An agent-based model of social care provision during the early stages of Covid-19

Gostoli, U. and Silverman, E. (2022) An agent-based model of social care provision during the early stages of Covid-19. Scientific Reports, 12, 16534. (doi: 10.1038/s41598-022-20846-9) (PMID:36192471) (PMCID:PMC9528879)

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Social care is a frequent topic in UK policy debates, with widespread concern that the country will be unable to face the challenges posed by the increase in demand for social care. While this is a societal problem whose dynamics depends on long-term trends, such as the increase of human lifespans and the drop of birth-rates, a short-term crisis, such as a pandemic, can affect the need and supply of social care to a considerable, although temporary, extent. Building on previous modelling effort of social care provision, we present an agent-based computational model to investigate social care provision in the context of a pandemic (using as an example, the early stages of the Covid-19 pandemic), and related mitigation policies, on social care demand and supply, using a proof-of-concept agent-based model (ABM). We show how policy solutions aimed at controlling the pandemic may have substantial effects on the level of unmet social care need and propose that such models may help policymakers to compare alternative containment policies, taking into account their side effects on the social care provision process.

Item Type:Articles
Additional Information:UG and ES are in the Complexity in Health programme supported by the Medical Research Council (MC_UU_00022/1) and the Chief Scientist Office (SPHSU16). 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.
Glasgow Author(s) Enlighten ID:Gostoli, Dr Umberto and Silverman, Dr Eric
Authors: Gostoli, U., and Silverman, E.
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > MRC/CSO SPHSU
Journal Name:Scientific Reports
Publisher:Nature Research
ISSN (Online):2045-2322
Copyright Holders:Copyright © 2022 The Authors
First Published:First published in Scientific Reports 12: 16534
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
3048231Complexity in healthSharon SimpsonMedical Research Council (MRC)MC_UU_00022/1HW - MRC/CSO Social and Public Health Sciences Unit
3048231Complexity in healthSharon SimpsonOffice of the Chief Scientific Adviser (CSO)SPHSU16HW - MRC/CSO Social and Public Health Sciences Unit
303087PHASE: The Population HeAlth Simulation nEtworkLaurence MooreMedical Research Council (MRC)MR/S037594/1HW - MRC/CSO Social and Public Health Sciences Unit