A network-based explanation of why most COVID-19 infection curves are linear.

ABSTRACT: Many countries have passed their first COVID-19 epidemic peak. Traditional epidemiological models describe this as a result of nonpharmaceutical interventions pushing the growth rate below the recovery rate. In this phase of the pandemic many countries showed an almost linear growth of confirmed cases for extended time periods. This new containment regime is hard to explain by traditional models where either infection numbers grow explosively until herd immunity is reached or the epidemic is completely suppressed. Here we offer an explanation of this puzzling observation based on the structure of contact networks. We show that for any given transmission rate there exists a critical number of social contacts, [Formula: see text], below which linear growth and low infection prevalence must o

SUBMITTER: Thurner S 

PROVIDER: S-EPMC7502715 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature