Stochastic approaches to mathematical modelling of HIV infection (Daniel Coombs - University of British Columbia)
Abstract: The overwhelming majority of mathematical models of viral infections are based on differential equations. These models provide a good approximation to the average behavior of the system when the numbers of infected cells and virions are high. However, during the first few days of infection, or during successful ongoing treatment that suppresses the viral load, this assumption is definitely violated. In this talk I will describe work with stochastic models (branching processes) that can give interesting insights into the population dynamics of HIV - for instance: the likelihood of extinction of HIV during long-term therapy, the window of opportunity for prophylactic treatment, and the duration of the gap between risky exposure and detectable infection.
- 4:00 pm on Thursday, October 12, 2017
- 5:00 pm on Thursday, October 12, 2017
- 111 Cummington Mall, Room 148