PHASE will facilitate the application of ABMs in population health through education, training and collaboration. Network activities will address issues of critical importance to enabling population health researchers and decision makers to apply ABMs: appropriate problem domains; best practices for model development; technical training; and ABM reporting guidelines. Working groups will develop documentation protocols, best-practice guidelines, and computational training. Our initial membership includes population health scientists, ABM specialists, health policy and practitioner groups and industrial collaborators, all of whom will be invited to contribute to our events and working groups. PHASE will also create an ABM study registry that will allow stakeholders to seek help with problems that may benefit from an ABM approach.
PHASE will particularly seek to engage with evidence users and researchers from multiple disciplines to generate new transdisciplinary teams that will apply ABMs to important challenges in the prevention of non-communicable disease.
This grant is funded by the UK Prevention Research Partnership (UKPRP) which is administered by the Medical Research Council on behalf of the UKPRP's 12 funding partners: British Heart Foundation; Cancer Research UK; Chief Scientist Office of the Scottish Government Health and Social Care Directorates; Engineering and Physical Sciences Research Council; Economic and Social Research Council; Health and Social Care Research and Development Division, Welsh Government; Health and Social Care Public Health Agency, Northern Ireland; Medical Research Council; Natural Environment Research Council; National Institute for Health Research; The Health Foundation; The Wellcome Trust.
PHASE will facilitate the application of ABMs in population health through education, training and collaboration. Network activities will address issues of critical importance to enabling population health researchers and decision makers to apply ABMs: appropriate problem domains; best practices for model development; technical training; and ABM reporting guidelines. Working groups will develop documentation protocols, best-practice guidelines, and computational training. Our initial membership includes population health scientists, ABM specialists, health policy and practitioner groups and industrial collaborators, all of whom will be invited to contribute to our events and working groups. PHASE will also create an ABM study registry that will allow stakeholders to seek help with problems that may benefit from an ABM approach.
PHASE will particularly seek to engage with evidence users and researchers from multiple disciplines to generate new transdisciplinary teams that will apply ABMs to important challenges in the prevention of non-communicable disease.
This grant is funded by the UK Prevention Research Partnership (UKPRP) which is administered by the Medical Research Council on behalf of the UKPRP's 12 funding partners: British Heart Foundation; Cancer Research UK; Chief Scientist Office of the Scottish Government Health and Social Care Directorates; Engineering and Physical Sciences Research Council; Economic and Social Research Council; Health and Social Care Research and Development Division, Welsh Government; Health and Social Care Public Health Agency, Northern Ireland; Medical Research Council; Natural Environment Research Council; National Institute for Health Research; The Health Foundation; The Wellcome Trust.
Planned Impact
Contribution of PHASE to planned UKPRP outcomes and impacts: The motivation and rationale for PHASE are underpinned by our vision to contribute to the achievement of UKPRP Impacts 21 (Evidence-based solutions) and 22 (Decreased health inequalities and redistribution of resources). We will do this by increasing the use of ABMs in co-productive transdisciplinary multi-sectoral teams that engage and influence decision makers (Outcome 17 and 18). The key impacts we expect to achieve within the award period relate to UKPRP Outcomes 8 (Sustained community), 10 (New methodology for systems approaches), 12 (New interdisciplinary research agenda) and 14 (Transdisciplinary research group capacity).
Our vision, to normalise the application and use of ABMs among researchers and decision makers in the primary prevention of NCDs, will be delivered through a Theory of Change informed by Normalisation Process Theory. This asserts that the widespread implementation in routine practice (normalisation) of new programmes/methods (eg. Complex systems aproaches and ABMs) is dependent on capacity, capability and potential.
Who will benefit and how?
