A stochastic model simulating milk fever in a dairy herd

Area of Science:

• Veterinary Epidemiology
• Animal Health Modeling
• Dairy Science

Background:

• Milk fever (MF) is a significant metabolic disorder in dairy cows, impacting herd health and productivity.
• Existing simulation models often lack comprehensive integration of MF with other common dairy herd diseases.
• Understanding the long-term effects of MF control strategies requires robust simulation tools.

Purpose of the Study:

• To develop and present the base simulation model, SimHerd III, for evaluating long-term control strategies against milk fever.
• To incorporate within-herd dynamics and interrelationships between MF and other prevalent dairy herd diseases.
• To conduct sensitivity analyses to identify key parameters influencing model outcomes.

Main Methods:

• Developed SimHerd III, an extension of the SimHerd II model, incorporating multiple dairy herd diseases.
• Modeled cow-level risk factors including herd base risk, parity, milk yield, body condition, and disease recurrence.
• Performed sensitivity analyses by varying eight key parameters to assess their impact on milk production.

Main Results:

• Simulated herd effects of reduced MF risk varied based on herd reproductive efficiency, influencing replacement rates.
• The model demonstrated sensitivity to the effects of MF on death risk and MF recurrence.
• Economic impact was most sensitive to uncertainties in MF's effect on mortality and disease recurrence.

Conclusions:

• SimHerd III provides a valuable tool for assessing the long-term impact of milk fever control strategies.
• Herd reproductive efficiency significantly modulates the benefits of reducing MF incidence.
• Accurate estimation of MF's impact on mortality and recurrence is crucial for reliable model predictions.