Strength and Weakness of Disease-induced Herd Immunity in Networks

During the COVID-19 pandemic, several studies suggested that the spread of infection might induce herd immunity more easily than previously thought due to population heterogeneity. However, these studies relied on differential equation-based epidemic models, which cannot account for correlations between individuals. We reexamine the effect of disease-induced herd immunity using individual-based contact network models. We find that herd immunity is weaker when such correlations are taken into account, so much so that the conclusions of the previous studies may be overturned. This effect is especially pronounced when the contact network is spatially embedded. Our results highlight the importance of considering network effects in policy decisions that affect the lives and well-being of millions in future pandemics.

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