Practitioners, policy-makers and multi-sectoral public and third sector organisations: these organisations will be the principal group of beneficiaries and are critical to the achievement of UKPRP and PHASE aims. We will seek to increase the capacity, capability and potential of these communities to adopt and apply ABMs by:
1. increasing their awareness and understanding of ABMs and how they can be a useful tool in conceptualising and modelling the complex 'wicked issues' they face every day;
2. increasing their knowledge of examples of the successful application of ABMs to NCD prevention;
3. providing access to resources and support;
4. facilitating accessibility to others working across multiple sectors with an interest in applying ABMs;
5. providing pump-priming funding for user-led transdisciplinary teams to develop ABM projects;
6. improving the transparency, reliability and reporting of ABMs.
Commercial sector: we have engaged with a number of industry partners who are already developing ABMs or providing software and hardware platforms for ABMs or large-scale simulations. PHASE will provide companies from the sector with the opportunity to identify academic and user partners to work with as collaborators or customers, and to inform them of product developments that may be required to meet the user requirements of ABM developers.
Public: The key long-term impact of UKPRP, to which PHASE will contribute, is the population prevention of NCDs and reduction in health inequalities. Our communications plan will aim to achieve a better public understanding of the multiple, interdependent factors that underlie the rising incidence of NCDs and the need for complex systems informed interventions at multiple levels. PPI will be required in Research Development Groups awarded PHASE pump-priming funds.
Research funders and journal editors: PHASE will seek to increase research funding for ABMs to increase capacity in the field, and to promote publications of high quality ABMs in high impact health journals. This will be achieved through increasing funders' and journals' potential and capability to recognise and evaluate the quality and importance of ABMs by, for example, using our reporting guidance and our register as markers of high standards.
Researchers from other disciplines: we will seek to engage and learn from scientists from other disciplines who have greater experience in applying complex systems in general and ABMs in particular. An impact on them will be benefit to their research methods and practice through learning from population health scientists and the central importance of health and wellbeing in addressing applied research questions in other sectors.
Our vision, to normalise the application and use of ABMs among researchers and decision makers in the primary prevention of NCDs, will be delivered through a Theory of Change informed by Normalisation Process Theory. This asserts that the widespread implementation in routine practice (normalisation) of new programmes/methods (eg. Complex systems aproaches and ABMs) is dependent on capacity, capability and potential.
Who will benefit and how?
Practitioners, policy-makers and multi-sectoral public and third sector organisations: these organisations will be the principal group of beneficiaries and are critical to the achievement of UKPRP and PHASE aims. We will seek to increase the capacity, capability and potential of these communities to adopt and apply ABMs by:
1. increasing their awareness and understanding of ABMs and how they can be a useful tool in conceptualising and modelling the complex 'wicked issues' they face every day;
2. increasing their knowledge of examples of the successful application of ABMs to NCD prevention;
3. providing access to resources and support;
4. facilitating accessibility to others working across multiple sectors with an interest in applying ABMs;
5. providing pump-priming funding for user-led transdisciplinary teams to develop ABM projects;
6. improving the transparency, reliability and reporting of ABMs.
Commercial sector: we have engaged with a number of industry partners who are already developing ABMs or providing software and hardware platforms for ABMs or large-scale simulations. PHASE will provide companies from the sector with the opportunity to identify academic and user partners to work with as collaborators or customers, and to inform them of product developments that may be required to meet the user requirements of ABM developers.
Public: The key long-term impact of UKPRP, to which PHASE will contribute, is the population prevention of NCDs and reduction in health inequalities. Our communications plan will aim to achieve a better public understanding of the multiple, interdependent factors that underlie the rising incidence of NCDs and the need for complex systems informed interventions at multiple levels. PPI will be required in Research Development Groups awarded PHASE pump-priming funds.
Research funders and journal editors: PHASE will seek to increase research funding for ABMs to increase capacity in the field, and to promote publications of high quality ABMs in high impact health journals. This will be achieved through increasing funders' and journals' potential and capability to recognise and evaluate the quality and importance of ABMs by, for example, using our reporting guidance and our register as markers of high standards.
Researchers from other disciplines: we will seek to engage and learn from scientists from other disciplines who have greater experience in applying complex systems in general and ABMs in particular. An impact on them will be benefit to their research methods and practice through learning from population health scientists and the central importance of health and wellbeing in addressing applied research questions in other sectors.
