JUNE: open-source individual-based epidemiology simulation

Aylett-Bullock, J.; Cuesta-Lazaro, C.; Quera-Bofarull, A.; Icaza-Lizaola, M.; Sedgewick, A.; Truong, H.; Curran, A.; Elliott, E.; Caulfield, T.; Fong, K.; Vernon, I.; Williams, J.; Bower, R.; Krauss, F.

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.

Citation

Aylett-Bullock, J., Cuesta-Lazaro, C., Quera-Bofarull, A., Icaza-Lizaola, M., Sedgewick, A., Truong, H., …Krauss, F. (2021). JUNE: open-source individual-based epidemiology simulation. Royal Society Open Science, 8(7), https://doi.org/10.1098/rsos.210506

• Journal Article Type: Article
• Acceptance Date: Jun 22, 2021
• Online Publication Date: Jul 7, 2021
• Publication Date: 2021-07
• Deposit Date: Jul 22, 2021
• Publicly Available Date: Jul 23, 2021
• Journal: Royal Society Open Science
• Publisher: The Royal Society
• Peer Reviewed: Peer Reviewed
• Volume: 8
• Issue: 7
• DOI: https://doi.org/10.1098/rsos.210506
• Public URL: https://durham-repository.worktribe.com/output/1244769