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Monitoring breeding herd production data to detect PRRSV outbreaks.

G S Silva1, M Schwartz2, R B Morrison3

  • 1Veterinary Diagnostic and Production Animal Medicine Department, Iowa State University, Ames, IA, United States; Veterinary Epidemiology Laboratory, Federal University of Rio Grande do Sul, Porto Alegre, Brazil.

Preventive Veterinary Medicine
|November 22, 2017
PubMed
Summary

Monitoring farm productivity using EWMA statistical methods can help detect Porcine Reproductive and Respiratory Syndrome virus (PRRSv) outbreaks early. This approach aids in quantifying economic losses and improving swine herd health surveillance.

Keywords:
Disease detectionEWMAMonitoringPRRSvProduction dataProductivitySPC

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Area of Science:

  • Veterinary epidemiology
  • Animal health economics
  • Statistical process control in agriculture

Background:

  • Porcine Reproductive and Respiratory Syndrome virus (PRRSv) significantly impacts swine production economics through productivity losses.
  • Quantifying PRRSv impact requires measuring productivity changes before and after infection.
  • Existing surveillance programs can be enhanced by integrating systematic productivity monitoring.

Purpose of the Study:

  • To assess the utility of Exponentially Weighted Moving Average (EWMA) for detecting PRRSv-associated productivity deviations.
  • To supplement PRRS surveillance by identifying significant changes in key production indicators.
  • To evaluate the timeliness and accuracy of EWMA-based monitoring against a reference diagnostic program.

Main Methods:

  • Applied EWMA, a statistical process control method, to weekly production data (abortions, pre-weaning mortality, prenatal losses).
  • Utilized data from 55,000 sows across 14 breed-to-wean herds in Minnesota, U.S.A.
  • Compared EWMA detection of productivity deviations with PRRS status data from the Morrison's Swine Health Monitoring Project (MSHMP).

Main Results:

  • EWMA detected productivity deviations associated with PRRS outbreaks between -4 to -1 weeks for abortions, 0-0 weeks for pre-weaning mortality, and -1 to 3 weeks for prenatal losses relative to MSHMP reporting.
  • The monitoring system demonstrated high relative sensitivity (85.7-100%) and specificity (98.5%-99.6%) compared to MSHMP PRRS status changes.
  • On-farm monitoring showed high concordance with MSHMP-reported outbreaks, suggesting efficient detection by staff, particularly with close abortion monitoring.

Conclusions:

  • Systematic monitoring of production indicators using EWMA can standardize and semi-automate the detection of PRRSv-related productivity deviations.
  • EWMA offers a valuable tool for early PRRS outbreak detection and quantifying associated production losses.
  • Enhanced focus on monitoring abortion frequency can further improve the efficiency of PRRSv detection in swine herds.