000063311 001__ 63311
000063311 005__ 20171129112117.0
000063311 0247_ $$2doi$$a10.1371/journal.pcbi.1003169
000063311 0248_ $$2sideral$$a82824
000063311 037__ $$aART-2013-82824
000063311 041__ $$aeng
000063311 100__ $$aPoletto, C.
000063311 245__ $$aHost Mobility Drives Pathogen Competition in Spatially Structured Populations
000063311 260__ $$c2013
000063311 5060_ $$aAccess copy available to the general public$$fUnrestricted
000063311 5203_ $$aInteractions among multiple infectious agents are increasingly recognized as a fundamental issue in the understanding of key questions in public health regarding pathogen emergence, maintenance, and evolution. The full description of host-multipathogen systems is, however, challenged by the multiplicity of factors affecting the interaction dynamics and the resulting competition that may occur at different scales, from the within-host scale to the spatial structure and mobility of the host population. Here we study the dynamics of two competing pathogens in a structured host population and assess the impact of the mobility pattern of hosts on the pathogen competition. We model the spatial structure of the host population in terms of a metapopulation network and focus on two strains imported locally in the system and having the same transmission potential but different infectious periods. We find different scenarios leading to competitive success of either one of the strain or to the codominance of both strains in the system. The dominance of the strain characterized by the shorter or longer infectious period depends exclusively on the structure of the population and on the the mobility of hosts across patches. The proposed modeling framework allows the integration of other relevant epidemiological, environmental and demographic factors, opening the path to further mathematical and computational studies of the dynamics of multipathogen systems.   

Author Summary: 
When multiple infectious agents circulate in a given population of hosts, they interact for the exploitation of susceptible hosts aimed at pathogen survival and maintenance. Such interaction is ruled by the combination of different mechanisms related to the biology of host-pathogen interaction, environmental conditions and host demography and behavior. We focus on pathogen competition and we investigate whether the mobility of hosts in a spatially structured environment can act as a selective driver for pathogen circulation. We use mathematical and computational models for disease transmission between hosts and for the mobility of hosts to study the competition between two pathogens providing each other full cross-immunity after infection. Depending on the rate of migration of hosts, competition results in the dominance of either one of the pathogens at the spatial level – though the two infectious agents are characterized by the same invasion potential at the single population scale – or cocirculation of both. These results highlight the importance of explicitly accounting for the spatial scale and for the different time scales involved (i.e. host mobility and spreading dynamics of the two pathogens) in the study of host-multipathogen systems.
000063311 536__ $$9info:eu-repo/grantAgreement/ES/DGA/FENOL-GROUP$$9info:eu-repo/grantAgreement/ES/MINECO/FIS2011-25167
000063311 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000063311 590__ $$a4.829$$b2013
000063311 591__ $$aMATHEMATICAL & COMPUTATIONAL BIOLOGY$$b3 / 51 = 0.059$$c2013$$dQ1$$eT1
000063311 591__ $$aBIOCHEMICAL RESEARCH METHODS$$b10 / 77 = 0.13$$c2013$$dQ1$$eT1
000063311 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000063311 700__ $$0(orcid)0000-0001-6202-3302$$aMeloni, S.$$uUniversidad de Zaragoza
000063311 700__ $$aColizza, V.
000063311 700__ $$0(orcid)0000-0002-0895-1893$$aMoreno, Y.$$uUniversidad de Zaragoza
000063311 700__ $$aVespignani, A.
000063311 7102_ $$12004$$2405$$aUniversidad de Zaragoza$$bDepartamento de Física Teórica$$cFísica Teórica
000063311 7102_ $$19999$$2999$$aUniversidad de Zaragoza$$bSIN ADSCRIPCION$$cSin Adscripción
000063311 773__ $$g9, 8 (2013), 1003169 [12 pp]$$pPLoS Comput. Biol.$$tPLoS Computational Biology$$x1553-734X
000063311 8564_ $$s910170$$uhttps://zaguan.unizar.es/record/63311/files/texto_completo.pdf$$yVersión publicada
000063311 8564_ $$s128971$$uhttps://zaguan.unizar.es/record/63311/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000063311 909CO $$ooai:zaguan.unizar.es:63311$$particulos$$pdriver
000063311 951__ $$a2017-11-28-12:46:34
000063311 980__ $$aARTICLE