Stacey Smith?
The University of Ottawa, Canada
ABSTRACT
This workshop deals with a range of different options for creating more advanced models, depending on the circumstances. First, we will examine choices that can be made for the infection term, for demography and inclusion of factors like the effects of media or available hospital beds. Next, we’re going to look at a disease where the infection may split into a symptomatic class and an asymptomatic class, like influenza. Asymptomatic individuals may not know they’re infected (which means they’re unlikely to seek treatment or stay home), but they may also transmit the infect at a lower rate, due to a lower viral load. They may also recover faster — or not, depending. Immunity may not be permanent. Recovered individuals can lose their immunity due to mutation of the virus and return to the susceptible class. This makes things a lot more complicated. By the end of this workshop, you should be able to understand when to make modelling choices, what the implications of these choices are and how to incorporate some realistic limitations into the models.