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Hadrons and Nuclei

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

David Blaschke, Thomas Duguet and Maria Jose Garcia Borge
It is a great satisfaction to see the fruit of months of research and discussions published in your journal. Besides, I express my gratitude for the quick and timely carrying out of the production process, the correct implementation of my amendments, the professionalism and the attention I have received.

G. Stellin, Institut fur Strahlen- und Kernphysik, Rheinische Friedrich-Wilhelms-Universitat Bonn, Germany

ISSN (Electronic Edition): 1434-601X

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