DIMACS Computational and Mathematical Epidemiology Seminar Series

Title: Transmission Probabilities and Disease Spread

Speaker: Michael Capalbo, DIMACS

Date: January 31, 2005 2:30 - 3:45 pm**

Location: DIMACS Center, CoRE Bldg, Room 433, Rutgers University, Busch Campus, Piscataway, NJ


Given a contagious infection that has hit a few members of a community, it is very natural to ask in Epidemiology how many people are likely to become infected. The answer to this depends, of course, on the distributions of the events $A_{u,v}$, where, for each two people $u$ and $v$ in the community, $A_{u,v}$ is the event that $u$ catches the infection directly from $v$, given that $u$ is not yet infected and $v$ already is. Several other researchers, such as S. Hartke, investigated the special case where the $P[A_{u,v}]$'s are either 0 or 1, and the pairs $\{u,v\}$ such that $P[A_{u,v}]$'s are 1 form a $d$-dimensional grid. We have been investigating cases where the $A_{u,v}$'s are allowed to take on a much wider range of distributions. In this talk we first give an (almost) complete set of conditions for when and when not an epidemic will likely spread to a large fraction of the community, given that the $A_{u,v}$'s satisfy a set of somewhat reasonable assumptions. Then we propose a model where we relax these assumptions, and indicate our current approach to extend the techniques we have developed to this new model.

(This is joint work with James Abello)

**Please note new time will be 2:30 - 3:45 on Mondays for the spring seminar series