COVID-19: The advantages and limitations of mathematical modelling

The recent COVID-19 pandemic has posed a great challenge for significant and meaningful mathematical modelling. A wide range of mathematical models have been proposed and analysed based upon various approaches and underlying research questions.

The focus of this talk is a multi-compartment epidemic model for COVID-19, along with the validation of model outcomes with data from several European countries. The proposed model is capable of incorporating the behavioural variations between two groups of people, one of them following COVID restrictions and another that is reluctant. The two-group epidemic model is capable of capturing multiple outbreaks with different peak sizes. The challenge is to understand how we can construct a reasonable and tractable mathematical model for large countries where the number of reported cases varies from one state to another, and determine optimal vaccination strategies keeping in mind the limitations in vaccine availability. Some challenging research questions will be discussed from the modelling point of view.

Speaker Bio: 
Dr Malay Banerjee is a Professor in the Mathematics and Statistics department of the Indian Institute of Technology, Kanpur. He received his PhD degree from the University of Calcutta in Applied Mathematics. His research interests lie in the area of Nonlinear Dynamics, Mathematical Ecology and Mathematical Epidemiology. He is currently the editor of the ‘Theoretical and Mathematical Ecology’ section of the journal Mathematics, and the Guest Editor for special issues on COVID-19 for the journals Mathematical Modelling of Natural Phenomena and Letters in Biomathematics.