Editorial Ppublish 5 citations
PubMed: 36475056 DOI: 10.1140/epjs/s11734-022-00724-1
Dynamics of the COVID-19 pandemic: nonlinear approaches on the modelling, prediction and control.
Eur Phys J Spec Top 231(18-20):3275-3280
Authors: Santo Banerjee
Affiliations
- Department of Mathematical Sciences, Politecnico di Torino, Turin, Italy.
Abstract
This special issue contains 35 regular articles on the analysis and dynamics of COVID-19 with several applications. Some analyses are on the construction of mathematical models representing the dynamics of COVID-19, and some are on the estimations and predictions of the disease, a few with possible applications. The various contributions report important, timely, and promising results, such as the effects of several waves, deep learning-based COVID-19 classifications, and multivariate time series with applications.
MeSH
Covid-19, Pandemics