Advanced mathematical methodologies to contrast COVID-19 pandemic

Background. The COVID-19 pandemic impacted the whole world including scientific communities. Notably, mathematical models became standard tools 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 are various reasons behind this 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. The community of modelers discussed the various reasons for drawbacks but also concentrated the efforts to generate new approaches to tackle with the unprecedented situation of the COVID-19 pandemic, and also help with future pandemics. This special issue collects a number of interesting approaches, which provide an interesting and broad perspective on such activities.