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Modeling the Spread of Vector-Borne Diseases on Bipartite Networks
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 distribution of the two classes of node...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2980486/ https://www.ncbi.nlm.nih.gov/pubmed/21103064 http://dx.doi.org/10.1371/journal.pone.0013796 |
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author | Bisanzio, Donal Bertolotti, Luigi Tomassone, Laura Amore, Giusi Ragagli, Charlotte Mannelli, Alessandro Giacobini, Mario Provero, Paolo |
author_facet | Bisanzio, Donal Bertolotti, Luigi Tomassone, Laura Amore, Giusi Ragagli, Charlotte Mannelli, Alessandro Giacobini, Mario Provero, Paolo |
author_sort | Bisanzio, Donal |
collection | PubMed |
description | 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 distribution 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 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. |
format | Text |
id | pubmed-2980486 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-29804862010-11-22 Modeling the Spread of Vector-Borne Diseases on Bipartite Networks Bisanzio, Donal Bertolotti, Luigi Tomassone, Laura Amore, Giusi Ragagli, Charlotte Mannelli, Alessandro Giacobini, Mario Provero, Paolo PLoS One Research Article 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 distribution 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 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. Public Library of Science 2010-11-12 /pmc/articles/PMC2980486/ /pubmed/21103064 http://dx.doi.org/10.1371/journal.pone.0013796 Text en Bisanzio et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Bisanzio, Donal Bertolotti, Luigi Tomassone, Laura Amore, Giusi Ragagli, Charlotte Mannelli, Alessandro Giacobini, Mario Provero, Paolo Modeling the Spread of Vector-Borne Diseases on Bipartite Networks |
title | Modeling the Spread of Vector-Borne Diseases on Bipartite Networks |
title_full | Modeling the Spread of Vector-Borne Diseases on Bipartite Networks |
title_fullStr | Modeling the Spread of Vector-Borne Diseases on Bipartite Networks |
title_full_unstemmed | Modeling the Spread of Vector-Borne Diseases on Bipartite Networks |
title_short | Modeling the Spread of Vector-Borne Diseases on Bipartite Networks |
title_sort | modeling the spread of vector-borne diseases on bipartite networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2980486/ https://www.ncbi.nlm.nih.gov/pubmed/21103064 http://dx.doi.org/10.1371/journal.pone.0013796 |
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