RAPID: Stochastic Ebola Modeling on Dynamic Contact Networks

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As the world faces a large outbreak of Ebola epidemic, several vaccines are currently in clinical trials with a reasonable chance of being available in the field in early 2015. Since the initial amount of vaccine will be limited, the understanding of Ebola epidemic dynamics is essential for maximizing the effectiveness of public health intervention through a combination of targeted vaccination, monitoring and quarantine.This project is concerned with developing a realistic but at the same time mathematically tractable and statistically predictive dynamic model of the current world-wide Ebola epidemics. The modeling approach that divides the population into three groups (susceptibles, infected, and removed--the so-called SIR model) and its various generalizations has been used historically as an important tool in deciding whether epidemics grow or dissipate. The investigators expand the traditional model of an SIR stochastic epidemic on a graph with a given degree distribution, in order to account for the Ebola-specific features. These include, among others, incorporating a class of individuals at high risk of infection (e.g., health workers), and incorporating a dynamic network structure that reflects how contacts with different segments of the population change over the course of infection within host.The new mathematical model describing the way in which Ebola spreads through a network of human contacts, both in rural and urban areas as well as across countries and continents, will be informed by the actual field data from various parts of the world including Africa and the United States. It is expected that the model will allow public health and government officials to quickly analyze a host of different intervention scenarios in order to speed up the current epidemic's dissipation and to select the most effective way of preventing, or at least minimizing, the future outbreaks.