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Social distance, speed of containment and crowding in/out in a network model of contagion

journal contribution
posted on 06.09.2021, 14:36 by Fabrizio Adriani, Dan Ladley
We study the effects of an intervention aimed at identifying and containing outbreaks in a network model of contagion where social distance is endogenous. The intervention induces a fall in the risk of contagion, to which agents respond by reducing social distance. If the intervention relies on infrequent or inaccurate testing, this crowding out effect may fully offset the intervention’s direct effect, so that the risk of contagion increases. In these circumstances, we show that “slow” interventions – which allow the outbreak to spread to immediate neighbors before being contained – may generate higher ex-ante welfare than “fast” ones and may even “crowd in” social distance. The theory thus identifies a trade off between (i) the swiftness of the intervention and (ii) the scope for crowding out. Simulations on a real world network confirm that the infection rate is not necessarily monotonically decreasing in the accuracy of the intervention and that slow interventions may outperform fast ones for intermediate levels of accuracy.

History

Citation

Journal of Economic Behavior & Organization Volume 190, October 2021, Pages 597-625

Author affiliation

School of Business

Version

AM (Accepted Manuscript)

Published in

Journal of Economic Behavior & Organization

Volume

190

Pagination

597 - 625

Publisher

Elsevier BV

issn

0167-2681

Acceptance date

01/08/2021

Copyright date

2021

Available date

24/02/2023

Language

en