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Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

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Protocol for Assessing the Relative Effects of Environment and Genetics on Antler and Body Growth for a Long-lived Cervid
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Using scenario tree modelling for targeted herd sampling to substantiate freedom from disease.

Sarah Blickenstorfer1, Heinzpeter Schwermer, Monika Engels

  • 1Veterinary Public Health Institute, Vetsuisse Faculty, University of Berne, Switzerland.

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|August 17, 2011
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A new targeted sampling strategy for animal disease surveillance significantly reduces farm sample sizes for infectious bovine rhinotracheitis (IBR) and enzootic bovine leucosis (EBL), improving cost-effectiveness.

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Area of Science:

  • Veterinary Epidemiology
  • Animal Health Surveillance
  • Quantitative Risk Assessment

Background:

  • Optimizing cost-effectiveness in active surveillance for disease freedom is crucial.
  • Infectious bovine rhinotracheitis (IBR) and enzootic bovine leucosis (EBL) are significant concerns in Swiss cattle farming.
  • Existing surveillance methods may not be optimally efficient.

Purpose of the Study:

  • To develop and evaluate a novel targeted sampling (TS) approach for disease surveillance.
  • To compare the efficiency of TS with traditional stratified random sampling (sRS).
  • To determine the required sample sizes for substantiating disease freedom for IBR and EBL.

Main Methods:

  • Identified relevant risk factors (RF) for IBR and EBL introduction based on literature and expert opinion.
  • Utilized a quantitative model employing the scenario tree method to calculate sample sizes for TS.
  • Calculated sample sizes for both TS and sRS for comparison.

Main Results:

  • TS required 1,241 farms for IBR and 1,750 for EBL to detect 0.2% herd prevalence with 99% sensitivity.
  • sRS required 2,259 farms for IBR and 2,243 for EBL.
  • TS demonstrated greater cost-effectiveness, reducing survey costs by 40% for IBR and 8% for EBL despite administrative overhead.

Conclusions:

  • The risk-based TS approach offers a promising tool for veterinary authorities to design cost-effective sampling strategies.
  • While expert-based parameterization introduces some uncertainty, the method significantly reduces sample size requirements.
  • This approach enhances the efficiency of active surveillance programs for animal diseases.