Modeling the Effect of Contact Rates on Infectious Diseases in Contact Networks

Infectious diseases have been modeled over the past centuries using equationbased modeling. Ordinary differential equations have been used in these models to represent the rate of flow of individuals among compartments in the modeling process. These equations have been quite useful but over the past few decades, two different models that have also proved a lot powerful and very useful are the agent-based model and the contact network-based model. In Agent-Based Modeling (ABM), the movements of individuals are simulated over time and space to model the spread of an infection. Similarly in contact Network-Based Modeling (NBM), the spread of an infection is modeled as a diffusion process on graphs. Our sole aim in this paper is to investigate how contact rates in a network based model influence infection spread within populations. We use susceptible-; infected-; and recovered epidemic models consisting of ordinary differential equations for our equation based model. For our contact based network model, we simulate the infection spread on a network following a Poisson degree distribution. The epidemic spread on the network uses bond percolation whereas in the agent based model, we use NetLogo to simulate the infection spread process. Using the network based model, we investigate how different contact rates contribute to epidemic spread within populations. Keywords—epidemiology; emerging infectious diseases; bond perclation; contact network.