Grant: Discovery Grants Program - Individual

With increasing mobility of populations worldwide, the spread of infectious diseases has become a matter of growing concern to public health. In particular, the imminent threat of pandemic influenza is receiving serious international attention. Along with other developed countries, Canada now has a pandemic preparedness plan. Underlying all health planning is the need to understand how pathogens interact with their hosts, adapt, and are transmitted through the population. Clinical or experimental approaches to epidemic interventions, by themselves, are often expensive, impractical, or even unethical. Mathematical and computer modelling of infectious diseases have become recognized as valuable tools for probing these systems, and determining the conditions that lead on the one hand to the spread of epidemics, and on the other to suggesting public health strategies for disease control or mitigation. Rapid advances in virology and immunology provide a wealth of useful information that has not yet been exploited in mathematical or computer models of these complex processes. Limitations of computer power to represent the vast range of scales of complexity compel one to adopt statistical descriptions of the underlying processes. The present proposal aims to take advantage of recent developments in applications of statistical mechanics to complex networks, to formulate self-consistent dynamical models of disease transmission and epidemic spread. These models will allow co-evolution of network structures (at the macro-scale) and pathogen transmission processes (at the micro-scale). Methods will be developed for statistical representations of complex networks in terms of indices that are critical determinants of their global, 'emergent' behaviour. These results will enable comparison of critical network properties deduced from idealized networks with those measured in real networks. It is anticipated that such an approach will afford otherwise unobtainable insights into disease propagation that will suggest effective preventive control strategies or contingency plans during an outbreak, and thus provide useful insights for planning public health policy.