Proposed dairy calf birth certificate data and death loss categorization scheme

Abstract

The majority of dairy heifer calves in the United States are destined to be dairy replacements. However, many dairy heifer and bull calves die before 6 mo of age. Of these calves, about 6% (more than 500,000 calves) die at birth or shortly after (i.e., currently termed "stillbirth"). An additional 6% of dairy heifers die during the preweaning period. Death loss in dairy calves is primarily due to stillbirths, failure to adapt to extrauterine life, and infectious disease processes. The reasons for preweaning heifer calf deaths caused by infectious diseases are generally categorized based on easily recognizable clinical signs such as digestive disease/scours or respiratory disease. Most causes of calf death can be mitigated by appropriate preventive care or well-tailored treatments, meaning that the typical death loss percentage could be decreased with better management. Producers could gather information on the circumstances near birth and at death if they had appropriate guidance on what details to record and monitor. This paper provides recommendations on data to collect at the time of birth (i.e., calf birth certificate data). The recording of these critical pieces of information is valuable in evaluating trends over time in morbidity and mortality events in dairy calves. Ideally, necropsy examination would substantially improve the identification of cause of death, but even without necropsy, attribution of cause of death can be improved by more carefully defining death loss categories in on-farm record systems. We propose a death loss categorization scheme that more clearly delineates causes of death. Recommendations are provided for additional data to be collected at the time of death. Recording and analyzing birth certificate and death loss data will allow producers and veterinarians to better evaluate associations between calf risk factors and death, with the goal of reducing dairy calf mortality.

Clarifying dairy calf mortality phenotypes through postmortem analysis

“…Based on postmortem evaluation, each of the other categories for Figure 1. Calf death loss flowchart adapted from a dairy calf death categorization scheme (Lombard et al, 2019). dairy calf deaths contained ≤4% of cases, both with (≤5) and without (≤8) input from WADDL, aside from the 9% of cases assigned to postnatal death both with (11) and without (19) input from WADDL.…”

“…This study adapted a calf death loss flowchart and dairy calf death categorization scheme (Lombard et al, 2019) to compare 3 levels of diagnostic information: on-farm treatment-based records alone, necropsy-based postmortem findings in addition to treatment records, and WADDL diagnostic results in addition to all other information. This categorization scheme is particularly useful in that it discriminates between uncomplicated diarrhea and other specific digestive ailments such as GI ulceration and peritonitis, and acknowledges the fact that many calf deaths present with ante-and postmortem evidence suggestive of both GI and lung pathology.…”

“…The WADDL-based diagnoses were determined on a case-by-case basis by the pathologist of record following completion of ancillary diagnostics including histopathology. Resultant mortality phenotypes were then categorized broadly by the principal investigator for each of the 3 levels of information according to a modified categorization scheme for dairy calf causes of death using a calf death loss flowchart ( Figure 1; Lombard et al, 2019). Although no information was available from the time of parturition, a category for calving problems was included to appropriately document trauma such as fractured ribs or pathology due to apparent hypoxic changes such as centrilobular hepatic necrosis within calves ≤48 h of age.…”

Improving resistance of cattle to BRD through genomics

“…Termination codes to include reasons for termination in heifers have been proposed as shown in Table 1. Dairy calf death losses were estimated at $327.3 billion in 2015 (Lombard et al ., 2019). Common health events that are encountered in heifers could be incorporated to increase available data for events such as BRD.…”

“…One system was recently proposed by Lombard et al . (2019). Collection of these data could aid in providing benchmarks for the dairy industry, and potentially be included with data of specific health events for genetic evaluations.…”