City Research Online

OpenABM-Covid19-An agent-based model for non-pharmaceutical interventions against COVID-19 including contact tracing

Hinch, R., Probert, W., Nurtay, A. , Kendall, M., Wymant, C., Hall, M., Lythgoe, K., Bulas Cruz, A., Zhao, L., Stewart, A., Ferretti, L., Montero, D., Warren, J., Mather, N., Abueg, M., Wu, N., Legat, O., Bentley, K., Mead, T., Van-Vuuren, K., Feldner-Busztin, D., Ristori, T., Finkelstein, A. ORCID: 0000-0003-2167-9844, Bonsall, D., Abeler-Dorner, L. & Fraser, C. (2021). OpenABM-Covid19-An agent-based model for non-pharmaceutical interventions against COVID-19 including contact tracing. PLoS Computational Biology, 17(7), article number e1009146. doi: 10.1371/journal.pcbi.1009146


SARS-CoV-2 has spread across the world, causing high mortality and unprecedented restrictions on social and economic activity. Policymakers are assessing how best to navigate through the ongoing epidemic, with computational models being used to predict the spread of infection and assess the impact of public health measures. Here, we present OpenABM-Covid19: an agent-based simulation of the epidemic including detailed age-stratification and realistic social networks. By default the model is parameterised to UK demographics and calibrated to the UK epidemic, however, it can easily be re-parameterised for other countries. OpenABM-Covid19 can evaluate non-pharmaceutical interventions, including both manual and digital contact tracing, and vaccination programmes. It can simulate a population of 1 million people in seconds per day, allowing parameter sweeps and formal statistical model-based inference. The code is open-source and has been developed by teams both inside and outside academia, with an emphasis on formal testing, documentation, modularity and transparency. A key feature of OpenABM-Covid19 are its Python and R interfaces, which has allowed scientists and policymakers to simulate dynamic packages of interventions and help compare options to suppress the COVID-19 epidemic.

Publication Type: Article
Additional Information: © 2021 Hinch et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Subjects: H Social Sciences > HN Social history and conditions. Social problems. Social reform
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QR Microbiology > QR180 Immunology
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
R Medicine > RC Internal medicine
Departments: Presidents's Portfolio
SWORD Depositor:
[thumbnail of journal.pcbi.1009146.pdf]
Text - Published Version
Available under License Creative Commons: Attribution International Public License 4.0.

Download (2MB) | Preview


Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email


Downloads per month over past year

View more statistics

Actions (login required)

Admin Login Admin Login