Travel Demand Models for Micro-Level Contact Network Modeling

Abstract

In the pursuit of accurate infectious disease forecasting, micro-level contact modeling in contact networks emerges as a pivotal element. This research delves into the intricacies of nuanced micro-level modeling, presenting adaptable models tailored for specific locations, derived from a refined travel demand model. In our experiments, we observed that varied encounter patterns among individuals directly influence infection dynamics. Additionally, we observe distinct trends in the spreading dynamics between temporal dynamic networks and their static counterparts for certain encounter models. The study underscores the need for a deeper appreciation of micro-level encounter patterns in epidemiological modeling. Such understanding is pivotal in shaping effective interventions and public health strategies during pandemic scenarios.