Abstract

We use daily data from Lombardy, the Italian region most affected by the COVID-19 outbreak, to calibrate a SIR model on each municipality. Municipalities with a higher initial number of cases feature a lower rate of diffusion, not attributable to herd immunity: there is a robust and strongly significant negative correlation between the estimated basic reproduction number (R0) and the initial outbreak size. This represents novel evidence of the prevalence-response elasticity in a cross-sectional setting, characterized by a same health system and homogeneous social distancing regulations. By ruling out alternative explanations, we 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 finding calls for the distribution of detailed epidemiological data to populations affected by COVID-19 outbreaks.

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