Abstract
The importance of implementing new methodologies to study the ever-increasing amount of Covid-19 data is apparent. The aftermath analysis of these data could inform us on how specific political decisions influenced the dynamics of the pandemic outbreak. In this paper we use the Italian outbreak as a case study, to study six different Covid indicators collected in twenty Italian regions. We define a new object, the Covidome, to investigate the network of functional Covid interactions between regions. We analyzed the Italian Covidome over the course of 2020, and found that Covid connectivity between regions follows a sharp North-South community gradient. Furthermore, we explored the Covidome dynamics and individuated differences in regional Covid connectivity between the first and second waves of the pandemic. These differences can be associated to the two different lockdown strategies adopted for the first and the second wave from the Italian government. Finally, we explored to what extent Covid connectivity was associated with the Italian geographical network, and found that Central regions were more tied to the structural constraints than Northern or Southern regions in the spread of the virus. We hope that this approach will be useful in gaining new insights on how political choices shaped Covid dynamics across nations.
Highlights
The probability for two regions of being in the same community across all Covid indicators. For both within-indicator modularity, as well as for the allegiance matrix, the Covidome network is mainly split into a North-South community pattern, with some exceptions: FVG (Friuli Venezia Giulia) and Veneto are included in the “Southern” module for the hospitalized with symptoms, whereas for new positives the “Northern” community spreads over to Abruzzo and Campania, and “Southern” incorporates Emilia Romagna and Marche in its community
We have found that: (i) the Covidome community structure shows a well defined North-South pattern; (ii) dynamic Covidome fluctuations stem from the effects of the two different preventive measures during the first and the second waves, in the early and towards the end of 2020, respectively; (iii) the association between Covidome and structural constraints for mobility depends on the differences between the two different lockdowns: one nationwide, the other more localized regionally
We here presented a first investigation of the functional network of Covid-19 pandemic (Covidome), across different indicators
Summary
We will first introduce the time series (i.e., Covid indicators) used for this study, and detail the Italian outbreak and political decisions made to prevent it. How political choices shaped Covid connectivity introduce the Covid connectivity matrix (”Covidome”) and give an overview of the network approaches employed. We analyzed different time series starting from 24 February 2020 until 7 January 2021 (few days after vaccine campaign started). All the considered time series are available for each Italian region. We focused on 6 different Covid indicators, such as: 1) the number of hospitalized individuals in ICU; 2) number of hospitalized individuals with symptoms; 3) number of individuals in home isolation; 4) number of new positives; 5) number of discharged healed; and 6) number of deceased individuals
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