Literature DB >> 34717286

A dynamic microsimulation model for epidemics.

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.
Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.

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


  4 in total

1.  A computational framework for modelling infectious disease policy based on age and household structure with applications to the COVID-19 pandemic.

Authors:  Joe Hilton; Heather Riley; Lorenzo Pellis; Rabia Aziza; Samuel P C Brand; Ivy K Kombe; John Ojal; Andrea Parisi; Matt J Keeling; D James Nokes; Robert Manson-Sawko; Thomas House
Journal:  PLoS Comput Biol       Date:  2022-09-06       Impact factor: 4.779

2.  Evaluating the risk of accessing green spaces in COVID-19 pandemic: A model for public urban green spaces (PUGS) in London.

Authors:  Jiayu Pan; Ronita Bardhan
Journal:  Urban For Urban Green       Date:  2022-06-14

3.  Visualization for epidemiological modelling: challenges, solutions, reflections and recommendations.

Authors:  Jason Dykes; Alfie Abdul-Rahman; Daniel Archambault; Benjamin Bach; Rita Borgo; Min Chen; Jessica Enright; Hui Fang; Elif E Firat; Euan Freeman; Tuna Gönen; Claire Harris; Radu Jianu; Nigel W John; Saiful Khan; Andrew Lahiff; Robert S Laramee; Louise Matthews; Sibylle Mohr; Phong H Nguyen; Alma A M Rahat; Richard Reeve; Panagiotis D Ritsos; Jonathan C Roberts; Aidan Slingsby; Ben Swallow; Thomas Torsney-Weir; Cagatay Turkay; Robert Turner; Franck P Vidal; Qiru Wang; Jo Wood; Kai Xu
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2022-08-15       Impact factor: 4.019

4.  A synthetic population dataset for estimating small area health and socio-economic outcomes in Great Britain.

Authors:  Guoqiang Wu; Alison Heppenstall; Petra Meier; Robin Purshouse; Nik Lomax
Journal:  Sci Data       Date:  2022-01-20       Impact factor: 8.501

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.