TY - JOUR
T1 - Modeling potential distribution of oligoryzomys longicaudatus, the andes virus (Genus: Hantavirus) reservoir, in Argentina
AU - Andreo, Verónica
AU - Glass, Gregory
AU - Shields, Timothy
AU - Provensal, Cecilia
AU - Polop, Jaime
N1 - Funding Information:
This research was made possible by grants from the Fondo para la Investigación Científica y Tecnológica (FONCYT) and Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). This article was written as a result of an internship of V.A. funded by Fulbright and Bunge and Born Foundation at the Johns Hopkins Bloomberg School of Public Health, Baltimore, USA. V.A. thanks Fulbright and Bunge and Born Foundation for the financial assistance and the host institution for great working facilities. We are also grateful to two anonymous reviewers who provided valuable comments and suggestions on an early version of the manuscript.
PY - 2011/9
Y1 - 2011/9
N2 - 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.
AB - 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.
KW - Argentina
KW - MaxEnt algorithm
KW - Oligoryzomys longicaudatus
KW - hantavirus reservoir
KW - logistic regression
KW - potential distribution
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U2 - 10.1007/s10393-011-0719-5
DO - 10.1007/s10393-011-0719-5
M3 - Review article
C2 - 22130568
AN - SCOPUS:84859949676
SN - 1612-9202
VL - 8
SP - 332
EP - 348
JO - EcoHealth
JF - EcoHealth
IS - 3
ER -