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

Abstract

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.

Modelling and assessing additional transmission routes for porcine reproductive and respiratory syndrome virus: vehicle movements and feed ingredients

“…In this study, we used weekly PRRSV records captured by the Morrison Swine Health Monitoring Program (MSHMP) (MSHMP, 2020). Data included outbreaks between January 22, 2009 and December 31, 2020, from 2,294 farms from three non-commercially related pig production companies (coded as A, B, and C) in a U.S. region (region not disclosed by confidentiality terms) (Galvis et al, 2021). Individually, each PRRSV record was classified as new or recurrent according to the time between consecutive outbreaks per farm (Galvis et al, 2021).…”

“…Data included outbreaks between January 22, 2009 and December 31, 2020, from 2,294 farms from three non-commercially related pig production companies (coded as A, B, and C) in a U.S. region (region not disclosed by confidentiality terms) (Galvis et al, 2021). Individually, each PRRSV record was classified as new or recurrent according to the time between consecutive outbreaks per farm (Galvis et al, 2021). A list of pig farms was available from the MSHMP database (MSHMP, 2020), which included individual national premises identification number, farm type (sow [which included farrow, farrow-to-wean, and farrow-to-feeder farms]), nursery, finisher [which included wean-to-feeder, wean-to-finish, feeder-to-finish], gilt development unit [which could be either part in finisher or sow farms depending upon production type used by pig production company], isolation and boar stud, pig spaces per farm, and geographic coordinates.…”

“…In order to perform the analysis of spatiotemporal distribution of farm-level PRRSV outbreaks, we extended a previously developed between-farm transmission model (Galvis et al, 2021), including additional transmission routes. The model was calibrated to the weekly PRRSV outbreaks and accounted for eight transmission modes including (1) contact network of discrete pig movements, (2) the local transmission events between neighboring farms driven by distances among farms, indirect contact by vehicles coming into farms, including for (3) feed delivery, animal delivery to (4) farms and (5) market, and (6) vehicles used by loading and unloading pigs personnel (crew), (7) amount of animal by-products in feed formulation delivery to farms, and (8) re-break by a previous exposure to the PRRSV (Figure 2).…”

“…lower transmission at longer distances), with maximum distance set at 35km, based on previous study (Galvis et al, 2021). Local transmission is also dependent on the enhanced vegetation index (EVI) around the farm i (Jara et al, 2020; Galvis et al, 2021), such that the probability of transmission decreases with high EVI values (Supplementary material Figure S4). The transmission between farm pig movements is modeled by the number of all infected and outbreak farms sending pigs to susceptible farms.…”

“…Porcine reproductive and respiratory syndrome virus (PRRSV) remains a major economic burden in North America (Holtkamp et al, 2013), which continue to spread across multiple pig-producing companies (Sanhueza et al, 2019; Jara et al, 2020; Galvis et al, 2021). A recent study developed a new mathematical model to reconstruct the between-farm PRRSV dynamics, revealed the role of between-farm pig movements, indirect contacts by farm-to-farm proximity, and the continued circulation of PRRSV within infected sites (re-break) (Galvis et al, 2021). Despite the promising results, the study did not fully consider indirect contacts formed by the between-farm transportation vehicles networks, which has been previously described as one the major modes of the between-farm transmission of disease in swine (Büttner and Krieter, 2020; Porphyre et al, 2020; Niederwerder, 2021), and also in other systems such as cattle (Yang et al, 2020).…”