| Literature DB >> 34295529 |
Joseph Aylett-Bullock1,2, Carolina Cuesta-Lazaro1,3, Arnau Quera-Bofarull1,3, Miguel Icaza-Lizaola1,3, Aidan Sedgewick1,4, Henry Truong1,2, Aoife Curran1,3, Edward Elliott1,3, Tristan Caulfield5, Kevin Fong6,7, Ian Vernon1,8, Julian Williams9, Richard Bower1,3, Frank Krauss1,2.
Abstract
We introduce June, an open-source framework for the detailed simulation of epidemics on the basis of social interactions in a virtual population constructed from geographically granular census data, reflecting age, sex, ethnicity and socio-economic indicators. Interactions between individuals are modelled in groups of various sizes and properties, such as households, schools and workplaces, and other social activities using social mixing matrices. June provides a suite of flexible parametrizations that describe infectious diseases, how they are transmitted and affect contaminated individuals. In this paper, we apply June to the specific case of modelling the spread of COVID-19 in England. We discuss the quality of initial model outputs which reproduce reported hospital admission and mortality statistics at national and regional levels as well as by age strata.Entities:
Keywords: individual-based model; infectious disease; simulation
Year: 2021 PMID: 34295529 PMCID: PMC8261230 DOI: 10.1098/rsos.210506
Source DB: PubMed Journal: R Soc Open Sci ISSN: 2054-5703 Impact factor: 2.963