Simulating the Spread of Malaria: A Cellular Automaton Based Mathematical Model & A Prototype Software Implementation

Every year three million deaths are attributed to malaria, of which one-third are of children. Malaria is a vector-borne disease, where a mosquito acts as the vector that transmits the disease. In the last few years, computer simulation based models have been used effectively to study the vector population dynamics and control strategies of vector-borne diseases. Typically, these models use ordinary differential equations to simulate the spread of malaria. Although these models provide a powerful mechanism to study the spread of malaria, they have several shortcomings. The research in this thesis focuses on creating a simulation model based on the framework of cellular automata, which addresses many shortcomings of previous models. Cellular automata are dynamical systems, which are discrete in time and space. The implementation of the model proposed can easily be integrated with EpiSims/TRANSIMS. EpiSims is an epidemiological modeling tool for studying the spread of infectious diseases; it uses social contact network from TRANSIMS (A Transport Analysis and Simulation System). Simulation results from the prototype implementation showed qualitatively correct results for vector densities, diffusion and epidemiological curves.