Surveillance of porcine reproductive and respiratory syndrome virus in the United States using risk mapping and species distribution modeling

Moh A. Alkhamis, Andreia G. Arruda, Carles Vilalta, Robert B. Morrison, Andres M Perez

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Porcine reproductive and respiratory syndrome virus (PRRSv) outbreaks cause significant financial losses to the U.S. swine industry, where the pathogen is endemic. Seasonal increases in the number of outbreaks are typically observed using PRRSv epidemic curves. However, the nature and extent to which demographic and environmental factors influence the risk for PRRSv outbreaks in the country remains unclear. The objective of this study was to develop risk maps for PRRSv outbreaks across the United States (U.S.) and compare ecological dynamics of the disease in five of the most important swine production regions of the country. This study integrates spatial information regarding PRRSv surveillance with relevant demographic and environmental factors collected between 2009 and 2016. We used presence-only Maximum Entropy (Maxent), a species distribution modeling approach, to model the spatial risk of PRRSv in swine populations. Data fitted the selected model relatively well when the modeling approach was conducted by region (training and testing AUCs < 0.75). All of the Maxent models selected identified high-risk areas, with probabilities greater than 0.5. The relative contribution of pig density to PRRSv risk was highest in pig-densely populated areas (Minnesota, Iowa and North Carolina), whereas climate and land cover were important in areas with relatively low pig densities (Illinois, Indiana, South Dakota, Nebraska, Kansas, Oklahoma, Colorado, and Texas). Although many previous studies associated the risk of PRRSv with high pig density and climatic factors, the study here quantifies, for the first time in the peer-reviewed literature, the spatial variation and relative contribution of these factors across different swine production regions in the U.S. The results will help in the design and implement of early detection, prevention, and control strategies for one of the most devastating diseases affecting the swine industry in the U.S.

Original languageEnglish (US)
Pages (from-to)135-142
Number of pages8
JournalPreventive Veterinary Medicine
Volume150
DOIs
StatePublished - Feb 1 2018

Bibliographical note

Funding Information:
This study was funded by the Swine Health Information Center , National Pork Board , and the University of Minnesota’s MnDrive program .

Publisher Copyright:
© 2017 Elsevier B.V.

Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.

Keywords

  • Climate
  • Maximum entropy
  • PRRSv
  • Pig density
  • Risk mapping
  • Swine production systems

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