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Application of Epidemiological Methods in a Large-Scale Cross-Sectional Study in 765 German Dairy Herds-Lessons Learned.

Roswitha MerleMartina HoedemakerGabriela Knubben-SchweizerMoritz MetznerKerstin-Elisabeth MüllerAmely Campe
Published in: Animals : an open access journal from MDPI (2024)
From 2016 to 2020, the "PraeRi" study, conducted by three German veterinary universities, was aimed at enhancing animal health and welfare in dairy farms. With 765 dairy farms visited and 101,307 animals examined, this study provided a basis for improving animal health and welfare. The study population comprised three different regions representing a broad variety of characteristics. To ensure representative estimates, a sample size of 250 farms was determined for each region, employing a stratified sampling plan based on farm size. According to the information provided by the farmers, the most commonly occurring disease in their herds was mastitis without general disorder (14.2% to 16.3% of the herd-depending on the region). For most disorders, prevalence data were lowest for the region South compared with the two remaining regions. Multivariable regression analyses were performed to identify risk factors for various target variables, and the results were communicated through individual reports and benchmarking flyers to participating farmers. The authors encountered challenges in management and communication due to the project's size in terms of personnel, data, and farms examined. Harmonizing data management and hypothesis testing across all involved parties added complexity.
Keyphrases
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  • deep learning