Spatiotemporal Analysis of COVID-19 Incidence Data

(1) Background: A better understanding of COVID-19 dynamics in terms of interactions among individuals would be of paramount importance to increase the effectiveness of containment measures. Despite this, the research lacks spatiotemporal statistical and mathematical analysis based on large datasets...

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Veröffentlicht in:	Viruses Jg. 13; H. 3; S. 463
Hauptverfasser:	Spassiani, Ilaria, Sebastiani, Giovanni, Palù, Giorgio
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 11.03.2021 MDPI
Schlagworte:	Cluster Analysis Clustering Coronaviruses COVID-19 COVID-19 - epidemiology COVID-19 - virology COVID-19 infection data collection Disease transmission Generalized linear models geophysics hierarchical clustering Humans Hypotheses Incidence Infections Information processing Italy mathematical analysis Models, Theoretical Morphology networks Pandemics Provinces SARS-CoV-2 - genetics SARS-CoV-2 - physiology Severe acute respiratory syndrome coronavirus 2 Spacetime Spatial distribution Spatio-Temporal Analysis Statistical analysis Statistics Italy China COVID-19 hierarchical clustering mathematical analysis networks spatial distribution
ISSN:	1999-4915, 1999-4915
Online-Zugang:	Volltext
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