Comprehensive identification of on-farm animal-health issues still requires extensive efforts so that in practice such monitoring is applied only sparsely. An appealing approach to improve on-farm animal health and welfare monitoring is the application of organ lesion scoring data from the abattoir as such is instantly available for every commercial farm in Europe. Unfortunately, it is also well-known that organ lesion scoring is often unreliable because results are altered by several non-health-related factors, diluting the validity of lesion scoring prevalence as a proxy for on-farm animal health. However, it is theoretically possible to improve prevalence reliability a-posteriori by application of time-series smoothing. The aim of this paper was therefore to analyse whether it is practically possible to increase apparent prevalence estimation reliability retrospectively using a running average, and, if so, which window length and smallest sample size should be preferred in such an approach. Because no gold standard for direct evaluation of lesion reliability is available for field-data, apparent prevalence reliability had to be approximated using prevalence agreement over time. Results indicate that by raising the number of lesion scores per prevalence estimate, apparent prevalence agreement over time can in general be considerably increased. Based on findings presented, a reasonable threshold for prevalence estimation is given by at least n = 50 lesions per farm/abattoir/time-series segment. Results further suggest that it is necessary to consider differences in prevalence sample size for future monitoring purposes, because prevalences that are estimated on a continuum of different sample sizes put together in one evaluation may induce substantial error in prevalence estimates.
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http://dx.doi.org/10.1016/j.prevetmed.2021.105258 | DOI Listing |
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