Reconstruction of the temporal correlation network of all-cause mortality fluctuation across Italian regions: the importance of temperature and among-nodes flux

TL;DR

This study reconstructs the correlation network of all-cause mortality fluctuations across Italian regions, highlighting the roles of temperature and human mobility in understanding systemic health threats.

Contribution

It introduces a statistical-mechanics approach to analyze mortality correlation networks, incorporating temperature and flux data to distinguish causes and monitor systemic risks.

Findings

Correlation network structure varies with temperature and flux.

Temperature and mobility significantly influence mortality correlations.

Network anomalies can indicate emerging systemic health threats.

Abstract

All-cause mortality is a very coarse grain, albeit very reliable, index to check the health implications of lifestyle determinants, systemic threats and socio-demographic factors. In this work we adopt a statistical-mechanics approach to the analysis of temporal fluctuations of all-cause mortality, focusing on the correlation structure of this index across different regions of Italy. The correlation network among the 20 Italian regions was reconstructed using temperature oscillations and travellers' flux (as a function of distance and region's attractiveness, based on GDP), allowing for a separation between infective and non-infective death causes. The proposed approach allows monitoring of emerging systemic threats in terms of anomalies of correlation network structure.