Organisations
- University of Glasgow (Lead Research Organisation)
- Macquarie University (Collaboration)
- University of Manchester (Collaboration)
- UNIVERSITY OF READING (Collaboration)
- Greater Manchester Combined Authority (Collaboration)
- COVENTRY CITY COUNCIL (Collaboration)
- University of Warwick (Collaboration)
- Public Health Scotland (Collaboration)
- QUEEN MARY UNIVERSITY OF LONDON (Collaboration)
- UNIVERSITY OF EDINBURGH (Collaboration)
- University of Sheffield (Collaboration)
- UNIVERSITY OF GLASGOW (Collaboration)
- NVIDIA (Collaboration)
- Government of Scotland (Collaboration)
- UNIVERSITY OF LIVERPOOL (Collaboration)
- UNIVERSITY OF ESSEX (Collaboration)
- Drexel University (Collaboration)
Publications
Badham J
(2021)
Network structure influence on simulated network interventions for behaviour change
in Social Networks
Badham J
(2019)
Effectiveness variation in simulated school-based network interventions
in Applied Network Science
Breeze PR
(2023)
Guidance on the use of complex systems models for economic evaluations of public health interventions.
in Health economics
Bryden J
(2022)
Modelling transitions between egalitarian, dynamic leader and absolutist power structures.
in PloS one
Gostoli U
(2019)
Modelling social care provision in an agent-based framework with kinship networks.
in Royal Society open science
Gostoli U
(2020)
Social and child care provision in kinship networks: An agent-based model.
in PloS one
Silverman E
(2020)
Situating Agent-Based Modelling in Population Health Research
Silverman E
(2021)
Situating agent-based modelling in population health research.
in Emerging themes in epidemiology
Silverman E
(2021)
PHASE: Facilitating Agent-Based Modelling in Population Health
Description | Invited Speaker, Agent Based Modelling for Policy Webinar, 5th October 2020 |
Geographic Reach | Multiple continents/international |
Policy Influence Type | Influenced training of practitioners or researchers |
Description | UKPRP Network Grant (Laurence Moore) |
Amount | £402,311 (GBP) |
Funding ID | MR/S037594/1 |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 05/2019 |
End | 05/2023 |
Title | Agent based model of COVID19 spread with digital contact tracing (version 1.0.0) |
Description | Multi-layer network agent-based model of the progression of the COVID19 infection, digital contact tracing |
Type Of Material | Computer model/algorithm |
Year Produced | 2021 |
Provided To Others? | Yes |
Impact | https://www.nature.com/articles/s41598-020-79000-y |
URL | https://www.comses.net/codebases/d1013f71-b7e0-45aa-9f42-870c8793895b/releases/1.0.0/ |
Title | MUGS - Model of Urban Green Spaces (version 0.5.9) |
Description | Abstract model investigating the determinants of inter- and intra-urban inequality in contact with nature. We explore the plausibility of a social integration hypothesis - whereby the primary factor in decisions to visit Urban Green Spaces (UGS) is an assessment of who else is likely to be using the space at the same time, and the assessment runs predominantly along class lines. The model simulates four cities in Scotland and shows the conditions under which the mechanisms theorised are sufficient to reproduce observed inequalities in UGS usage. |
Type Of Material | Computer model/algorithm |
Year Produced | 2021 |
Provided To Others? | Yes |
Impact | None as yet but interest from agencies. |
URL | https://www.comses.net/codebases/99b2b351-dd51-47dc-bd96-7914f21cb4f2/releases/0.5.9/ |
Title | Simulating the cost of social care in an ageing population (Version 0.9.1). CoMSES Computational Model Library. |
Description | This model is an agent-based simulation written in Python 2.7, which simulates the cost of social care in an ageing UK population. The simulation incorporates processes of population change which affect the demand for and supply of social care, including health status, partnership formation, fertility and mortality. Fertility and mortality rates are drawn from UK population data, then projected forward to 2050 using the methods developed by Lee and Carter 1992. The model demonstrates that rising life expectancy combined with lower birthrates leads to growing social care costs across the population. More surprisingly, the model shows that the oft-proposed intervention of raising the retirement age has limited utility; some reductions in costs are attained initially, but these reductions taper off beyond age 70. Subsequent work has enhanced and extended this model by adding more detail to agent behaviours and familial relationships. The version of the model provided here produces outputs in a format compatible with the GEM-SA uncertainty quantification software by Kennedy and O'Hagan. This allows sensitivity analyses to be performed using Gaussian Process Emulation. |
Type Of Material | Computer model/algorithm |
Year Produced | 2021 |
Provided To Others? | Yes |
Impact | Discussing with Scottish Government the further development of this model for policy purposes. |
URL | https://www.comses.net/codebases/8a567240-f644-4574-9c1d-40f2ee67add0/releases/0.9.1/ |
