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Assessing the effect of containment measures on the spatio-temporal dynamic of COVID-19 in Italy

Maria Michela Dickson, Giuseppe Espa, Diego Giuliani, Flavio Santi, Lucia Savadori

2020Nonlinear Dynamics44 citationsDOIOpen Access PDF

Abstract

This paper aims at investigating empirically whether and to what extent the containment measures adopted in Italy had an impact in reducing the diffusion of the COVID-19 disease across provinces. For this purpose, we extend the multivariate time-series model for infection counts proposed in Paul and Held (Stat Med 30(10):118-1136, 2011) by augmenting the model specification with B-spline regressors in order to account for complex nonlinear spatio-temporal dynamics in the propagation of the disease. The results of the model estimated on the time series of the number of infections for the Italian provinces show that the containment measures, despite being globally effective in reducing both the spread of contagion and its self-sustaining dynamics, have had nonlinear impacts across provinces. The impact has been relatively stronger in the northern local areas, where the disease occurred earlier and with a greater incidence. This evidence may be explained by the shared popular belief that the contagion was not a close-to-home problem but rather restricted to a few distant northern areas, which, in turn, might have led individuals to adhere less strictly to containment measures and lockdown rules.

Topics & Concepts

Containment (computer programming)Coronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)EconometricsMathematicsComputer scienceOutbreakVirologyMedicineProgramming languageInfectious disease (medical specialty)DiseasePathologyCOVID-19 epidemiological studiesData-Driven Disease SurveillanceSpatial and Panel Data Analysis
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