Disease Spread as a Function of Socioeconomic Status in Manhattan
When studying the spread of disease, it is impressive to consider variable factors such as population distributions, the interactions between differing populations, and socioeconomic factors. We use a network model of interacting nodes with contact rates dependent on population size and socioeconomic status to explore the disease spread across the twelve districts of Manhattan, New York City. Influenza was chosen as an example due to its short infection period and negligible disease-related deaths in comparison to prevalence levels. Since transmission occurs primarily through casual contact, proportionate mixing is incorporated in the model. Numerical simulation of the model and sensitivity analysis of its parameters are then used to identify critical factors, dependent on socioeconomic status, responsible for the severity of the epidemic. Vaccination strategies are also implemented to explore what methods will have the greatest effects on the dynamics of the model.
Julie Blackwood, Rochester Institute of Technology
Carlos Chiquete, University of Arizona
Russell Latterman, Arizona State University
Stephen Small, Norfolk State University