Title | Software and results for: An agent-based model for simulating the impact of social norms on active commuting interventions |
Description | Interventions to increase active commuting have been recommended as a method to increase population physical activity, but evidence is mixed. Social norms related to travel behaviour may influence the uptake of active commuting interventions but are rarely considered in the design and evaluation of interventions. In this study we develop an agent-based model that incorporates social norms related to travel behaviour and simulate the relative impact of four active commuting interventions. A synthetic population of Waltham Forest, London, UK was generated using a microsimulation approach with data from the UK Census 2011 and UK HLS datasets. An agent-based model was created using this synthetic population which modelled how the actions of peers and neighbours, subculture, habit, weather, bicycle ownership, car ownership, environmental supportiveness, and congestion affect the decision to travel between four modes: walking, cycling, driving, and taking public transport. We examined four scenarios (and a control): car-free days; increasing environmental supportiveness for walking and cycling; decreasing environmental supportiveness for driving; increasing environmental supportiveness for walking and decreasing environmental supportiveness for driving. Compared to the control scenario, the car-free days scenario increased the odds of active commuting by 81.8% (OR 1.818; 95% CrI: [1.816 to 1.820]). Increasing environmental supportiveness for walking and cycling had no effect (OR: 1.000; 95% CrI: [1.000 to 1.001]), as did decreasing environmental supportiveness for driving (OR: 1.000; 95% CrI: [0.999 to 1.001]), and increasing environmental supportiveness for walking and cycling while decreasing environmental supportiveness for driving (OR: 1.000; 95% CrI: [1.000 to 1.001]). These results provide support for car-free days as an intervention to 'nudge' people into active commuting. However, why built environment interventions were less effective is unclear. |
Type Of Material | Computer model/algorithm |
Year Produced | 2021 |
Provided To Others? | Yes |
Impact | None as yet |
URL | https://datacompass.lshtm.ac.uk/id/eprint/2425/ |
Description | Developing collaboration with Nvidia (Eric Silverman) |
Organisation | NVIDIA |
Country | Global |
Sector | Private |
PI Contribution | Multiple meetings with Chris Emerson, Craig Rhodes, Jonny Hancox and Marjut Dieringer of Nvidia. Chris, Craig and Jonny work in Nvidia's health science team, and have developed multiple large collaborations with universities in areas like medical imaging. Marjut is part of their Deep Learning Institute which provides training on deep learning/AI. In our meetings we have discussed collaboration on the UKPRP-funded PHASE project, which focuses on agent-based modelling, and on applying deep learning methods to problems in population health. I have been introducing them to the PHASE project and developing specific areas for collaborative work on simulation approaches for population health. |
Collaborator Contribution | Nvidia intend to take part in our PHASE project and as a confirmation of the strategic importance of our relationship they have offered to provide deep learning training to the Unit. In upcoming meetings we will discuss their participation in PHASE events and they will provide feedback about the types of events that would be most useful to them. |
Impact | No outputs yet, however there will be opportunities to develop proof-of-concept projects via PHASE seed funds which can produce collaborative outputs. |
Start Year | 2019 |
Description | Modelling collaboration with Centre for Virus Research |
Organisation | University of Glasgow |
Department | MRC - University of Glasgow Centre for Virus Research |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Dr Eric Silverman, Dr Stefano Picascia and Dr Umberto Gostoli have developed a collaborative research initiative with Prof David L Robertson of the Centre for Virus Research, University of Glasgow. We are developing a simulation model combining an agent-based simulation of SARS-CoV-2 spread with a linked evolutionary model of viral evolution. This simulation will allow us to investigate the potential dangers of future variants of SARS-CoV-2, and how those variants will be affected by changes in public health policy and vaccine distribution, which may change the selection pressures imposed upon the virus. |
Collaborator Contribution | Prof Robertson has contributed by evaluating the early results of our initial model, providing details of the possible mutations of SARS-CoV-2 and how they affect the properties of the virus, and directing us toward relevant research in viral genomics and evolutionary biology. |
Impact | Early-stage outputs include a simulation model of SARS-CoV-2 spread incorporating competing variants and vaccines with waning immunity. |
Start Year | 2021 |
Description | PHASE project: A heterogenous agents framework for tobacco availability interventions (Alice MacLachlan) |
Organisation | Public Health Scotland |
