Mathematics has been used to study the spread of the disease for centuries. In the 1700s, Daniel Bernoulli used a mathematical models to provide compelling evidence of the effectiveness of vaccination as a means for combating smallpox. In the 1800s, investigations of the spatial distribution of cholera cases helped overturn incorrect notions about the origin of cholera and laid a foundation for the germ theory of disease. In the 20th century, pioneers like Kermack and McKendrick used compartmental models like the SIR model to investigate the various factors that contribute to the severity of an epidemic.
When combined with spatial information about human mobility, epidemic models can be a powerful tool for determining how quickly an epidemic will spread, how many people will be infected, and if and when it will subside. They can also be used to investigate intervention strategies in order to inform public policy about what can be done to diminish the severity of the outbreak. Past work (with Nir Yungster) involved modeling the spread of influenza on a European transportation network to identiify which countries were most vulnerable to an outbreak. More recently, I am interested in studying epidemics on mobility networks in order to explore the role of environmental contamination in the spread of food and water-borne pathogens like cholera, noro-virus.
Mathematical Epidemiology
