A dynamic microsimulation model for epidemics
| Autor: | Fiona Spooner, Jamil Nur, Rory Greig, Mark Birkin, Alex Coleman, Jesse F Abrams, Natalie Nelissen, Gavin Shaddick, Nick Malleson, Adam Dennett, Richard Milton, Nik Lomax, Michael Batty, Karyn Morrissey, Charlie Shenton, Ying Jin |
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| Přispěvatelé: | Morrissey, Karyn [0000-0001-7259-1047], Apollo - University of Cambridge Repository |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Flexibility (engineering)
Health (social science) Activities of daily living Public economics SARS-CoV-2 Computer science Simulation modeling Psychological intervention Microsimulation COVID-19 Private sector Article Data-driven Dynamics Coronavirus Policy History and Philosophy of Science General partnership Communicable Disease Control Humans Spatial-interaction Epidemics SEIR |
| Zdroj: | Spooner, F, Abrams, J F, Morrissey, K, Shaddick, G, Batty, M, Milton, R, Dennett, A, Lomax, N, Malleson, N, Nelissen, N, Coleman, A, Nur, J, Jin, Y, Greig, R, Shenton, C & Birkin, M 2021, ' A dynamic microsimulation model for epidemics ', Social Science & Medicine, vol. 291, 114461 . https://doi.org/10.1016/j.socscimed.2021.114461 Social Science & Medicine (1982) |
| ISSN: | 0277-9536 |
| DOI: | 10.1016/j.socscimed.2021.114461 |
| Popis: | Funder: Aerospace Technology Institute Funder: UK Research and Innovation Funder: The Alan Turing Institute A large evidence base demonstrates that the outcomes of COVID-19 and national and local interventions are not distributed equally across different communities. The need to inform policies and mitigation measures aimed at reducing the spread of COVID-19 highlights the need to understand the complex links between our daily activities and COVID-19 transmission that reflect the characteristics of British society. As a result of a partnership between academic and private sector researchers, we introduce a novel data driven modelling framework together with a computationally efficient approach to running complex simulation models of this type. We demonstrate the power and spatial flexibility of the framework to assess the effects of different interventions in a case study where the effects of the first UK national lockdown are estimated for the county of Devon. Here we find that an earlier lockdown is estimated to result in a lower peak in COVID-19 cases and 47% fewer infections overall during the initial COVID-19 outbreak. The framework we outline here will be crucial in gaining a greater understanding of the effects of policy interventions in different areas and within different populations. |
| Databáze: | OpenAIRE |
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