Country | United Kingdom |
Sector | Public |
PI Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. In addition to funding, the PHASE research assistant is involved in supporting the research team to deliver the project. PHASE will be supporting the dissemination of project outputs through our website, social media and webinar series. |
Collaborator Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. Partners came up with the research proposal and have responsibility for overall delivery of the project. |
Impact | Outputs will be added as they emerge from the project. The project is multidisciplinary, involving academic public health, health geography and computer simulation experts, as well as practice partners. |
Start Year | 2022 |
Description | PHASE project: A heterogenous agents framework for tobacco availability interventions (Alice MacLachlan) |
Organisation | University of Edinburgh |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. In addition to funding, the PHASE research assistant is involved in supporting the research team to deliver the project. PHASE will be supporting the dissemination of project outputs through our website, social media and webinar series. |
Collaborator Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. Partners came up with the research proposal and have responsibility for overall delivery of the project. |
Impact | Outputs will be added as they emerge from the project. The project is multidisciplinary, involving academic public health, health geography and computer simulation experts, as well as practice partners. |
Start Year | 2022 |
Description | PHASE project: ABM-based Land Use-Transport Interaction (LUTI) simulation: healthier urban development and healthier travel behaviour for Greater Manchester (Alice MacLachlan) |
Organisation | Greater Manchester Combined Authority |
Country | United Kingdom |
Sector | Public |
PI Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. In addition to funding, a PHASE research assistant was available to support the research team. PHASE will be supporting the dissemination of project outputs through our website, social media and webinar series. |
Collaborator Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. Partners came up with the research proposal and have responsibility for overall delivery of the project. |
Impact | Outputs will be added as they emerge from the project. The project is multidisciplinary, involving academic public health , urban planning and computer simulation experts, as well as practice partners. |
Start Year | 2022 |
Description | PHASE project: ABM-based Land Use-Transport Interaction (LUTI) simulation: healthier urban development and healthier travel behaviour for Greater Manchester (Alice MacLachlan) |
Organisation | University of Manchester |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. In addition to funding, a PHASE research assistant was available to support the research team. PHASE will be supporting the dissemination of project outputs through our website, social media and webinar series. |
Collaborator Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. Partners came up with the research proposal and have responsibility for overall delivery of the project. |
Impact | Outputs will be added as they emerge from the project. The project is multidisciplinary, involving academic public health , urban planning and computer simulation experts, as well as practice partners. |
Start Year | 2022 |
Description | PHASE project: ABM-based Land Use-Transport Interaction (LUTI) simulation: healthier urban development and healthier travel behaviour for Greater Manchester (Alice MacLachlan) |
Organisation | University of Reading |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. In addition to funding, a PHASE research assistant was available to support the research team. PHASE will be supporting the dissemination of project outputs through our website, social media and webinar series. |
Collaborator Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. Partners came up with the research proposal and have responsibility for overall delivery of the project. |
Impact | Outputs will be added as they emerge from the project. The project is multidisciplinary, involving academic public health , urban planning and computer simulation experts, as well as practice partners. |
Start Year | 2022 |
Description | PHASE project: Chronic pain, mental health and employment: the role of firms, workers and the state (Alice MacLachlan) |
Organisation | Macquarie University |
Country | Australia |
Sector | Academic/University |
PI Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. In addition to funding, PHASE offered research assistant support to the research team. PHASE will be supporting the dissemination of project outputs through our website, social media and webinar series. |
Collaborator Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. Partners came up with the research proposal and have responsibility for overall delivery of the project. |
