The Spread of COVID-19 in London: Network Effects and Optimal Lockdowns
52 Pages Posted: 22 Oct 2020 Last revised: 7 Feb 2023
Date Written: October 19, 2020
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 47% 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 re- gions 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.
Note: Funding: None to declare.
Declaration of Interests: None to declare.
Keywords: COVID-19, networks, key players, spatial modelling, SIR model
JEL Classification: I12, I18, C31, C51, D85
Suggested Citation: Suggested Citation