A1311
Title: Connecting mass-action models and network models for infectious diseases
Authors: Thien Minh Le - University of Tennessee at Chattanooga (United States) [presenting]
Abstract: Infectious disease modeling is used to forecast epidemics and assess the effectiveness of intervention strategies. Although the core assumption of mass-action models of homogeneously mixed population is often implausible, they are nevertheless routinely used in studying epidemics and provide useful insights. Network models can account for the heterogeneous mixing of populations, which is especially important for studying sexually transmitted diseases. Despite the abundance of research on mass-action and network models, the relationship between them is not well understood. The attempt is to bridge the gap by first identifying a spreading rule that results in an exact match between disease spreading on a fully connected network and the classic mass-action models. A method for mapping epidemic spread on arbitrary networks to a form similar to that of mass-action models is then proposed. A theoretical justification for the procedure is also provided. Finally, the advantages of the proposed methods are shown using synthetic data that is based on an empirical network. These findings help in understanding when mass-action models and network models are expected to provide similar results and identify reasons when they do not.
