Probabilistic Graph Theoretical Models for Predicting Ebola Spread
Rucha Joshi*, Westwood High School, Austin Texas
The current Ebola outbreak has affected thousands around the world and has threatened the safety of nations. Modeling the spread of the virus by predicting when, where, and how it will affect the world will allow countries to prepare for its arrival.
The study here uses directed line graphs with probabilistic edges to determine the interaction between various states over time. The states are a function of the number of infected and uninfected people, infection and death rates, travel etc. Recursive line graphs allow us to model historical progression of all nodes and their edges up to a current stage.
This study has been modeled by Java programming, while taking into consideration all above factors. The variation of the factors over time can be modeled by polynomial equations. These equations also enable the model to perform what-if analysis, which can help authorities to appropriate resources to the critical variables.
This study factors in variables, such as travel and rate changes over time, that were not available in other, similar studies. This is a novel approach to modeling biological and social issues using graph theory.
Keywords: modeling, recursive line graph, Ebola pandemic