Year: 2021
Type: article
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.
Source: Social Science & Medicine
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,090
Awards: JPI Urban Europe/NSFC SustaInable Mobility and Equality in mega-ciTy RegIons: patterns, mechanisms and governance, G1623820126, G3433308809, G3495160753, Consumer Data Research Support Service (CDRSS), CDRC, G5228939224, G6098645062, Strategic Priorities Fund - AI for Science, Engineering, Health and Government, G8479848735, G8786159991
OpenAlex ID: W3207215952