Impact | Outputs will be added as these emerge from the project. This collaboration is multidisciplinary, involving academic public health, economic and computer simulation experts. |
Start Year | 2021 |
Description | PHASE project: Chronic pain, mental health and employment: the role of firms, workers and the state (Alice MacLachlan) |
Organisation | University of Essex |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. In addition to funding, PHASE offered research assistant support to the research team. PHASE will be supporting the dissemination of project outputs through our website, social media and webinar series. |
Collaborator Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. Partners came up with the research proposal and have responsibility for overall delivery of the project. |
Impact | Outputs will be added as these emerge from the project. This collaboration is multidisciplinary, involving academic public health, economic and computer simulation experts. |
Start Year | 2021 |
Description | PHASE project: Developing a proof-of-concept agent-based model of the relationship between food advertising and food choices in England (Alice MacLachlan) |
Organisation | University of Sheffield |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. In addition to funding, the PHASE research assistant is involved in supporting the research team to deliver the project. PHASE will be supporting the dissemination of project outputs through our website, social media and webinar series. |
Collaborator Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. Partners came up with the research proposal and have responsibility for overall delivery of the project. |
Impact | Outputs will be added as they emerge from the project. The project is multidisciplinary, involving academic public health and computer simulation experts. |
Start Year | 2022 |
Description | PHASE project: Leveraging local policies to improve diet: modelling the role of local interventions impacting the food environment (Alice MacLachlan) |
Organisation | Drexel University |
Country | United States |
Sector | Academic/University |
PI Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. In addition to funding, the PHASE research assistant was heavily involved in supporting the research team to design and develop the model. PHASE will be supporting the dissemination of project outputs through our website, social media and webinar series. |
Collaborator Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. Partners came up with the research proposal and have responsibility for overall delivery of the project. |
Impact | Outputs will be added as they emerge from the project. The project is multidisciplinary, involving academic public health and computer simulation experts, as well as practice partners. |
Start Year | 2021 |
Description | PHASE project: Leveraging local policies to improve diet: modelling the role of local interventions impacting the food environment (Alice MacLachlan) |
Organisation | University of Liverpool |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. In addition to funding, the PHASE research assistant was heavily involved in supporting the research team to design and develop the model. PHASE will be supporting the dissemination of project outputs through our website, social media and webinar series. |
Collaborator Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. Partners came up with the research proposal and have responsibility for overall delivery of the project. |
Impact | Outputs will be added as they emerge from the project. The project is multidisciplinary, involving academic public health and computer simulation experts, as well as practice partners. |
Start Year | 2021 |
Description | PHASE project: Modelling the spread of multiple behavioural risk factors for cardiovascular disease in social networks using an agent-based model (Alice MacLachlan) |
Organisation | Coventry City Council |
Country | United Kingdom |
Sector | Charity/Non Profit |
PI Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. In addition to funding, a PHASE research assistant is available to provide support to the research team to deliver the project. PHASE will be supporting the dissemination of project outputs through our website, social media and webinar series. |
Collaborator Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. Partners came up with the research proposal and have responsibility for overall delivery of the project. |
Impact | Outputs will be added as they emerge from the project. The project is multidisciplinary, involving academic public health and computer simulation experts, as well as practice partners. |
Start Year | 2022 |
Description | PHASE project: Modelling the spread of multiple behavioural risk factors for cardiovascular disease in social networks using an agent-based model (Alice MacLachlan) |
Organisation | Queen Mary University of London |
Department | Wolfson Institute of Preventive Medicine |
Country | United Kingdom |
Sector | Public |
PI Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. In addition to funding, a PHASE research assistant is available to provide support to the research team to deliver the project. PHASE will be supporting the dissemination of project outputs through our website, social media and webinar series. |
