Back to Search Start Over

June: open-source individual-based epidemiology simulation

Authors :
Joseph Aylett-Bullock
Carolina Cuesta-Lazaro
Arnau Quera-Bofarull
Miguel Icaza-Lizaola
Aidan Sedgewick
Henry Truong
Aoife Curran
Edward Elliott
Tristan Caulfield
Kevin Fong
Ian Vernon
Julian Williams
Richard Bower
Frank Krauss
Source :
Royal Society Open Science, Vol 8, Iss 7 (2021)
Publication Year :
2021
Publisher :
The Royal Society, 2021.

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.

Details

Language :
English
ISSN :
20545703
Volume :
8
Issue :
7
Database :
Directory of Open Access Journals
Journal :
Royal Society Open Science
Publication Type :
Academic Journal
Accession number :
edsdoj.85ddf5e9b8fb4346a5949c4b1e379f5b
Document Type :
article
Full Text :
https://doi.org/10.1098/rsos.210506