A regional model of sheep lice management practices for predicting the impact of treatment for lice when no lice are detected
Brian J. Horton A B , Andrew Bailey A and Anna L. Carew AA Tasmanian Institute of Agriculture, University of Tasmania, PO Box 46, Kings Meadows, Tas. 7249, Australia.
B Corresponding author. Email: brian.horton@utas.edu.au
Animal Production Science 56(1) 24-32 https://doi.org/10.1071/AN14474
Submitted: 3 April 2014 Accepted: 8 September 2014 Published: 15 January 2015
Abstract
A model of sheep lice management incorporating different assumed levels of lice prevalence in different regions of Australia was used to determine the conditions under which it would be cost-effective to treat sheep for lice at shearing when no lice had been detected. The probability that a flock might be infested was calculated from the probability that the previous treatment had failed to eradicate lice, purchased sheep may have introduced lice, or lice may have entered on straying sheep. The model showed that a flock should be treated if the probability of infestation is greater than 10%. It was projected that acceptance of a risk level greater than 10% would reduce treatment of flocks where no lice were present, thus reducing treatment costs. This higher risk level, however, would increase the proportion of louse-infested flocks that remained untreated, resulting in increased direct lice costs and an increase in the regional prevalence of lice, but little overall change in costs to the sheep industry. The model indicated that treatment of sheep at lower levels of risk (less than 10%) would incur unnecessary costs due to treatment of flocks where no lice were present and would not reduce the regional prevalence of lice more effectively than a 10% intervention level. The model suggested that more accurate methods of detecting lice at shearing would allow higher levels of risk, reduce the use of treatment and hence reduce overall costs associated with managing lice, without increasing the prevalence of lice.
Additional keywords: intervention, lice detection, lice infested, risk.
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