2023 Impact factor 2.6
Special Topics

EPJ ST Highlight - Dynamics of the COVID-19 pandemic

The outbreak of COVID-19 changed the human perception of day-to-day life and tested the bounds of medical technology in protecting the welfare of humans. Several approaches and safety measures have been implemented to minimize the countless lives that are being affected. However, public health and educational breaches are evidenced in most countries in which not all citizens have the same opportunities to deal with the pandemic. Therefore, this has led to pervasive consequences, including mental health problems because of the disruption of everyday life routines.

This special issue is a collection of 35 orginal research articles that address the dynamics and applications of COVID-19 through nonlinear dynamics. The articles are organized in five sections, comprising mathematical modeling and epidemics, the dynamics of several waves and transmission, neural network and deep learning related to COVID-19, predictions and estimations related to COVID-19, and detailed analysis on the pandemic and its applications. The various contributions report important, timely, and promising results and provide insight into the spread of the coronavirus and control measures against the COVID-19 pandemic.

All articles are available here and are freely accessible until 21 March 2023. For further information read the Editorial by Santo Banerjee ”Dynamics of the COVID-19 pandemic: nonlinear approaches on the modelling, prediction and control” Eur. Phys. J. Spec. Top. 231, 3275–3280 (2022). https://doi.org/10.1140/epjs/s11734-022-00724-1

Managing Editors
Sandrine Karpe and Vijala Kiruvanayagam (EDP Sciences) and Sabine Lehr (Springer-Verlag)
Many thanks for the excellent work and support from you and your team at Springer / EDP sciences.

Susana Alexandra Barbosa, Centre for Information Systems and Computer Graphics, Porto, Portugal
Editor EPJ Special Topics 224/4, 2015

ISSN: 1951-6355 (Print Edition)
ISSN: 1951-6401 (Electronic Edition)

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