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dc.contributor.author
Andreo, Verónica Carolina  
dc.contributor.author
Glass, Gregory  
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Shields, Timothy  
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Provensal, María Cecilia  
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Polop, Jaime  
dc.date.available
2023-03-16T10:42:46Z  
dc.date.issued
2011-09  
dc.identifier.citation
Andreo, Verónica Carolina; Glass, Gregory; Shields, Timothy; Provensal, María Cecilia; Polop, Jaime; Modeling potential distribution of oligoryzomys longicaudatus, the andes virus (Genus: Hantavirus) reservoir, in Argentina; Springer; Ecohealth; 8; 3; 9-2011; 332-348  
dc.identifier.issn
1612-9202  
dc.identifier.uri
http://hdl.handle.net/11336/190703  
dc.description.abstract
We constructed a model to predict the potential distribution of Oligoryzomys longicaudatus, the reservoir of Andes virus (Genus: Hantavirus), in Argentina. We developed an extensive database of occurrence records from published studies and our own surveys and compared two methods to model the probability of O. longicaudatus presence; logistic regression and MaxEnt algorithm. The environmental variables used were tree, grass and bare soil cover from MODIS imagery and, altitude and 19 bioclimatic variables from WorldClim database. The models performances were evaluated and compared both by threshold dependent and independent measures. The best models included tree and grass cover, mean diurnal temperature range, and precipitation of the warmest and coldest seasons. The potential distribution maps for O. longicaudatus predicted the highest occurrence probabilities along the Andes range, from 32°S and narrowing southwards. They also predicted high probabilities for the south-central area of Argentina, reaching the Atlantic coast. The Hantavirus Pulmonary Syndrome cases coincided with mean occurrence probabilities of 95 and 77% for logistic and MaxEnt models, respectively. HPS transmission zones in Argentine Patagonia matched the areas with the highest probability of presence. Therefore, colilargos presence probability may provide an approximate risk of transmission and act as an early tool to guide control and prevention plans.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Springer  
dc.rights
info:eu-repo/semantics/restrictedAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
ARGENTINA  
dc.subject
HANTAVIRUS RESERVOIR  
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LOGISTIC REGRESSION  
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MAXENT ALGORITHM  
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OLIGORYZOMYS LONGICAUDATUS  
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POTENTIAL DISTRIBUTION  
dc.subject.classification
Ecología  
dc.subject.classification
Ciencias Biológicas  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Modeling potential distribution of oligoryzomys longicaudatus, the andes virus (Genus: Hantavirus) reservoir, in Argentina  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2023-03-15T20:27:40Z  
dc.journal.volume
8  
dc.journal.number
3  
dc.journal.pagination
332-348  
dc.journal.pais
Alemania  
dc.journal.ciudad
Berlin  
dc.description.fil
Fil: Andreo, Verónica Carolina. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas, Fisicoquímicas y Naturales. Departamento de Ciencias Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina  
dc.description.fil
Fil: Glass, Gregory. The Johns Hopkins Bloomberg School of Public Health; Estados Unidos  
dc.description.fil
Fil: Shields, Timothy. The Johns Hopkins Bloomberg School of Public Health; Estados Unidos  
dc.description.fil
Fil: Provensal, María Cecilia. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas, Fisicoquímicas y Naturales. Departamento de Ciencias Naturales; Argentina  
dc.description.fil
Fil: Polop, Jaime. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas, Fisicoquímicas y Naturales. Departamento de Ciencias Naturales; Argentina  
dc.journal.title
Ecohealth  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://link.springer.com/article/10.1007/s10393-011-0719-5  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1007/s10393-011-0719-5