Tooling-up for infectious disease transmission modelling

• Main Authors: Marc Baguelin, Graham F. Medley, Emily S. Nightingale, Kathleen M. O’Reilly, Eleanor M. Rees, Naomi R. Waterlow, Moritz Wagner
• Format: Article
• Language: English
• Published: Elsevier 2020-09-01
• Series: Epidemics
• Subjects: Mathematical modelling; Perspective; Methodology
• Online Access: http://www.sciencedirect.com/science/article/pii/S1755436520300220

In this introduction to the Special Issue on methods for modelling of infectious disease epidemiology we provide a commentary and overview of the field. We suggest that the field has been through three revolutions that have focussed on specific methodological developments; disease dynamics and heterogeneity, advanced computing and inference, and complexity and application to the real-world. Infectious disease dynamics and heterogeneity dominated until the 1980s where the use of analytical models illustrated fundamental concepts such as herd immunity. The second revolution embraced the integration of data with models and the increased use of computing. From the turn of the century an emergence of novel datasets enabled improved modelling of real-world complexity. The emergence of more complex data that reflect the real-world heterogeneities in transmission resulted in the development of improved inference methods such as particle filtering. Each of these three revolutions have always kept the understanding of infectious disease spread as its motivation but have been developed through the use of new techniques, tools and the availability of data. We conclude by providing a commentary on what the next revoluition in infectious disease modelling may be.