Background: Vector-borne diseases for which transmission occurs exclusively between vectors and hosts can be modeled as spreading on a bipartite network. Methodology/Principal Findings: In such models the spreading of the disease strongly depends on the degree distributions of the two classes of nodes. It is sufficient for one of the classes to have a scale-free degree distribution with a slow enough decay for the network to have asymptotically vanishing epidemic threshold. Data on the distribution of {\it Ixodes ricinus} ticks on mice and lizards from two independent studies are well described by a scale-free distribution compatible with an asymptotically vanishing epidemic threshold. The commonly used negative binomial, instead, cannot describe the right tail of the empirical distribution. Conclusions/Significance: The extreme aggregation of vectors on hosts, described by the power-law decay of the degree distribution, makes the epidemic threshold decrease with the size of the network and vanish asymptotically.

Modeling the Spread of Vector-Borne Diseases on Bipartite Networks

BISANZIO, DONAL;BERTOLOTTI, Luigi;TOMASSONE, Laura;MANNELLI, Alessandro;GIACOBINI, Mario Dante Lucio;PROVERO, Paolo
2010-01-01

Abstract

Background: Vector-borne diseases for which transmission occurs exclusively between vectors and hosts can be modeled as spreading on a bipartite network. Methodology/Principal Findings: In such models the spreading of the disease strongly depends on the degree distributions of the two classes of nodes. It is sufficient for one of the classes to have a scale-free degree distribution with a slow enough decay for the network to have asymptotically vanishing epidemic threshold. Data on the distribution of {\it Ixodes ricinus} ticks on mice and lizards from two independent studies are well described by a scale-free distribution compatible with an asymptotically vanishing epidemic threshold. The commonly used negative binomial, instead, cannot describe the right tail of the empirical distribution. Conclusions/Significance: The extreme aggregation of vectors on hosts, described by the power-law decay of the degree distribution, makes the epidemic threshold decrease with the size of the network and vanish asymptotically.
2010
5(11)
e13796
-
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2980486/pdf/pone.0013796.pdf
Donal Bisanzio; Luigi Bertolotti; Laura Tomassone; Giusi Amore; Charlotte Ragagli; Alessandro Mannelli; Mario Giacobini; Paolo Provero
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/82845
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