The between-farm transmission dynamics of porcine epidemic diarrhoea virus: A short-term forecast modelling comparison and the effectiveness of control strategies

Jason A. Galvis, Chris M. Jones, Joaquin M. Prada, Cesar A. Corzo, Gustavo Machado

Research output: Contribution to journalArticlepeer-review

Abstract

A limited understanding of the transmission dynamics of swine disease is a significant obstacle to prevent and control disease spread. Therefore, understanding between-farm transmission dynamics is crucial to developing disease forecasting systems to predict outbreaks that would allow the swine industry to tailor control strategies. Our objective was to forecast weekly porcine epidemic diarrhoea virus (PEDV) outbreaks by generating maps to identify current and future PEDV high-risk areas, and simulating the impact of control measures. Three epidemiological transmission models were developed and compared: a novel epidemiological modelling framework was developed specifically to model disease spread in swine populations, PigSpread, and two models built on previously developed ecosystems, SimInf (a stochastic disease spread simulations) and PoPS (Pest or Pathogen Spread). The models were calibrated on true weekly PEDV outbreaks from three spatially related swine production companies. Prediction accuracy across models was compared using the receiver operating characteristic area under the curve (AUC). Model outputs had a general agreement with observed outbreaks throughout the study period. PoPS had an AUC of 0.80, followed by PigSpread with 0.71, and SimInf had the lowest at 0.59. Our analysis estimates that the combined strategies of herd closure, controlled exposure of gilts to live viruses (feedback) and on-farm biosecurity reinforcement reduced the number of outbreaks. On average, 76% to 89% reduction was seen in sow farms, while in gilt development units (GDU) was between 33% to 61% when deployed to sow and GDU farms located in probabilistic high-risk areas. Our multi-model forecasting approach can be used to prioritize surveillance and intervention strategies for PEDV and other diseases potentially leading to more resilient and healthier pig production systems.

Original languageEnglish (US)
JournalTransboundary and Emerging Diseases
Early online dateJan 21 2021
DOIs
StateE-pub ahead of print - Jan 21 2021

Bibliographical note

Funding Information:
The primary funding support of this project is from the Swine Health Information Center under project #19‐211. Partially supported by Food and Agriculture Cyberinformatics and Tools, 2020‐67021‐32462 from the USDA National Institute of Food and Agriculture. Dr. Machado and Dr. Prada laboratory from the travel support provided by the University Global Partnership Network (UGPN) Research Collaboration Fund. The Morrison Swine Health Monitoring Project is a Swine Health Information Center funded project.

Publisher Copyright:
© 2021 Wiley-VCH GmbH

Keywords

  • disease surveillance
  • mechanistic modelling
  • swine disease spread
  • transmission dynamics

PubMed: MeSH publication types

  • Journal Article

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