A weighted approach for spatio-temporal clustering of COVID-19 spread in Italy

Raffaele Mattera

doi:10.1016/j.sste.2022.100500

A weighted approach for spatio-temporal clustering of COVID-19 spread in Italy

Spat Spatiotemporal Epidemiol. 2022 Jun:41:100500. doi: 10.1016/j.sste.2022.100500. Epub 2022 Mar 25.

Author

Raffaele Mattera¹

Affiliation

¹ Department of Economics and Statistics, University of Naples "Federico II", Italy; Department of Social and Economic Sciences, Sapienza University of Rome, Italy. Electronic address: raffaele.mattera@unina.it.

Abstract

The SARS-Cov-2 has spread differently over space and time worldwide. By monitoring the contagion's time evolution, the November 3 2020 the Italian government introduced differentiated regime of restrictions among its regions. This experiment demonstrated that public health policies can be effectively designed by means of clustering. This paper proposes a fuzzy clustering model where spatial and temporal dimensions of the disease spread are optimally weighted. The resulting model is applied with the aim of identifying groups of Italian regions with similar contagion spread. We found that two groups of regions sharing similar patterns of COVID-19 spread over both space and time exist. Appropriate public health policies can be designed on the basis of this evidence.

Keywords: COVID-19; Fuzzy clustering; LISA; Policy design; Spatial auto-correlation; Time series.

MeSH terms

COVID-19* / epidemiology
Cluster Analysis
Humans
Italy / epidemiology
SARS-CoV-2