Network size, structure, and pathogen transmission: a simulation study comparing different community detection algorithms

摘要: Social substructure can influence pathogen transmission. Modularity measures the degree of social contact within versus between “communities” in a network, with increasing modularity expected to reduce transmission opportunities. We investigated how scales network size and disease Using small-scale primate networks, we applied seven community detection algorithms calculate subgroup cohesion, defined as individuals’ interactions subgroups proportional network. found larger networks were more modular higher but association’s strength varied by algorithm measure. These findings highlight importance choosing an appropriate for question interest, if not possible, using multiple algorithms. Disease simulations revealed cohesion resulted fewer infections, confirming that has epidemiological consequences. Increased subdivision could reflect constrained time budgets or evolved defences against risk.