| Literature DB >> 34717286 |
Fiona Spooner1, Jesse F Abrams2, Karyn Morrissey3, Gavin Shaddick4, Michael Batty5, Richard Milton5, Adam Dennett5, Nik Lomax6, Nick Malleson6, Natalie Nelissen6, Alex Coleman7, Jamil Nur8, Ying Jin8, Rory Greig9, Charlie Shenton9, Mark Birkin10.
Abstract
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.Entities:
Keywords: COVID-19; Coronavirus; Dynamics; Microsimulation; SEIR; Spatial-interaction
Mesh:
Year: 2021 PMID: 34717286 PMCID: PMC8520832 DOI: 10.1016/j.socscimed.2021.114461
Source DB: PubMed Journal: Soc Sci Med ISSN: 0277-9536 Impact factor: 4.634