PHASE: Facilitating Agent-Based Modelling in Population Health

Silverman, E. and Gostoli, U. (2021) PHASE: Facilitating Agent-Based Modelling in Population Health. In: Winter Simulation Conference 2020, Orlando, FL, USA, 13-16 Dec 2020, pp. 135-146. ISBN 9781728194998

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Abstract

Agent-based modelling (ABM), despite numerous successes in various disciplines of the physical and natural sciences, remains at the fringes of population health research. ABM can contribute to public health policy-making by providing a means to develop and test ambitious policies on virtual populations prior to roll-out, and to incorporate detailed individual-level modelling of relevant behavioral processes. Here we introduce PHASE: Population Health Agent-based Simulation nEtwork, a research network started in October 2019 and funded by the UK Prevention Research Partnership that will develop and support the community of agent-based modellers in population health. We then present a worked example of ABM being applied to social care provision in the United Kingdom, demonstrating how our model facilitates the development of complex policy interventions in this area. We propose that ABM for population health research can thrive when underpinned by a strong collaborative network and supported by open-source tools and exemplar models.

Item Type:Conference Proceedings
Additional Information:Umberto Gostoli and Eric Silverman are part of the Complexity in Health Improvement Programme supported by the Medical Research Council (MC UU 12017/14) and the Chief Scientist Office (SPHSU14). This work was supported by UK Prevention Research Partnership MR/S037594/1, which is funded by the 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), Medical Research Council, National Institute for Health Research, Natural Environment Research Council, Public Health Agency (Northern Ireland), The Health Foundation and Wellcome.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Gostoli, Dr Umberto and Silverman, Dr Eric
Authors: Silverman, E., and Gostoli, U.
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > MRC/CSO SPHSU
ISBN:9781728194998
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
727661Complexity in Health ImprovementLaurence MooreMedical Research Council (MRC)MC_UU_12017/14HW - MRC/CSO Social and Public Health Sciences Unit
727661Complexity in Health ImprovementLaurence MooreOffice of the Chief Scientific Adviser (CSO)SPHSU14HW - MRC/CSO Social and Public Health Sciences Unit
303087PHASE: The Population HeAlth Simulation nEtworkLaurence MooreMedical Research Council (MRC)MR/S037594/1SHW - MRC/CSO Social & Public Health Sciences Unit