Publication: Estimación bayesiana de la prevalencia de mamitis subclínica en una población de vacuno de leche española
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2022-07-18
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Abstract
El objetivo de este trabajo fue la estimación de la prevalencia de mamitis subclínica en una población de vacuno de leche en España a partir de la información de 321 ganaderías con un total de 33.182 vacas. Para ello se utilizaron dos pruebas diagnósticas, el diagnóstico en granja confirmado mediante test de California y el recuento de células somáticas (RCS). Se estimaron, además de la prevalencia de mamitis subclínica, la sensibilidad y especificidad de ambas pruebas diagnósticas mediante la implementación de metodología bayesiana. Para ello se dividió a la población en tres periodos de tiempo (2013-2015,2016-2018 y 2019-2020) y se utilizó un proceso iterativo para la elicitación de los hiperparámetros de las distribuciones a priori utilizando las distribuciones posteriores del periodo inmediatamente anterior, excepto para la elicitación de los hiperparámetros de las distribuciones a priori del primer periodo donde se utilizó la información recogida en la bibliografía. Así, se asumieron distribuciones Beta para la prevalencia, sensibilidad y especificidad y una distribución multinomial para las verosimilitudes. Se realizaron análisis de sensibilidad para estimar el impacto de las distribuciones a priori en los resultados obtenidos. La prevalencia media estimada en la población fue de entre el 5% (4,2%-7,5%) y el 15,7% (6,4%-38,7%). El diagnóstico en granja obtuvo altos valores medios de sensibilidad (87%-89%) y una baja o moderada especificidad media (54,3%-64,5%), mientras que el recuento de células somáticas se mostró como una prueba de alta especificidad, con valores medios entre un 96,4% y un 97,7%, pero con una sensibilidad baja o moderada, con resultados medios de entre el 47,3 y el 79,1%. Por tanto, las dos pruebas se muestran como complementarias para un correcto diagnóstico de mamitis subclínica, una de alta especificidad (RCS) y otra de alta sensibilidad (diagnóstico en granja), pudiendo ser utilizada RCS para un primer cribado y el diagnóstico en granja mediante conformación con test de California como confirmación de los casos.
This work applied the Bayesian approach to estimate the prevalence of subclinical mastitis in a Spanish population which included data from 321 herds and 33.182 cows. For this estimation two tests were used: diagnosis by farmers or vets with California test confirmation and somatic cell count (SCC). In addition, sensitivity and specificity of those tests were estimated. Data was divided in 3 periods (2013-2015,2016-2018, and 2019-2020) and an iterative process was implemented for the elicitation of the hyperparameters of the prior distributions of prevalence, and sensitivity and specificity of the two tests. Beta distributions were used for the distributions of prevalence, and sensitivity and specificity of the tests, and multinomial distribution as likelihood’s functions. Prevalence of subclinical mastitis was from 5% (4.2%-7.5%) to 15.7% (6.4%-38.7%). Farmers or vets’ diagnosis with California test conformation showed high average sensitivity (84%-89%) and low or moderate average specificity (54.3%-64.5%). On other hand, somatic cell count showed high average specificity (96.4-97.7%) and low or moderate sensitivity (47.3-79.1%). For instance, the use of the two tests should be complementary for the diagnosis of subclinical mastitis, firstly with the use of somatic cells count and secondly using California test for the positives´ confirmations.
This work applied the Bayesian approach to estimate the prevalence of subclinical mastitis in a Spanish population which included data from 321 herds and 33.182 cows. For this estimation two tests were used: diagnosis by farmers or vets with California test confirmation and somatic cell count (SCC). In addition, sensitivity and specificity of those tests were estimated. Data was divided in 3 periods (2013-2015,2016-2018, and 2019-2020) and an iterative process was implemented for the elicitation of the hyperparameters of the prior distributions of prevalence, and sensitivity and specificity of the two tests. Beta distributions were used for the distributions of prevalence, and sensitivity and specificity of the tests, and multinomial distribution as likelihood’s functions. Prevalence of subclinical mastitis was from 5% (4.2%-7.5%) to 15.7% (6.4%-38.7%). Farmers or vets’ diagnosis with California test conformation showed high average sensitivity (84%-89%) and low or moderate average specificity (54.3%-64.5%). On other hand, somatic cell count showed high average specificity (96.4-97.7%) and low or moderate sensitivity (47.3-79.1%). For instance, the use of the two tests should be complementary for the diagnosis of subclinical mastitis, firstly with the use of somatic cells count and secondly using California test for the positives´ confirmations.
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