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Soc. open sci."],"published-print":{"date-parts":[[2021,7]]},"abstract":"<jats:p>\n                    We introduce\n                    <jats:monospace>\n                      J\n                      <jats:sc>une<\/jats:sc>\n                    <\/jats:monospace>\n                    , 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.\n                    <jats:monospace>\n                      J\n                      <jats:sc>une<\/jats:sc>\n                    <\/jats:monospace>\n                    provides a suite of flexible parametrizations that describe infectious diseases, how they are transmitted and affect contaminated individuals. In this paper, we apply\n                    <jats:monospace>\n                      J\n                      <jats:sc>une<\/jats:sc>\n                    <\/jats:monospace>\n                    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.\n                  <\/jats:p>","DOI":"10.1098\/rsos.210506","type":"journal-article","created":{"date-parts":[[2021,7,7]],"date-time":"2021-07-07T03:05:24Z","timestamp":1625627124000},"page":"210506","update-policy":"https:\/\/doi.org\/10.1098\/crossmark-policy","source":"Crossref","is-referenced-by-count":28,"title":["J\n                    <scp>une<\/scp>\n                    : open-source individual-based epidemiology simulation"],"prefix":"10.1098","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7551-3423","authenticated-orcid":true,"given":"Joseph","family":"Aylett-Bullock","sequence":"first","affiliation":[{"name":"Institute for Data Science, Durham University, Durham DH1 3LE, UK"},{"name":"Institute for Particle Physics Phenomenology, Durham University, Durham DH1 3LE, 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UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ian","family":"Vernon","sequence":"additional","affiliation":[{"name":"Institute for Data Science, Durham University, Durham DH1 3LE, UK"},{"name":"Department of Mathematical Sciences, Durham University, Durham DH1 3LE, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julian","family":"Williams","sequence":"additional","affiliation":[{"name":"Institute of Hazard, Risk and Resilience, Durham University, Durham DH1 3LE, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard","family":"Bower","sequence":"additional","affiliation":[{"name":"Institute for Data Science, Durham University, Durham DH1 3LE, UK"},{"name":"Institute for Computational Cosmology, Durham University, Durham DH1 3LE, 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