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Cryptosporidium spp., comparative diagnosis and geospatial distribution in diarrheic calves from dairy farms, Valdivia, Chile

Cryptosporidium spp., comparative diagnosis and geospatial distribution in diarrheic calves from dairy farms, Valdivia, Chile



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Muñoz A, P., Mercado P, R., Morales T, G., Bravo O, V., & Raffo C, E. (2014). Cryptosporidium spp., comparative diagnosis and geospatial distribution in diarrheic calves from dairy farms, Valdivia, Chile. Revista MVZ Córdoba, 19(1), 3954-3961. https://doi.org/10.21897/rmvz.115

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PlumX
Pamela Muñoz A
Rubén Mercado P
Gabriela Morales T
Viviana Bravo O
Eduardo Raffo C

ABSTRACT

Objective. To determine the Cryptosporidium spp. infection frequency by using Ziehl-Neelsen and Auramine stains on samples obtained from diarrheic calves from milking farms of the Valdivia province. To compare both diagnostic tests and to determine the geospatial distribution of the infections caused by this protozoan. Materials and methods. 221 fecal samples of diarrheic calves of 24 milking farms of the Valdivia province were studied. The processing and analysis of the samples was done by Ziehl-Neelsen (ZN) and Auramine (AU) staining techniques, and the results were compared by McNemar statistical test and the concordance level was determined by kappa index. A map was also generated to determine the geospatial distribution of Cryptosporidium infections. Results. 57.9% of all the animals tested were classified as positive with the ZN stain test, while 55.6% of all the animals turned out positive for the AU stain test. The McNemar test showed no significant difference between both diagnostic techniques (p>0.05), while the kappa index showed proper concordance between tests (κ=0.73). 100% of the farms studied showed protozoan presence demonstrating the broad distribution of the parasite, however, and considering the previous factor, it was not possible to determine geospatial associations for the parasite distribution. Conclusions. The infection frequency of Cryptosporidium is higher than 50% in the milking farms studied from the Valdivia province. No difference between the Ziehl-Neelsen and Auramine staining techniques was demonstrated showing very consistent results. It was possible to detect that the number of farms infected correspond to 100% of the farms analyzed.


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