Biomedical subjects

A J Branscum

Publications and source records attributed to A J Branscum.

5 recordsLinked to original sources

PubMed2006

Relationships between milk culture results and treatment for clinical mastitis or culling in Norwegian dairy cattle.

In quarter milk samples from 2,492 randomly sampled cows that were selected without regard to their current or previous udder health status, the relationships between the following outcome variables were studied: treatment of clinical mastitis; the joint event of either treatment or culling for mastitis; culling for all reasons; culling specifically for mastitis; and the covariates of positive milk culture for Staphylococcus aureus, Streptococcus spp., and coagulase-negative Staphylococcus spp., or other pathogens, or of negative culture for mastitis pathogens. Microbiological diagnoses were assigned at the cow level, and altogether 3,075 diagnoses were related to the outcome variables. The relation between the absence of pathogens and rich (>1,500 cfu/mL of milk) or sparse (<or=1,500 cfu/mL of milk) growth of Staph. aureus were also assessed separately for each outcome variable. The hazard of treatment of clinical mastitis was greater for cows diagnosed with Staph. aureus compared with cows with no pathogens in all analyses. Cows with sparse growth of Staph. aureus upon microbiological analysis were more likely to be treated for clinical mastitis, and cows with rich growth of the bacteria experienced a higher overall risk of culling when the models adjusted for cow composite milk somatic cell count. No difference between rich and sparse growth of Staph. aureus was found when mastitis was defined as the joint event of either culling for mastitis or treatment of clinical mastitis, and when the relationship with culling specifically for mastitis was assessed. The combined outcome of treatment and culling for mastitis was related to a positive diagnosis of Strep. spp. after cow composite milk somatic cell count was omitted from the model. Presence of Streptococcus spp. was also related to culling specifically for mastitis, whereas culling for all reasons and treatment of clinical mastitis was not related to a positive culture of Strep. spp. Presence of coagulase-negative Staph. spp. or other pathogens was not associated with either of the outcome variables.

Animals↗

PubMed2005

Effect of diagnostic testing error on intracluster correlation coefficient estimation.

Estimation of the intracluster correlation coefficient (ICC) for infectious animal diseases may be of interest for survey planning and for calculating variance inflation factors for estimators of prevalence. Typically, diagnostic tests with imperfect sensitivity and specificity are used in surveys. In such studies, where animals from multiple herds are tested, the ICC often is estimated using apparent (test-based) rather than true prevalence data. Through Monte Carlo simulation, we examined the effect of substituting diagnostic test outcomes for true infection status on an ANOVA estimator of ICC, which was designed for use with true infection status data. We considered effects of diagnostic test sensitivity and specificity on the estimated ICC when the true ICC value and infection status of the sampled individuals were known. The ANOVA estimator underestimated the true ICC when the diagnostic test was imperfect. We also demonstrated, under the beta-binomial model, that the ICC based on apparent infection status for individuals is < or = ICC based on true infection status. In addition, we propose a Bayesian model for estimating the ICC that incorporates imperfect sensitivity and specificity and illustrate the Bayesian model using a simulation study and one example; a seroprevalence survey of ovine progressive pneumonia in U.S. sheep flocks.

Animals↗

PubMed2005

Estimation of diagnostic-test sensitivity and specificity through Bayesian modeling.

We review recent Bayesian approaches to estimation (based on cross-sectional sampling designs) of the sensitivity and specificity of one or more diagnostic tests. Our primary goal is to provide veterinary researchers with a concise presentation of the computational aspects involved in using the Bayesian framework for test evaluation. We consider estimation of diagnostic-test sensitivity and specificity in the following settings: (i) one test in one population, (ii) two conditionally independent tests in two or more populations, (iii) two correlated tests in two or more populations, and (iv) three tests in two or more populations, where two tests are correlated but jointly independent of the third test. For each scenario, we describe a Bayesian model that incorporates parameters of interest. The WinBUGS code used to fit each model, which is available at http://www.epi.ucdavis.edu/diagnos-tictests/, can be altered readily to conform to different data.

Animals↗

PubMed2005

Predicting the probability of abortion in dairy cows: a hierarchical Bayesian logistic-survival model using sequential pregnancy data.

Although abortion contributes substantially to poor reproductive health of dairy herds, little is known about the predictability of abortion based on age, previous abortion or gravidity (number of previous pregnancies). A poor understanding of effects of maternal factors on abortion risk exists, in part, because of methodological difficulties related to non-independence of multiple pregnancies of the same cow in analysis of fetal survival data. We prospectively examined sequential pregnancies to investigate relationships between fetal survival and putative dam risk factors for 2991 abortions from 24,706 pregnancies of 13,145 cows in nine California dairy herds. Relative risks and predicted probabilities of abortion (PPA) were estimated using a previously described hierarchical Bayesian logistic-survival model generalized to incorporate longitudinal data of multiple pregnancies from a single cow. The PPA increased with increasing dam age at conception, with increasing number of previous abortions, and if the previous pregnancy was aborted >60 days in gestation. The PPA decreased with increasing gravidity and with increasing number of days open. For cows that aborted, the median time to fetal death decreased slightly as gravidity increased. The study considers several methodological issues faced in epidemiologic investigations of fetal health, including multi-modal hazard functions, extensive censoring and non-independence of multiple pregnancies. The model improves our ability to predict bovine abortion and to characterize fetal survival, which have important applications to herd health management.

Abortion, Veterinary↗

PubMed2004

Bayesian modeling of animal- and herd-level prevalences.

We reviewed Bayesian approaches for animal-level and herd-level prevalence estimation based on cross-sectional sampling designs and demonstrated fitting of these models using the WinBUGS software. We considered estimation of infection prevalence based on use of a single diagnostic test applied to a single herd with binomial and hypergeometric sampling. We then considered multiple herds under binomial sampling with the primary goal of estimating the prevalence distribution and the proportion of infected herds. A new model is presented that can be used to estimate the herd-level prevalence in a region, including the posterior probability that all herds are non-infected. Using this model, inferences for the distribution of prevalences, mean prevalence in the region, and predicted prevalence of herds in the region (including the predicted probability of zero prevalence) are also available. In the models presented, both animal- and herd-level prevalences are modeled as mixture distributions to allow for zero infection prevalences. (If mixture models for the prevalences were not used, prevalence estimates might be artificially inflated, especially in herds and regions with low or zero prevalence.) Finally, we considered estimation of animal-level prevalence based on pooled samples.

Animals↗