Factors Affecting Susceptibility to Intramammary Infection and Mastitis: An Approximate Bayesian Analysis

S. L. Rodriguez-Zas, D. Gianola, G. E. Shook

Research output: Contribution to journalArticlepeer-review

Abstract

Susceptibility to IMI and to mastitis in Holstein cows was studied using logistic mixed effects models and an approximate Bayesian analysis. Dichotomous response variables were the presence or absence of IMI, caused by any microorganism, IMI caused by Staphylococcus spp. or Corynebacterium spp., and clinical mastitis caused by any microorganism at specific lactation stages. Data included 619 lactation records from 282 cows. Fixed explanatory variables in the model were period, season and age at calving, lactation number, log-transformed SCC, and a joint effect of age and log SCC. Because random cow effects were assumed to be normally distributed and to have an unknown variance, this parameter was estimated by approximate marginal maximum likelihood. Results from the Bayesian analysis were contrasted with maximum likelihood estimates obtained from a fixed effects logistic model that ignored cow effects. Posterior mode and maximum likelihood estimates of location parameters were similar, although standard errors of the maximum likelihood estimates understated uncertainty. The IMI status during a previous lactation was a poor predictor of IMI status in subsequent lactations, and susceptibility increased as SCC increased. Interlactation (logit scale) repeatability estimates of susceptibility ranged from 0.22 to 0.23. A Taylor series expansion was used to approximate correlations between lactations on a binary scale. These correlations depended on associated fixed effects and ranged between 0.12 and 0.18, which were lower than correlations using the logit scale.

Original languageEnglish (US)
Pages (from-to)75-85
Number of pages11
JournalJournal of Dairy Science
Volume80
Issue number1
DOIs
StatePublished - Jan 1997
Externally publishedYes

Keywords

  • Bayesian analysis
  • Intramammary infection
  • Logistic mixed model
  • Mastitis

ASJC Scopus subject areas

  • Food Science
  • Animal Science and Zoology
  • Genetics

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