Special Issue: Advanced Mathematical Methodologies to Manage Pandemics
Guest Editors
Prof. Monique Chyba
Department of Mathematics, College of Natural Sciences, University of Hawaii at Manoa, USA
Email: chyba@hawaii.edu
Prof. Rinaldo M. Colombo
Email: rinaldo.colombo@unibs.it
Prof. Mauro Garavello
Department of Mathematics and its Applications, University of Milano-Bicocca, Italy
Email: mauro.garavello@unimib.it
Prof. Benedetto Piccoli
Department of Mathematical Sciences and Center for Computational and Integrative Biology, Rutgers University, USA
Email: piccoli@camden.rutgers.edu
Manuscript Topics
The COVID-19 pandemic impacted the whole world including scientific communities. A significant role was played by mathematical models to predict, manage, and control the pandemic. However, the same models were also deeply criticized because of their limited capability in making precise predictions. There were various reasons behind these drawbacks, including: the novelty of a fast-spreading pandemic in a connected world, the role played by the human factor, the abundance of data with low level of fidelity, and the appearance of virus variants with different clinical impacts. This is a second special issue on this theme to report on advancements in new approaches.
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