Dynamics of Epidemics in Contact Networks

Various deterministic and stochastic epidemic models for directly transmissible diseases, such as influenza, measles, HIV and SARS, have attracted increasing attention from researchers. However the most common models are still based on restrictive assumptions which refrain from accurate description of infectious agent's characteristics and their propagation from individual to individual, in time and space. In this project we relax two important epidemic model hypotheses. The first assumption is known as the "law of mass action" and implies that all individuals in a population are equally likely to acquire the infection. Since some directly transmissible infections require specific kind of contacts to propagate, e.g. sexually transmitted illnesses, the related epidemics are heavily affected by specific population's contact structure. The second hypothesis assumes agent's infectious and latent periods are exponentially distributed. The proposed outcomes of this project are theoretical results for the outbreak evolution and a computer simulation program. The statistical analysis and simulation of the outbreak will lead to more informed decision-making and the reduction of the economical and social impact of infectious illness.

Faculty Supervisor:

Dr. Mary Thompson

Student:

Lilia Leticia Ramirez Ramirez

Partner:

Infonaut Inc.

Discipline:

Statistics / Actuarial sciences

Sector:

Life sciences

University:

University of Waterloo