Modeling the spread of vector-borne diseases on bipartite networks
Vector-borne diseases for which transmission occurs exclusively between vectors and hosts can be modeled as spreading on a bipartite network. 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 t...
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| Veröffentlicht in: | PloS one 2010-11, Vol.5 (11), p.e13796-e13796 |
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| creator | Bisanzio, Donal Bertolotti, Luigi Tomassone, Laura Amore, Giusi Ragagli, Charlotte Mannelli, Alessandro Giacobini, Mario Provero, Paolo |
| description | Vector-borne diseases for which transmission occurs exclusively between vectors and hosts can be modeled as spreading on a bipartite network.
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.
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. |
| doi_str_mv | 10.1371/journal.pone.0013796 |
| format | Article |
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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.
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.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0013796</identifier><identifier>PMID: 21103064</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Acari ; Algorithms ; Analysis ; Animal models ; Animals ; Arachnid Vectors ; Arachnids ; Asymptotic properties ; Biotechnology ; Borrelia ; Communicable Diseases - transmission ; Computational Biology/Ecosystem Modeling ; Computer Simulation ; Computer viruses ; Decay ; Disease transmission ; Encephalitis ; Epidemics ; Epidemiology ; Host-Parasite Interactions ; Infectious Diseases ; Ixodes - physiology ; Ixodes ricinus ; Ixodidae ; Lizards ; Mice ; Models, Biological ; Murinae ; Parasitic diseases ; Parasitology ; Public Health and Epidemiology ; Sexually transmitted diseases ; Simulation ; Spreading ; STD ; Tick Infestations - parasitology ; Ticks ; Vector-borne diseases ; Vectors ; Vectors (Biology)</subject><ispartof>PloS one, 2010-11, Vol.5 (11), p.e13796-e13796</ispartof><rights>COPYRIGHT 2010 Public Library of Science</rights><rights>2010 Bisanzio et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Bisanzio et al. 2010</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c723t-b7d202f851894259f3afe3b53f1d2d0403095310da3b54eedddcdd932142c853</citedby><cites>FETCH-LOGICAL-c723t-b7d202f851894259f3afe3b53f1d2d0403095310da3b54eedddcdd932142c853</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2980486/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2980486/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,724,777,781,861,882,2096,2915,23847,27905,27906,53772,53774,79349,79350</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21103064$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Munayco, Cesar V.</contributor><creatorcontrib>Bisanzio, Donal</creatorcontrib><creatorcontrib>Bertolotti, Luigi</creatorcontrib><creatorcontrib>Tomassone, Laura</creatorcontrib><creatorcontrib>Amore, Giusi</creatorcontrib><creatorcontrib>Ragagli, Charlotte</creatorcontrib><creatorcontrib>Mannelli, Alessandro</creatorcontrib><creatorcontrib>Giacobini, Mario</creatorcontrib><creatorcontrib>Provero, Paolo</creatorcontrib><title>Modeling the spread of vector-borne diseases on bipartite networks</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Vector-borne diseases for which transmission occurs exclusively between vectors and hosts can be modeled as spreading on a bipartite network.
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.
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.</description><subject>Acari</subject><subject>Algorithms</subject><subject>Analysis</subject><subject>Animal models</subject><subject>Animals</subject><subject>Arachnid Vectors</subject><subject>Arachnids</subject><subject>Asymptotic properties</subject><subject>Biotechnology</subject><subject>Borrelia</subject><subject>Communicable Diseases - transmission</subject><subject>Computational Biology/Ecosystem Modeling</subject><subject>Computer Simulation</subject><subject>Computer viruses</subject><subject>Decay</subject><subject>Disease transmission</subject><subject>Encephalitis</subject><subject>Epidemics</subject><subject>Epidemiology</subject><subject>Host-Parasite Interactions</subject><subject>Infectious Diseases</subject><subject>Ixodes - physiology</subject><subject>Ixodes ricinus</subject><subject>Ixodidae</subject><subject>Lizards</subject><subject>Mice</subject><subject>Models, Biological</subject><subject>Murinae</subject><subject>Parasitic diseases</subject><subject>Parasitology</subject><subject>Public Health and Epidemiology</subject><subject>Sexually transmitted diseases</subject><subject>Simulation</subject><subject>Spreading</subject><subject>STD</subject><subject>Tick Infestations - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bisanzio, Donal</au><au>Bertolotti, Luigi</au><au>Tomassone, Laura</au><au>Amore, Giusi</au><au>Ragagli, Charlotte</au><au>Mannelli, Alessandro</au><au>Giacobini, Mario</au><au>Provero, Paolo</au><au>Munayco, Cesar V.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modeling the spread of vector-borne diseases on bipartite networks</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2010-11-12</date><risdate>2010</risdate><volume>5</volume><issue>11</issue><spage>e13796</spage><epage>e13796</epage><pages>e13796-e13796</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Vector-borne diseases for which transmission occurs exclusively between vectors and hosts can be modeled as spreading on a bipartite network.
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.
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.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>21103064</pmid><doi>10.1371/journal.pone.0013796</doi><tpages>e13796</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Acari Algorithms Analysis Animal models Animals Arachnid Vectors Arachnids Asymptotic properties Biotechnology Borrelia Communicable Diseases - transmission Computational Biology/Ecosystem Modeling Computer Simulation Computer viruses Decay Disease transmission Encephalitis Epidemics Epidemiology Host-Parasite Interactions Infectious Diseases Ixodes - physiology Ixodes ricinus Ixodidae Lizards Mice Models, Biological Murinae Parasitic diseases Parasitology Public Health and Epidemiology Sexually transmitted diseases Simulation Spreading STD Tick Infestations - parasitology Ticks Vector-borne diseases Vectors Vectors (Biology) |
| title | Modeling the spread of vector-borne diseases on bipartite networks |
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