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Detalle de: Stochastic analysis of Ebola infection in small zoonotic niches

Title Stochastic analysis of Ebola infection in small zoonotic niches
Abstract

The size of fruit bat colonies ranges from dozens to hundreds of thousands of individuals, depending on the species. While a deterministic modelling approach is appropriate for large colonies, the role of population fluctuations can be all-important for small colonies. From this perspective, we analyse the infection dynamics in small zoonotic niches due to filoviruses, e.g. Ebola. To this end, we perform stochastic numerical simulations and analytical calculations. The inherent stochasticity in ecological processes may play a significant role in driving small populations towards extinction. Here, we reveal that fluctuations can either lead to virus eradication or to sustain infection compared with the deterministic dynamics, depending on the size of the zoonotic niche. Altogether, our findings reveal non-trivial stochastic effects, which can shed light on the infection dynamics in small- and medium-sized bat colonies and help design preventive measures for zoonotic diseases.

Apa Reference Mursel, S., Bocchini, P., & Buceta, J. (2024). Stochastic analysis of Ebola infection in small zoonotic niches. Royal Society Open Science, 11(11). 10.1098/rsos.240298
Doi 10.1098/rsos.240298
Publication Date Nov 2024
Publication Type Article
Researcher Javier Buceta
Ontology Computational models and simulations, Animal health
Research Groups TheSiMBioSys (Theoretical and In Silico Modeling of Biological Systems)
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