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Título: | Accelerometer-based detection of African swine fever infection in wild boar |
Autor: | Morelle, Kevin; Barasona, Jose A.; Bosch, Jaime CSIC ORCID ; Heine, Georg; Daim, Andreas; Arnold, Janosch; Bauch, Toralf; Kosowska, Aleksandra; Cadenas-Fernández, Estefanía; Martínez Avilés, Marta; Zuñiga, Daniel; Wikelski, Martin; Vizcaino-Sanchez, Jose Manuel; Safi, Kamran | Palabras clave: | African swine fever Animal sentinel Biosignal Wild boar Wildlife disease monitoring |
Fecha de publicación: | 30-ago-2023 | Editor: | Royal Society (Great Britain) | Citación: | Proceedings of the Royal Society of London - B 290(2005): e20231396 (2023) | Resumen: | Infectious wildlife diseases that circulate at the interface with domestic animals pose significant threats worldwide and require early detection and warning. Although animal tracking technologies are used to discern behavioural changes, they are rarely used to monitor wildlife diseases. Common disease-induced behavioural changes include reduced activity and lethargy ('sickness behaviour'). Here, we investigated whether accelerometer sensors could detect the onset of African swine fever (ASF), a viral infection that induces high mortality in suids for which no vaccine is currently available. Taking advantage of an experiment designed to test an oral ASF vaccine, we equipped 12 wild boars with an accelerometer tag and quantified how ASF affects their activity pattern and behavioural fingerprint, using overall dynamic body acceleration. Wild boars showed a daily reduction in activity of 10-20% from the healthy to the viremia phase. Using change point statistics and comparing healthy individuals living in semi-free and free-ranging conditions, we show how the onset of disease-induced sickness can be detected and how such early detection could work in natural settings. Timely detection of infection in animals is crucial for disease surveillance and control, and accelerometer technology on sentinel animals provides a viable complementary tool to existing disease management approaches. | Descripción: | 10 Pag. | Versión del editor: | https://doi.org/10.1098/rspb.2023.1396 | URI: | http://hdl.handle.net/10261/347539 | DOI: | 10.1098/rspb.2023.1396 | ISSN: | 0962-8452 | E-ISSN: | 1471-2954 |
Aparece en las colecciones: | (INIA) Artículos |
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Accelerometer_based_detection.pdf | artículo | 1,32 MB | Adobe PDF | Visualizar/Abrir |
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