Modelling the transmission and vaccination strategy for porcine reproductive and respiratory syndrome virus

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

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Many aspects of the porcine reproductive and respiratory syndrome virus (PRRSV) between-farm transmission dynamics have been investigated, but uncertainty remains about the significance of farm type and different transmission routes on PRRSV spread. We developed a stochastic epidemiological model calibrated on weekly PRRSV outbreaks accounting for the population dynamics in different pig production phases, breeding herds, gilt development units, nurseries and finisher farms, of three hog producer companies. Our model accounted for indirect contacts by the close distance between farms (local transmission), between-farm animal movements (pig flow) and reinfection of sow farms (re-break). The fitted model was used to examine the effectiveness of vaccination strategies and complementary interventions such as enhanced PRRSV detection and vaccination delays and forecast the spatial distribution of PRRSV outbreak. The results of our analysis indicated that for sow farms, 59% of the simulated infections were related to local transmission (e.g. airborne, feed deliveries, shared equipment) whereas 36% and 5% were related to animal movements and re-break, respectively. For nursery farms, 80% of infections were related to animal movements and 20% to local transmission; while at finisher farms, it was split between local transmission and animal movements. Assuming that the current vaccines are 1% effective in mitigating between-farm PRRSV transmission, weaned pigs vaccination would reduce the incidence of PRRSV outbreaks by 3%, indeed under any scenario vaccination alone was insufficient for completely controlling PRRSV spread. Our results also showed that intensifying PRRSV detection and/or vaccination pigs at placement increased the effectiveness of all simulated vaccination strategies. Our model reproduced the incidence and PRRSV spatial distribution; therefore, this model could also be used to map current and future farms at-risk. Finally, this model could be a useful tool for veterinarians, allowing them to identify the effect of transmission routes and different vaccination interventions to control PRRSV spread.

Original languageEnglish (US)
JournalTransboundary and Emerging Diseases
Early online dateJan 27 2021
StatePublished - Mar 9 2021

Bibliographical note

Funding Information:
This work was also supported by Food and Agriculture Cyberinformatics and Tools, 2020‐67021‐32462 from the USDA National Institute of Food and Agriculture. Partial support from the Swine Health Information Center under project #19‐211. This project also fostered international collaboration between 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. Authors would like to acknowledge participating systems and veterinarians.

Publisher Copyright:
© 2021 Wiley-VCH GmbH


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

PubMed: MeSH publication types

  • Journal Article


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