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

• Autor(a) principal: Moreno,Eduardo S
• Data de Publicação: 2015
• Outros Autores: Agostini,Ilaria, Holzmann,Ingrid, Di Bitetti,Mario S, Oklander,Luciana I, Kowalewski,Martín M, Beldomenico,Pablo M, Goenaga,Silvina, Martínez,Mariela, Lestani,Eduardo, Desbiez,Arnaud LJ, Miller,Philip
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Memórias do Instituto Oswaldo Cruz
• Texto Completo: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762015000700865
• topic: conservation medicine; wildlife disease; disease impact; sensitivity analysis

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.