The use of satellite data in modeling population dynamics and prevalence of infection in the rodent reservoir of Junin virus

• Autores: Porcasi, X; Calderón, Gladys; Lamfri, Mario; Gardenal, Cristina N; Polop, Jaime J; Sabattini, Marta S.; Scavuzzo, C. M.
• Año de publicación: 2005
• Idioma: inglés
• Tipo de recurso: artículo
• Fuente: Ecological Modelling 2005; 185(2):437-449
• Materia: Fiebre Hemorrágica Americana; Virus Junin
• Institución: Administración Nacional de Laboratorios e Institutos de Salud "Dr. Carlos G. Malbrán"

Fil: Porcasi. X. Instituto Gulich, Comisión Nacional de Actividades Espaciales, Centro Espacial Teófilo Tabanera; Argentina.
Fil: Calderón, Gladys. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Enfermedades Virales Humanas; Argentina.
Fil: Lamfri, Mario. Instituto Gulich, Comisión Nacional de Actividades Espaciales, Centro Espacial Teófilo Tabanera; Argentina.
Fil: Gardenal, Cristina N. Universidad Nacional de Córdoba, Córdoba; Argentina.
Fil: Polop, Jaime J. Universidad Nacional de Río Cuarto, Río Cuarto; Argentina.
Fil: Sabattini, Marta S. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Enfermedades Virales Humanas; Argentina.
Fil: Scavuzzo, C. M. Instituto Gulich, Comisión Nacional de Actividades Espaciales, Centro Espacial Teófilo Tabanera; Argentina.
We present the first results of a simple numerical model of rodent population dynamics and viral infection for Junin virus, etiologic agent of Argentine hemorrhagic fever (AHF), in its host, Calomys musculinus. In contrast to the more common statistical approach, the model incorporates satellite-derived environmental data in a causal approach. In addition, the model incorporates specific biological characteristics of the host, such as birth rate and longevity. Theoretical and actual rodent population densities are compared with several years of capture data at locations on the Argentine pampas. The model appears to be a good tool for simulating dynamics of populations using remotely sensed data. Results are in agreement with field data showing maximum population densities during the autumn in most localities. The differences between simulated population densities and field observed values indicate that, although computer simulation is useful to obtain some aspects of population dynamics, improvements should be introduced in order to generate more robust results.