The spread of COVID-19 in London: network effects and optimal lockdowns

Christian Julliard, Ran Shi and Kathy Yuan

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: We generalise a stochastic version of the workhorse SIR (Susceptible-Infectious- Removed) epidemiological model to account for spatial dynamics generated by network interactions. Using the London metropolitan area as a salient case study, we show that commuter network externalities account for about 42% of the propagation of COVID-19. We find that the UK lockdown measure reduced total propagation by 57%, with more than one third of the effect coming from the reduction in network externalities. Counterfactual analyses suggest that: i) the lockdown was somehow late, but further delay would have had more extreme consequences; ii) a targeted lockdown of a small number of highly connected geographic regions would have been equally effective, arguably with significantly lower economic costs; iii) targeted lockdowns based on threshold number of cases are not effective, since they fail to account for network externalities.

Keywords: COVID-19; networks; key players; spatial modelling; SIR model (search for similar items in EconPapers)
JEL-codes: C31 C51 D85 I12 I18 (search for similar items in EconPapers)
Pages: 45 pages
Date: 2020-10-20
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http://eprints.lse.ac.uk/118864/ Open access version. (application/pdf)

Related works:
Journal Article: The spread of COVID-19 in London: Network effects and optimal lockdowns (2023)
Working Paper: The spread of COVID-19 in London: network effects and optimal lockdowns (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:118864

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