Several metrics are crucial in understanding the dynamics of disease spread in networks. Degree centrality measures the number of direct connections an individual has, which can indicate their potential to spread infection. Betweenness centrality identifies individuals who act as bridges between different network clusters, potentially controlling the flow of information or pathogens. Clustering coefficient assesses the degree to which nodes in a network tend to cluster together, affecting how quickly a disease might spread locally.
