Curated by the Fields Institute for Research in Mathematical Sciences from their COVID-19 Math Modelling Seminars, this first in a series of volumes on the mathematics of public health allows readers to access the dominant ideas and techniques being used in this area, while indicating problems for further research. This work brings together experts in mathematical modelling from across Canada and the world, presenting the latest modelling methods as they relate to the COVID-19 pandemic.

A primary aim of this book is to make the content accessible so that researchers share the core methods that may be applied elsewhere. The mathematical theories and technologies in this book can be used to support decision makers on critical issues such as projecting outbreak trajectories, evaluating public health interventions for infection prevention and control, developing optimal strategies to return to a new normal, and designing vaccine candidates and informing mass immunization program.

Topical coverage includes: basic susceptible-exposed-infectious-recovered (SEIR) modelling framework modified and applied to COVID-19 disease transmission dynamics; nearcasting and forecasting for needs of critical medical resources including personal protective equipment (PPE); predicting COVID-19 mortality; evaluating effectiveness of convalescent plasma treatment and the logistic implementation challenges; estimating impact of delays in contact tracing; quantifying heterogeneity in contact mixing and its evaluation with social distancing; modelling point of care diagnostics of COVID-19; and understanding non-reporting and underestimation.

Further, readers will have the opportunity to learn about current modelling methodologies and technologies for emerging infectious disease outbreaks, pandemic mitigation rapid response, and the mathematics behind them. The volume will help the general audience and experts to better understand the important role that mathematics has been playing during this on-going crisis in supporting critical decision-making by governments and public health agencies.

Jianhong Wu is the co-editor of this volume with Kumar Murty. A University Distinguished Research Professor and Senior Canada Research Chair in Industrial and Applied Mathematics, York University. He is also the NSERC Industrial Research Chair in vaccine mathematics, modelling, and manufacturing. His expertise includes dynamical systems and bifurcation theory, that develops methodologies to identify long-term dynamic scenarios of an epidemiological system. He also pioneered a neural network architecture for pattern recognition in high dimensional data. This expertise, along with his interdisciplinary collaborative network, put him in a good position to develop a reciprocal linkage between public health and mathematics. Staring from the 2003 SARS outbreak, Dr. Wu has led multiple national teams to develop mathematical technologies to address key public health issues relevant to emerging infectious diseases including SARS, pandemic influenza, Ebola, antimicrobial drug resistance, and Lyme disease. He is currently leading the National COVID-19 Modeling Rapid Response Task Force.