Avian Flu: Modeling, Analysis, and Simulations

University Of Florida, Gainesville FL

Investigators

Abstract

The relatively benign human influenza virus strain that infects many of us year-round, albeit with seasonal pulses in frequency, can sometimes evolve into a potentially deadly strain that is capable of triggering a pandemic. The three recent human flu pandemics of 1918, 1957 and 1968--respectively known as the "Spanish flu", "Asian flu", and "Hong Kong flu"--caused huge devastation both in terms of the loss of human lives and consequent economic impacts. For each of these, genetic evidence suggests that a novel influenza strain evolved from the genetic recombination ("shift") of an animal flu strain and a human flu strain within a common host species that was co-infected by these two strains. This newly evolved strain had catastrophic effects on humans because of the absence of natural immunity by the host to this strain. The recent cases of human infection and death from avian influenza virus in several parts of the world, and the fact that humans and other animal species (such as swine) can act as a shared host to both avian flu and human flu strains, has raised concern that we may face a near-term emergence of another novel and highly virulent strain, thus another potential pandemic. Mathematical models provide crucial tools for understanding and possibly predicting and controlling the emergence and subsequent spread of novel pathogen strains. In this project we develop and analyze mathematical and simulation models to study real-world biological scenarios, in which there is co-infection of human host by avian flu and human flu strains. We will focus in particular on characterizing conditions for invasion and persistence of emergent virulent strains within human populations. This project will significantly advance our knowledge of the transmission dynamics and evolution of avian influenza from bird to human populations in particular, and of multi-species epidemic systems in general. It will provide a series of usable, realistic models that are grounded on available data. These models can serve as a solid background for future extensions incorporating and testing the efficacy of various control measures (such as vaccination, chemotherapy, and social distancing) for pandemic influenza, and suggest avenues of empirical study that are particularly important to pursue for disease prediction. In terms of technical approaches, this project unites the efforts of mathematicians and biologists in developing models based on integrated partial differential equations (PDE), ordinary differential equations (ODE), and stochastic individual-based simulations (IBS), to study the evolutionary epidemiology and population biology of avian influenza (AI). The research goal will be pursued along two main directions. 1) The "drift" and "shift" mechanisms of genomic evolution of an influenza virus will be simultaneously incorporated within a multi-strain PDE model that then will be used to predict the epidemiological consequences in a human population of an evolved influenza variant -- a novel avian influenza strain with both high pathogenicity and high human-to-human transmission efficiency. ODE versions of this model will be fitted to available World Health Organization (WHO) data of the cumulative number of human cases of avian influenza infection. Mathematical analysis of the best fitting ODE and PDE models will then be carried out, to rigorously characterize conditions for spread and persistence. 2) Complementary individual-based simulation (IBS) models of a human population will be developed on a small-world type network that incorporate explicit social interaction (contact) neighborhoods of each individual, and stochastic processes of birth, death and infection events. The pattern of flu outbreaks in these IBS models will be studied with respect to the underlying network structure, and related to the predictions of the corresponding ODE models. This will help elucidate the role of stochastic factors likely to be important in the early stages of strain emergence.