Dynamic network connectivity influences the spread of a sub-lineage of porcine reproductive and respiratory syndrome virus

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6 Scopus citations

Abstract

Swine production in the United States is characterized by dynamic farm contacts through animal movements; such movements shape the risk of disease occurrence on farms. Pig movements have been linked to the spread of a virulent porcine reproductive and respiratory syndrome virus (PRRSV), RFLP type 1-7-4, herein denoted as phylogenetic sub-lineage 1A [L1A]. This study aimed to quantify the contribution of pig movements to the risk of L1A occurrence on farms in the United States. Farms were defined as L1A-positive in a given 6-month period if at least one L1A sequence was recovered from the farm. Temporal network autocorrelation modelling was performed using data on animal movements and 1,761 PRRSV ORF5 sequences linked to 494 farms from a dense pig production area in the United States between 2014 and 2017. A farm's current and past exposure to L1A and other PRRSV variants was assessed through its primary and secondary contacts in the animal movement network. Primary and secondary contacts with an L1A-positive farm increased the likelihood of L1A occurrence on a farm by 19% (p =.04) and 23% (p =.03), respectively. While the risk posed by primary contacts with PRRS-positive farms is unsurprising, the observation that secondary contacts also increase the likelihood of infection is novel. Risk of L1A occurrence on a farm also increased by 3.0% (p =.01) for every additional outgoing shipment, possibly due to biosecurity breaches during loading and transporting pigs from the farm. Finally, use of vaccines or field virus inoculation on sow farms one year prior reduced the risk of L1A occurrence in downstream farms by 36% (p =.04), suggesting that control measures that reduce viral circulation and enhance immunological protection in sow farms have a carry-over effect on L1A occurrence in downstream farms. Therefore, coordinated disease management interventions between farms connected via animal movements may be more effective than individual farm-based interventions.

Original languageEnglish (US)
Pages (from-to)524-537
Number of pages14
JournalTransboundary and Emerging Diseases
Volume69
Issue number2
DOIs
StatePublished - Mar 2022

Bibliographical note

Funding Information:
We would like to acknowledge Juan Sanhueza, Carles Vilalta, Mariana Kikuti and Emily Geary for their role in curating these data. We also express our thanks to MSHMP participating pig production companies and practitioners for sharing their data. This study was partially funded by the Swine Health Information Center (SHIC). Funding was also provided by the joint NIFA‐NSF‐NIH Ecology and Evolution of Infectious Disease award 2019‐67015‐29918 and the Agriculture and Food Research Initiative Competitive grant no. 2018‐68008‐27890 from the USDA National Institute of Food and Agriculture.

Funding Information:
We would like to acknowledge Juan Sanhueza, Carles Vilalta, Mariana Kikuti and Emily Geary for their role in curating these data. We also express our thanks to MSHMP participating pig production companies and practitioners for sharing their data. This study was partially funded by the Swine Health Information Center (SHIC). Funding was also provided by the joint NIFA-NSF-NIH Ecology and Evolution of Infectious Disease award 2019-67015-29918 and the Agriculture and Food Research Initiative Competitive grant no. 2018-68008-27890 from the USDA National Institute of Food and Agriculture.

Publisher Copyright:
© 2021 Wiley-VCH GmbH.

Keywords

  • animal movements
  • lineage 1 PRRSV
  • network analysis
  • outbreak risk
  • temporal network autocorrelation
  • time-varying exposure

PubMed: MeSH publication types

  • Journal Article

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