This volume addresses SDG 3 from a mathematical standpoint, sharing novel perspectives of existing communicable disease modelling technologies of the next generation and disseminating new developments in modelling methodologies and simulation techniques. These methodologies are important for training and research in communicable diseases and can be applied to other threats to human health. The contributions contained in this collection/book cover a range of modelling techniques that have been and may be used to support decision-making on critical health related issues such as:

Preface.- Mathematical models: perspectives of mathematical modelers and public health professionals.- Discovering first-principle of behavioural change in disease transmission dynamics by deep learning.- Understanding Epidemic Multi-Wave Patterns via Machine Learning Clustering and the Epidemic Renormalization Group.- Contact Matrices in Compartmental Disease Transmission Models.- An optimal control approach for public health interventions on an Epidemic-Viral model in deterministic and stochastic environments.- Modeling airborne disease dynamics: progress and questions.- Modelling mutation-driven emergence of drug-resistance: a case study of SARS-CoV-2.- A Categorical Framework for Modeling with Stock and Flow Diagrams.- Agent-Based Modeling and its Tradeoffs: An Introduction & Examples.- Mathematical assessment of the role of interventions against SARS-CoV-2.- Long term dynamics of COVID-19 in a multi-strain model.