COVID-19: R 0 Is Lower Where Outbreak Is Larger

21 Pages Posted: 21 Apr 2020

See all articles by Pietro Battiston

Pietro Battiston

University of Pisa - Department of Economics and Management

Simona Gamba

Catholic University of the Sacred Heart of Milan - Department of Economics and Finance

Date Written: April 17, 2020

Abstract

We use daily data from Lombardy, the Italian region most affected by the COVID-19 outbreak, to calibrate a SIR model individually on each municipality. These are all covered by the same health system and, in the post-lockdown phase we focus on, all subject to the same social distancing regulations. We find that municipalities with a higher number of cases at the beginning of the period analyzed to have a lower rate of diffusion, which cannot be imputed to herd immunity. In particular, there is a robust and strongly significant negative correlation between the estimated basic reproduction number (R0 ) and the initial outbreak size, in contrast with the role of R0 as a predictor of outbreak size. We explore different possible explanations for this phenomenon and conclude that a higher number of cases causes changes of behavior, such as a more strict adoption of social distancing measures among the population, that reduce the spread. This result calls for transparent, real-time distribution of detailed epidemiological data, as such data affects the behavior of populations in areas affected by the outbreak.

Keywords: COVID-19, tests, basic reproduction number, social distancing, containment

JEL Classification: I12, I18, C53, C22

Suggested Citation

Battiston, Pietro and Gamba, Simona, COVID-19: R 0 Is Lower Where Outbreak Is Larger (April 17, 2020). University of Milan Bicocca Department of Economics, Management and Statistics Working Paper No. 438, 2020, Available at SSRN: https://ssrn.com/abstract=3579338

Pietro Battiston (Contact Author)

University of Pisa - Department of Economics and Management ( email )

Pisa
Italy

Simona Gamba

Catholic University of the Sacred Heart of Milan - Department of Economics and Finance ( email )

Via Necchi 5
Milan, MI 20123
Italy

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