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. 2013 Dec;37(4):259-67.
doi: 10.1007/s11259-013-9570-1. Epub 2013 Jun 19.

Comparison of the epidemiological behavior of mastitis pathogens by applying time-series analysis in results of milk samples submitted for microbiological examination

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Comparison of the epidemiological behavior of mastitis pathogens by applying time-series analysis in results of milk samples submitted for microbiological examination

G Fernández et al. Vet Res Commun. 2013 Dec.

Abstract

The objective of this study is to examine and compare the trends of mastitis pathogens in quarter milk samples (n = 240,232) submitted for microbiological examination at the Milk Analysis Laboratory (L.I.G.A.L.) at Galicia, Spain from June 2005 to September 2011. Autoregressive Integrated Moving Average (ARIMA) models and multivariate statistical techniques such as Cluster Analysis were used in order to detect seasonal trends and similarities between the series trends and to classify mastitis pathogens into relatively homogeneous groups. The decrease of bulk milk somatic cell counts achieved by the mastitis control program, developed in recent years in this region, is the result of the decrease in IMI caused by a limited number of mastitis pathogens. The obtained results reflect a greater complexity in the behavior of mastitis pathogens, unlike the traditional classification into contagious or environmental. Staphylococcus aureus showed a trend similar to Streptococcus dysgalactiae, a mastitis pathogen can behave in both a contagious and an environmental manner. Among the traditionally considered environmental mastitis pathogens, Strep. uberis showed a different behavior to Escherichia coli and Klebsiella pneumoniae. Coagulase-negative staphylococci (CNS) species and Streptococcus other than Strep. agalactiae showed differences in the trend model. Time-series analysis and multivariate statistical techniques, such as Cluster Analysis, could be powerful tools to assess the isolation trend of mastitis pathogens because of their ability to cope with stochastic dependence of consecutive data. Furthermore, they could be used to identify the epidemiological behavior of mastitis pathogens using the results of milk samples submitted for routine microbiological examination, by classifying them into relatively homogeneous groups.

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