Lauren Meyers, Mark Newman, Babak Pourbohloul
Paper #: 04-12-037
Contact network epidemiology is an approach to modeling the spread of infectious diseases that explicitly considers patterns of person-to-person contacts within a community. Contacts can be asymmetric, with a person more likely to infect one of their contacts than to become infected by that contact. This is true for some sexually transmitted diseases that are more easily caught by women than men during heterosexual encounters; and for severe infectious diseases that cause an average person to seek medical attention and thereby potentially infect health care workers who would not, in turn, have an opportunity to infect that average person. Here we use methods from percolation theory to develop a mathematical framework for predicting disease transmission through semi-directed contact networks in which some contacts are undirected - the probability of transmission is symmetric between individuals - and others are directed - transmission is possible only in one direction. We find that probability of an epidemic and the expected fraction of a population infected during an epidemic can be different in semi-directed networks, in contrast to the routine assumption that these two quantities are equal. Using these methods, we furthermore demonstrate the vulnerability of health care workers and the importance hospital-based containment during outbreaks of severe respiratory diseases.