Collaborator Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. Partners came up with the research proposal and have responsibility for overall delivery of the project. |
Impact | Outputs will be added as they emerge from the project. The project is multidisciplinary, involving academic public health and computer simulation experts, as well as practice partners. |
Start Year | 2022 |
Description | PHASE project: Modelling the spread of multiple behavioural risk factors for cardiovascular disease in social networks using an agent-based model (Alice MacLachlan) |
Organisation | University of Warwick |
Department | Department of Computer Science |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. In addition to funding, a PHASE research assistant is available to provide support to the research team to deliver the project. PHASE will be supporting the dissemination of project outputs through our website, social media and webinar series. |
Collaborator Contribution | This research project has been funded through the PHASE Network pump-prime funding scheme. Partners came up with the research proposal and have responsibility for overall delivery of the project. |
Impact | Outputs will be added as they emerge from the project. The project is multidisciplinary, involving academic public health and computer simulation experts, as well as practice partners. |
Start Year | 2022 |
Description | Social Care Modelling Collaboration with Scottish Government (Eric Silverman) |
Organisation | Government of Scotland |
Country | United Kingdom |
Sector | Public |
PI Contribution | Dr Umberto Gostoli and myself, following my seminar at St Andrews House for the Health and Social Care Analysis, were contacted by members of Scottish Government with an interest in producing policy advice relating to social care provision. Subsequently over the course of two in-person meetings we have a agreed a plan of action to begin producing an updated version of our social care simulation model to examine the possible outcomes of proposed changes to social care policy in Scotland. Our contribution will be additional modifications to our simulation model, further parameterising the simulation using empirical data, and producing and analysing results from the simulations. |
Collaborator Contribution | Our partners in Scottish Government will provide empirical data for use in our simulation, where possible, and will arrange meetings between our team and relevant user groups, practitioners and policy-makers. They may be able to provide material support for the research when the additional work required is outside the scope of our normal modelling work. |
Impact | Near-term outputs expected include a modified version of the simulation, which will be shared publicly via GitHub, and papers documenting the results of these first modifications. |
Start Year | 2019 |
Description | Agent-based modelling for policy seminar (Alice MacLachlan) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | A joint academic and policy workshop, tailored to promote and widen understanding of the application of agent based modelling (ABMs) in supporting the development of public policy, led by Digital Catapult. Laurence Moore was invited as a presenter and panel member for the discussion session on social policy and public health. |
Year(s) Of Engagement Activity | 2020 |
URL | https://www.digicatapult.org.uk/events/agent-based-modelling-for-policy-seminar |
Description | Bayesian Agent-Based Population Studies workshop (Eric Silverman) |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | A small group of 10 researchers from the UK, Germany and Poland gathered in Southampton for this workshop organised by the Centre for Population Change and run by Professor Jakub Bijak. Professor Bijak and his colleagues shared some outcomes of their project on Bayesian agent-based modelling for demography, and the group used these presentations as jumping-off points for discussing ways to increase the uptake of agent-based modelling across various disciplines, and to increase policy-makers' confidence in the method. Professor Bijak is producing a written summary of the event and the main discussion points raised, and we have agreed to develop an online forum for ABM practitioners to share advice and code, and to investigate the possibility of a journal focussed on methodological questions in ABM research. |
Year(s) Of Engagement Activity | 2020 |
Description | Expert lecture |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Third sector organisations |
Results and Impact | Expert talk given to CRUK/Ludwig led conference. I set out the work of the programme at the leading edge of assessing how built environment might relate to cancer prevention. There was a Q&A discussion afterwards. I was contacted by third sector organisations afterwards for follow up and connections. |
Year(s) Of Engagement Activity | 2021 |
Description | Invited Seminar (Health and Social Care Analysis/ISD, Scottish Government) (Eric Silverman) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Policymakers/politicians |
