Prevalence estimation of Pestivirus scrofae (atypical porcine pestivirus) among Hungarian pig herds and the effects of different sample types on detection rates.

Abstract

Background: Atypical porcine pestivirus (APPeV), also known as Pestivirus scrofae, is a member of the Pestivirus genus within the Flaviviridae family. Experimental infections have directly linked APPeV to congenital tremor (CT) type A-II in congenitally infected piglets born to challenged sows. Here, we report the assessment of the prevalence of APPeV in Hungarian pig herds and the influence of different sample types on detection rates.

Results: Altogether, 2650 blood serum, 198 oral fluid and 163 processing fluid samples were obtained via a systemic approach from 26 Hungarian farms and one Slovakian farm. The samples originated from different age groups and were analyzed via reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The estimated prevalence of APPeV was determined to be 66.67% in the sampled farms, indicating the widespread distribution of the virus within Hungary. Within the positive farms, APPeV genetic material was detected in the serum (21%), processing fluid (57%), and oral fluid (72%) samples. Notably, in some farms, the presence of APPeV was confirmed in only specific sample types, and five farms had APPeV in all three sample types. Age group analysis revealed that 10-week-old animals had the highest positivity rate in their blood serum (27%), whereas 20-week-old animals presented the highest rate in their oral fluid samples (59%). Processing fluid and oral fluid samples proved to be valuable for noninvasive diagnostic matrices, allowing for efficient population-level virus detection. We determined the partial NS2-3 coding region of 15 Hungarian strains and a Slovakian strain, and our phylogenetic analysis revealed that very similar strains can be found on different farms.

Conclusion: In conclusion, our study provides insights into APPeV prevalence in Hungarian pig herds, emphasizing the importance of different sample types for accurate diagnostics. These findings contribute to our understanding of the virus's distribution across different age groups.