Naser Alqutaifi | Applied Math, University of Waterloo
Networks and the Epidemiology of Infectious Disease
Infectious diseases are a leading cause of death globally. One of the major reasons for studying infectious diseases is to improve control and ultimately to eradicate the infection from the population. The earliest account of Mathematical modelling of spread of disease was carried out in 1766. Nowadays, Mathematical models have become important tools for investigating infectious diseases.
Many diseases spread through populations by contact between infective individuals and susceptible individuals. The pattern of these disease-causing contacts forms a network. The primary advantage of network models is their ability to capture complex individual-level structure in a simple framework. All processes take time to complete.
In realistic systems, we cannot neglect the time delay, such as period during which the epidemic recovers and information transmitting interval, etc.. The models that incorporate such delay times are referred as delay differential equation (DDE) models. Time-delay systems widely exist in engineering and science, where the rate of change of state is determined by both present and past state variables. Recently, multiple time delays are introduced to complex dynamical networks. So, our aim is to study different epidemic models with multiple-time delays on complex networks.