A1108
Title: Breaking down homogeneous mixing assumptions in epidemic compartmental models
Authors: Jorge M Mendes - NOVA Information Management School, NOVA University Lisbon (Portugal) [presenting]
Abstract: A spatial age-structured SIR model is proposed to refine the simplistic assumption of homogeneous mixing found in traditional compartmental models by incorporating population stratification by age groups and spatial distribution. This approach acknowledges the heterogeneity in contact patterns and mobility behaviours across different demographics and geographical locations. The model utilises a contact-mobility stochastic matrix, which integrates network analysis features such as betweenness and clustering. These network metrics significantly influence the dynamics of infection transmission by either facilitating or impeding the spread of disease. Betweenness centrality identifies key individuals or nodes that act as bridges within the network, playing a crucial role in potential outbreak propagation. Clustering reflects the degree to which nodes cluster together, affecting local transmission dynamics. By incorporating these elements, the model offers a more nuanced understanding of epidemic spread, capturing the complex interplay between social structure and disease dynamics. This spatial and age-stratified approach allows for more accurate predictions and effective intervention strategies, ultimately enhancing public health responses to infectious disease outbreaks.
