Abstract

A farm-level stochastic simulation model was modified to estimate the cost per case of 3 foot disorders (digital dermatitis, sole ulcer, and white line disease) by parity group and incidence timing. Disorder expenditures considered within the model included therapeutics, outside labor, and on-farm labor. Disorder losses considered within the model included discarded milk, reduced milk production, extended days open, an increased risk of culling, an increased risk of death (natural or euthanized), and disease recurrence. All estimates of expenditures and losses were defined using data from previously published research in stochastic distributions. Stochastic simulation was used to account for variation within the farm model; 1,000 iterations were run. Sensitivity of foot disorder costs to selected market prices (milk price, feed price, replacement heifer price, and slaughter price) and herd-specific performance variables (pregnancy rate) were analyzed. Using our model assumptions, the cost per disorder case over all combinations of parity group and incidence timing, regardless of incidence likelihood, was lowest for digital dermatitis ($64 ± 24; mean ± standard deviation), followed by white line disease ($152 ± 26) and sole ulcer ($178 ± 29). Disorder costs were greater in multiparous versus primiparous cows and were always highest at the beginning of lactation. The greatest contributing cost categories were decreased milk production, an increased risk of culling, and disease recurrence. The contribution of cost categories to the total cost of disorder varied by disorder type, parity group, and incidence timing. For all disorders, the cost per case increased as milk price or replacement heifer price increased and decreased as feed price, pregnancy rate, or slaughter price increased. Understanding how foot disorder costs change according to cow-specific conditions (i.e., disorder type, parity group, and days in milk at incidence) and herd-specific conditions (i.e., market prices and performance variables) can help improve on-farm decisions about treatment and prevention of foot disorders.

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