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

Animals (Basel)

Department of Biometry, Epidemiology and Information Processing (IBEI), WHO Collaborating Centre for Research and Training for Health at the Human-Animal-Environment Interface, University of Veterinary Medicine Hannover, Foundation, Buenteweg 2, 30559 Hannover, Germany.

Published: May 2024

AI Article Synopsis

  • The "PraeRi" study (2016-2020) involved three German veterinary universities and focused on improving animal health and welfare in 765 dairy farms, examining over 101,000 animals.
  • A stratified sampling plan targeting 250 farms per region was used to gather data, revealing mastitis as the most common disease, affecting 14.2% to 16.3% of herds based on geographic location.
  • The study faced challenges in managing its extensive scope, including personnel and data communication, complicating data management and hypothesis testing among participating parties.

Article Abstract

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11083683PMC
http://dx.doi.org/10.3390/ani14091385DOI Listing

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