J une : open-source individual-based epidemiology simulation

Author:

Aylett-Bullock Joseph12ORCID,Cuesta-Lazaro Carolina13,Quera-Bofarull Arnau13ORCID,Icaza-Lizaola Miguel13,Sedgewick Aidan14ORCID,Truong Henry12ORCID,Curran Aoife13,Elliott Edward13,Caulfield Tristan5,Fong Kevin67,Vernon Ian18,Williams Julian9,Bower Richard13,Krauss Frank12ORCID

Affiliation:

1. Institute for Data Science, Durham University, Durham DH1 3LE, UK

2. Institute for Particle Physics Phenomenology, Durham University, Durham DH1 3LE, UK

3. Institute for Computational Cosmology, Durham University, Durham DH1 3LE, UK

4. Centre for Extragalactic Astronomy, Durham University, Durham DH1 3LE, UK

5. Department of Computer Science, University College London, London WC1E 6BT, UK

6. Department of Science, Technology, Engineering and Public Policy, University College London, London WC1E 6BT, UK

7. Department of Anaesthesia, University College London Hospital, London NW1 2BU, UK

8. Department of Mathematical Sciences, Durham University, Durham DH1 3LE, UK

9. Institute of Hazard, Risk and Resilience, Durham University, Durham DH1 3LE, UK

Abstract

We introduce J une , 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. J une provides a suite of flexible parametrizations that describe infectious diseases, how they are transmitted and affect contaminated individuals. In this paper, we apply J une 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.

Publisher

The Royal Society

Subject

Multidisciplinary

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