Predicting Disease Risk in Feeder Cattle

Today, emerging chute-side technologies for detecting the earliest signs of respiratory disease have potential to help move the industry toward a goal of more individualized management. ( John Maday )

While predicting disease risk in a group of cattle is relatively reliable for experienced cattle feeders, predicting risk in individual animals presents a much greater challenge. Veterinarians and industry partners continue to develop ways to predict risk or detect early signs of disease in individual cattle for more targeted treatments.

Today, emerging chute-side technologies for detecting the earliest signs of respiratory disease have potential to help move the industry toward a goal of more individualized management.

At the recent Academy of Veterinary Consultants conference, West Texas A&M Animal Scientist John Richeson, PhD, discussed how new chute-side diagnostic tools can help cattle feeders assess morbidity risk for individual cattle upon arrival, potentially reducing antibiotic use in mass treatments while improving health outcomes. Advanced Animal Diagnostics (AAD) hosted the breakfast presentation.

Richeson reviewed several methods in use, or under testing, for predicting disease risk upon arrival and guiding treatment decisions. “Chute-side” is a key term in the assessment, as rapid diagnostics and treatment decisions at the time and speed of initial processing offer advantages in terms of labor, logistics, treatment efficacy and animal welfare.

In his review, Richeson traditional and emerging technologies for chute-side health assessments.

Rectal temperatures can reveal cases of morbidity, but in research trials have not provided a reliable early prediction of disease risk.

Auscultation can detect early signs of respiratory disease, but accuracy depends largely on the person operating the stethoscope. The electronic Whisper auscultation system removes much of the subjectivity. Richeson says that while the system can detect early signs of BRD and objectively rate severity of the infection, lung sounds probably are not the earliest signs of BRD risk for predictive applications.

Tests for serum haptoglobin levels provide a non-specific indicator of inflammatory status, but levels need to be measured at a very specific times for reliability as a disease-prediction tool.

Concentration of NEFAs (Non-esterified fatty acids) can serve as an indicator of lipolysis or a negative energy balance. More research is needed to determine if or how NEFA levels predicts BRD risk.

Analysis of nasal microbiome signatures shows promise as a predictive tool, Richeson says, but more research is needed and current tests require lab work, so it is not a “chute-side” tool.

Measurement of blood Leukocyte differential (BLD) can provide indications of stress, dehydration and immune challenge, Richeson says. AAD’s Qscout BLD test measures total leukocyte, neutrophil, mononuclear and eosinophil counts and the percentages of neutrophil, mononuclear and eosinophil in the total blood leukocyte count. The test uses an algorithm to analyze BLD parameters in about 35 seconds. Controlled field trials indicate the test can facilitate targeted treatment on arrival, reducing costs and antibiotic use compared with metaphylaxis without significant differences in morbidity, treatment rates or cattle performance.

Research and field testing needs to continue, Richeson says, but chute-side diagnostic testing shows considerable promise for improving health while reducing costs and antibiotic use with more targeted treatment.

AVC members can access the full recorded proceedings from every AVC conference, and qualify for continuing education credits. The proceedings are available on the AVC website or on mobile devices using an app developed by Kansas State University’s Beef Cattle Institute. The app is available from the Apple App Store or Google Play. Search “BCI Conference.”

The AVC’s winter 2018 conference takes place Nov 29 to Dec 1, at the Intercontinental Hotel, Kansas City, Mo.