Reproductive performance monitored with statistical process control over 2 years in a farm, which faced an acute PRRS outbreak and implemented PRRS vaccination

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Dražen Hižman1, Rebecca Morgenstern2, Vladan Miljković3

1Belje Agro-Vet plus, Croatia; 2Boehringer Ingelheim RCV GmbH & Co. KG, Austria; 3Boehringer Ingelheim Serbia d.o.o., Serbia.

 

Introduction

Infection with porcine reproductive and respiratory syndrome virus (PRRSV) may lead to significant losses in productivity of breeding and growing pig herds.1,2

Performance data was monitored over two years in a commercial farm in Croatia, which faced an acute PRRS outbreak and subsequently implemented vaccination against PRRSV. The present abstract presents the results of sow performance. Nursery mortality is presented in a second abstract.

Materials and Methods

The study was conducted on a one site, farrow-to-finish farm with 2000 sows in Croatia. The farm is PRRSV positive since 2014, however, the first introduction never caused noticeable changes in performance and production was stable. A new, acute and severe PRRS outbreak occurred in late 2018, which negatively influenced reproduction (from week 44/2018) and shortly after the growing pig performance (from week 48/2018). No PRRS vaccination was implemented prior to this new outbreak. A PRRS control program started early 2019.

The herd was loaded with gilts and closed for six month.

Management changes implemented to reduce PRRSV transmission included limited cross-fostering, no use of foster sows (until Sept. 2019), change of needles and disinfection of surgical blades between litters. From week 8/2019 the breeding herd, including all gilts, was vaccinated twice four weeks apart with ReproCyc PRRS® EU , followed by routine mass vaccination every three month. Vaccination against PRRSV was also implemented for piglets. Four key performance parameters were analyzed via statistical process control (SPC) starting from week 20/2018 until week 20/2020. Weekly data was compared between three different periods, respecting the phases before (period 1), during the acute PRRS outbreak (period 2) and after the implementation of PRRS vaccination (period 3). One other major event was reported for the observational period. From week 25/2019 a remarkable drop in the pregnancy rate was noted that continued over several weeks (event 1). A full diagnostic work-up revealed spermicide substances in the tubes used for semen storage. The problem was solved by the exchange of the respective materials. Consequences of event 1 were noticeable in several other parameters following through the production line. No other changes of vaccinations in sows or major changes in feeding or housing were implemented during the observational period. A transition period, during which results could not be assigned to one or the other treatment, as well as results influenced by event 1 were excluded.

Results and Discussion

Table 1 presents the detailed results of the reproductive parameters.

Table 1: Mean and standard deviation of 4 reproductive parameters during 3 comparison periods. Different superscripts within the rows indicate significant differences (p<0.05).

Table 1 Image

Reproductive performance was stabilized after implementation of the PRRS control program following the acute PRRS outbreak. Results in period 3 (3.1 and 3.2 combined) were close to pre-outbreak values and variation (i.e. standard deviation) could be stabilized at pre-outbreak levels (p=0.601) leading to more predictable production (table 1; figure 1).

Figure 1: Farrowing rate (%) in the different periods presented in an I-MR chart. The mean is calculated for each period (x̄ ; 3.1 and 3.2 combined) and indicated by the green line. Red lines indicate the upper and lower control limits. Data during transition period and event 1 are blended out.

Figure 1 Image

Conclusions

Vaccination and biosecurity measures are valid tools to stabilize production after an acute PRRS outbreak. Statistical process control offers a straightforward way to analyze large continuous data sets, as in the present case, taking into consideration mean and variation of the data associated with process changes.

References

  1. Zimmerman et al. 2019: Diseases of Swine, 11th edition: 685-708.
  2. Nathues et al. 2017: Preventive Veterinary Medicine 142: 16-29.