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Modelling SARS-COV2 Spread in London: Approaches to Lift the Lockdown

Goscé, L; Phillips, PA; Spinola, P; Gupta, DRK; Abubakar, PI; (2020) Modelling SARS-COV2 Spread in London: Approaches to Lift the Lockdown. Journal of Infection , 81 (2) pp. 260-265. 10.1016/j.jinf.2020.05.037. Green open access

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Abstract

OBJECTIVE: To use mathematical models to predict the epidemiological impact of lifting the lockdown in London, UK, and alternative strategies to help inform policy in the UK. METHODS: A mathematical model for the transmission of SARS-CoV2 in London. The model was parametrised using data on notified cases, deaths, contacts, and mobility to analyse the epidemic in the UK capital. We investigated the impact of multiple non pharmaceutical interventions (NPIs) and combinations of these measures on future incidence of COVID-19. RESULTS: Immediate action at the early stages of an epidemic in the affected districts would have tackled spread. While an extended lockdown is highly effective, other measures such as shielding older populations, universal testing and facemasks can all potentially contribute to a reduction of infections and deaths. However, based on current evidence it seems unlikely they will be as effective as continued lockdown. In order to achieve elimination and lift lockdown within 5 months, the best strategy seems to be a combination of weekly universal testing, contact tracing and use of facemasks, with concurrent lockdown. This approach could potentially reduce deaths by 48% compared with continued lockdown alone. CONCLUSIONS: A combination of NPIs such as universal testing, contact tracing and mask use while under lockdown would be associated with least deaths and infections. This approach would require high uptake and sustained local effort but it is potentially feasible as may lead to elimination in a relatively short time scale.

Type: Article
Title: Modelling SARS-COV2 Spread in London: Approaches to Lift the Lockdown
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.jinf.2020.05.037
Publisher version: https://doi.org/10.1016/j.jinf.2020.05.037
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute for Global Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute for Global Health > Infection and Population Health
URI: https://discovery.ucl.ac.uk/id/eprint/10103144
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