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

Christian Julliard, Ran Shi and Kathy Yuan

Journal of Econometrics, 2023, vol. 235, issue 2, 2125-2154

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 44%, 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: C51 C54 D85 I12 I18 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Related works:
Working Paper: 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 (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:235:y:2023:i:2:p:2125-2154

DOI: 10.1016/j.jeconom.2023.02.012

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