Positive feedback loops exacerbate the influence of superspreaders in disease transmission



Wanelik KM, Begon M, Fenton A, Norman RA & Beldomenico PM (2023) Positive feedback loops exacerbate the influence of superspreaders in disease transmission. Norman R (Researcher) iScience, 26 (5), Art. No.: 106618.

Superspreaders are recognized as being important drivers of disease spread. However, models to date have assumed random occurrence of superspreaders, irrespective of whom they were infected by. Evidence suggests though that those individuals infected by superspreaders may be more likely to become superspreaders themselves. Here, we begin to explore, theoretically, the effects of such a positive feedback loop on (1) the final epidemic size, (2) the herd immunity threshold, (3) the basic reproduction number, R0, and (4) the peak prevalence of superspreaders, using a generic model for a hypothetical acute viral infection and illustrative parameter values. We show that positive feedback loops can have a profound effect on our chosen epidemic outcomes, even when the transmission advantage of superspreaders is moderate, and despite peak prevalence of superspreaders remaining low. We argue that positive superspreader feedback loops in different infectious diseases, including SARS-CoV-2, should be investigated further, both theoretically and empirically.

Health sciences; Medicine; Virology; Disease transmission;

iScience: Volume 26, Issue 5

FundersBelmont Forum and The Leverhulme Trust
Publication date31/05/2023
Publication date online11/04/2023
Date accepted by journal03/04/2023
PublisherElsevier BV

People (1)


Professor Rachel Norman

Professor Rachel Norman

Chair in Food Security & Sustainability, Mathematics

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