On a national scale, Lombardy is the region most intensely and severely affected by Covid-19. The present study relies on reflexive cartography to investigate the hypothesis that viral spread was facilitated by a set of physical and social factors in the region. As it traces the monitoring of contagion, the study reveals crucial spatial features, such as a “backbone” of intense epidemic spread in the central-eastern part of the territory, which unites the Lodi area with the Bergamo area. This backbone may be said to have determined a regional bipartition, with a high intensity of contagion in less inhabited areas of Lombardy compared to metropolitan areas. As a matter of fact, the metropolitan area of Milan was initially spared and was severely hit only in the subsequent phase of contagion. Such differing features are conveyed by means of digital mapping, built in a space–time perspective, with a view to tracing the details of epidemic distribution and evolution.

(2021). Evolution and intensity of infection in Lombardy . Retrieved from http://hdl.handle.net/10446/190073

Evolution and intensity of infection in Lombardy

Consolandi, Elisa
2021-01-01

Abstract

On a national scale, Lombardy is the region most intensely and severely affected by Covid-19. The present study relies on reflexive cartography to investigate the hypothesis that viral spread was facilitated by a set of physical and social factors in the region. As it traces the monitoring of contagion, the study reveals crucial spatial features, such as a “backbone” of intense epidemic spread in the central-eastern part of the territory, which unites the Lodi area with the Bergamo area. This backbone may be said to have determined a regional bipartition, with a high intensity of contagion in less inhabited areas of Lombardy compared to metropolitan areas. As a matter of fact, the metropolitan area of Milan was initially spared and was severely hit only in the subsequent phase of contagion. Such differing features are conveyed by means of digital mapping, built in a space–time perspective, with a view to tracing the details of epidemic distribution and evolution.
2021
Consolandi, Elisa
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/190073
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