Artículo

Yellow fever impact on brown howler monkeys (Alouatta guariba clamitans) in Argentina: a metamodeling approach based in population viability analysis and epidemiological dynamics

Moreno, Eduardo S. ; Agostini, Ilaria Icon; Holzmann, Ingrid Icon; Di Bitetti, Mario Santiago Icon; Oklander, Luciana Inés Icon; Kowalewski, Miguel Martin Icon; Beldomenico, Pablo Martín Icon; Goenaga, Silvina ; Martínez, Mariela Florencia Icon; Lestani, Eduardo Ariel Icon; Desbiez, Arnaud L. J. ; Miller, Philip

Otros responsables

Fecha

11/2015

Editorial

Fundacao Oswaldo Cruz

Revista

Memórias do Instituto Oswaldo Cruz

Título del libro

Nombre del evento

Fecha del evento

Institución organizadora

ISSN

0074-0276

eISSN

1678-8060

ISBN

Idioma

Inglés

Tipo del evento

Clasificación temática

Resumen

In South America, yellow fever (YF) is an established infectious disease that has been identified outside of its traditional endemic areas, affecting human and nonhuman primate (NHP) populations. In the epidemics that occurred in Argentina between 2007-2009, several outbreaks affecting humans and howler monkeys (Alouatta spp) were reported, highlighting the importance of this disease in the context of conservation medicine and public health policies. Considering the lack of information about YF dynamics in New World NHP, our main goal was to apply modelling tools to better understand YF transmission dynamics among endangered brown howler monkey (Alouatta guariba clamitans) populations in northeastern Argentina. Two complementary modelling tools were used to evaluate brown howler population dynamics in the presence of the disease: Vortex, a stochastic demographic simulation model, and Outbreak, a stochastic disease epidemiology simulation. The baseline model of YF disease epidemiology predicted a very high probability of population decline over the next 100 years. We believe the modelling approach discussed here is a reasonable description of the disease and its effects on the howler monkey population and can be useful to support evidence-based decision-making to guide actions at a regional level.

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