When a fraction of a population becomes immune to an infectious disease, the risk of widespread outbreaks decreases non-linearly as a result of the collective protection known as herd immunity. Typically, immunity to a disease can be acquired through natural infection or vaccination. It has been argued that natural infection in a heterogeneous population may induce a stronger herd immunity effect than homogeneous vaccination, because the early stages of transmission would primarily affect highly interactive individuals, leading to more efficient suppression of subsequent infections. In this study, we provide a comprehensive assessment of the herd immunity effect by analyzing the behavior of the susceptible-infected-recovered (SIR) model on static contact networks. We find that the effectiveness of disease-induced herd immunity is shaped by two competing mechanisms: While it exploits degree heterogeneity in the contact network to efficiently target highly connected individuals for immunity, it also introduces mixing heterogeneity between immune and susceptible individuals, weakening herd immunity. By controlling the degree of spatial embeddedness of the contact network structure, we find that spatial structure generally makes herd immunity stronger and also enhances the advantage of the herd immunity effect induced by random immunization over the disease-induced one in networks with low degree heterogeneity. These findings provide valuable insights into the complexity of herd immunity and have implications for designing effective disease control strategies.
TilaHyväksytty/In press - 10 heinäk. 2023
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