Results and Impact | 12 civil servants and analysts from ISD and the Health and Social Care Analysis team in Scottish Government invited me to give a seminar on agent-based modelling for the study of social care. The seminar took place at St Andrews House in Edinburgh and lasted 90 minutes. Participants were very enthusiastic about the possibilities presented by ABM approaches, and are keen to establish collaborative links with the Unit and with our UKPRP-funded PHASE project. |
Year(s) Of Engagement Activity | 2019 |
Description | PHASE ECR seminar (Alice MacLachlan) |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | The PHASE ECR seminar provided an opportunity for PhD students and post-docs to present their research on ABM in public health in a supportive environment and receive feedback and participate in discussion around their work. The event was attended by 20 people, mostly other ECRs and some more senior researchers. There was also an opportunity for wider discussion around what the PHASE network could offer ECRs in the future. |
Year(s) Of Engagement Activity | 2022 |
URL | https://phasenetwork.org/abm-resources/ |
Description | PHASE case study portfolio (Alice MacLachlan) |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | PHASE have developed a series of interactive case studies providing examples of key principles of agent-based modelling and how agent-based models can be applied to address public health challenges. The case studies are designed to provide an introduction into agent-based models for evidence-users (e..g those from policy/practice) as well as researchers unfamiliar with this methodology. The case studies were presented as part of a PHASE webinar series and were included on a poster at the Lancet Public Health Science Conference in November 2022. The network has already received requests for further information in response to this resource. |
Year(s) Of Engagement Activity | 2022 |
URL | https://phasenetwork.org/case-studies/ |
Description | PHASE webinar series: An introduction to ABM for public health (Alice MacLachlan) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | This 3-part webinar series provided an introduction to the use of agent-based models in public health. Each of the three webinars was attended by between 40-60 people, including those from research, practice and policy. There were a range of questions from the audience within each webinar and we have since received requests for further information after the webainrs. |
Year(s) Of Engagement Activity | 2022 |
Description | PHASE website and social media (Alice MacLachlan) |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | The PHASE website and Twitter account were launched in December 2019 to provide public information about the network aims and objectives, advertise network activities, share resources and provide a way for people to easily get in touch with the network team and sign up as members. As of October 2020 the network has 70 members signed up to the mailing list via the website and a growing Twitter following. |
Year(s) Of Engagement Activity | 2019,2020 |
URL | http://phasenetwork.org/ |
Description | Seminar for Scottish Government |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | Dr Umberto Gostoli presented on joint work by Dr Gostoli and Dr Eric Silverman (leader of the SPHSU Modelling Complex Systems workstream) at a seminar organised by Laura Martin of the Scottish Government. The seminar was attended by members of the Health and Social Care Governance, Evidence and Finance Unit, Care Inspectorate Unit and the Independent Living Fund Unit. The seminar presented work on agent-based modelling of social care, which is intended to provide a platform for investigating the possible impact of social care policy reform. All audience members were involved in reforms to adult social care, and responding to the independent review of social care. |
Year(s) Of Engagement Activity | 2021 |
Description | Social Simulation Week 2020 Symposium (Alice MacLachlan) |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | PHASE symposium titled "Opportunities and challenges of modelling complex health behaviour" delivered as part of the Social Simulation Week 2020 hosted by Behave Lab and the European Social Simulation Association. The symposium included five presenters and audience discussion and reached an International audience of ~40 people from the simulation and public health communities. |
Year(s) Of Engagement Activity | 2020 |
URL | http://phasenetwork.org/services/ |
Description | Society for Social Medicine Workshop on Agent Based Models |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | 30 Delegates attended this workshop which provided an overview of the ways in which Agent Based Models could be used for population health improvement. The presentations and breakout groups were well received, will several of the delegates offering to get involved in the network and signing up to the mailing list. |
Year(s) Of Engagement Activity | 2021 |