A Geographic-Based Model for Simulating and Forecasting the Diffusion of an Infectious Disease

Abstract

New challenges and heighten health awareness have surfaced with new and emerging infectious diseases like Severe Acute Respiratory Syndrome (SARS) and avian flu. Conventional models on disease transmission dynamics are limited in addressing the heterogeneous nature of the population and location-specific concerns. It seems to be necessary for an alternative and improved epidemiological approach to address these issues. The focus of this study is to establish a model to simulate the spatio-temporal transmission of an infectious disease, using the 2003 SARS data of Hong Kong in model development. It will also develop a stochastic and geographical-based approach for forecasting the possible spread of the disease. It is expected to result in an early warning system based on the model and a greater understanding of the spatial dynamics of infectious diseases, particularly in the spatial transmission of SARS.