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• W1889156735 startingPage "10551" @default.
• W1889156735 abstract "We investigate the impact of contact structure clustering on the dynamics of multiple diseases interacting through coinfection of a single individual, two problems typically studied independently. We highlight how clustering, which is well known to hinder propagation of diseases, can actually speed up epidemic propagation in the context of synergistic coinfections if the strength of the coupling matches that of the clustering. We also show that such dynamics lead to a first-order transition in endemic states, where small changes in transmissibility of the diseases can lead to explosive outbreaks and regions where these explosive outbreaks can only happen on clustered networks. We develop a mean-field model of coinfection of two diseases following susceptible-infectious-susceptible dynamics, which is allowed to interact on a general class of modular networks. We also introduce a criterion based on tertiary infections that yields precise analytical estimates of when clustering will lead to faster propagation than nonclustered networks. Our results carry importance for epidemiology, mathematical modeling, and the propagation of interacting phenomena in general. We make a call for more detailed epidemiological data of interacting coinfections." @default.
• W1889156735 created "2016-06-24" @default.
• W1889156735 creator A5035455593 @default.
• W1889156735 creator A5049359232 @default.
• W1889156735 date "2015-07-20" @default.
• W1889156735 modified "2023-10-06" @default.
• W1889156735 title "Complex dynamics of synergistic coinfections on realistically clustered networks" @default.
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• W1889156735 doi "https://doi.org/10.1073/pnas.1507820112" @default.
• W1889156735 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4547298" @default.
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• W1889156735 hasPublicationYear "2015" @default.
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