PRRSV and HEV in UK Pigs at the Time of Slaughter

Viruses. 2017 Jun 9;9(6). pii: E110. doi: 10.3390/v9060110.

UK Pigs at the Time of Slaughter: Investigation into the Correlation of Infection with PRRSV and HEV.

Frossard JP1, Grierson S2, Cheney T3, Steinbach F4, Choudhury B5, Williamson S6.

Author information

1

Animal and Plant Health Agency, Woodham Lane, New Haw, Surrey KT15 3NB, UK. jean-pierre.frossard@apha.gsi.gov.uk.

2

Animal and Plant Health Agency, Woodham Lane, New Haw, Surrey KT15 3NB, UK. Sylvia.Grierson@apha.gsi.gov.uk.

3

Animal and Plant Health Agency, Woodham Lane, New Haw, Surrey KT15 3NB, UK. tcheney87@hotmail.com.

4

Animal and Plant Health Agency, Woodham Lane, New Haw, Surrey KT15 3NB, UK. Falko.Steinbach@apha.gsi.gov.uk.

5

Animal and Plant Health Agency, Woodham Lane, New Haw, Surrey KT15 3NB, UK. Bhudipa.Choudhury@apha.gsi.gov.uk.

6

Surveillance Intelligence Unit, Animal and Plant Health Agency, Rougham Hill, Bury St Edmunds, Suffolk IP33 2RX, UK. Susanna.Williamson@apha.gsi.gov.uk.

Abstract

Hepatitis E virus (HEV) and porcine reproductive and respiratory syndrome virus (PRRSV) and are both globally prevalent in the pig population. While HEV does not cause clinical disease in pigs, its zoonotic potential has raised concerns in the food safety sector. PRRS has become endemic in the United Kingdom (UK) since its introduction in 1991, and continues to cause considerable economic losses to the swine industry. A better understanding of the current prevalence and diversity of PRRSV and HEV in the UK, and their potential association, is needed to assess risks and target control measures appropriately. This study used plasma, tonsil, and cecal content samples previously collected from pigs in 14 abattoirs in England and Northern Ireland to study the prevalence of several pathogens including PRRSV and HEV. The diversity of PRRSV strains detected in these samples was analyzed by sequencing open reading frame 5 (ORF5), revealing no substantial difference in PRRSV strains from these clinically unaffected pigs relative to those from clinical cases of disease in the UK. Despite the potential immuno-modulatory effect of PRRSV infection, previously demonstrated to affect Salmonellaand HEV shedding profiles, no significant association was found between positive PRRSV status and positive HEV status.

KEYWORDS: 

HEV; PRRSV; co-infections; evolution and molecular epidemiology; porcine viruses

PMID:

 

28598352

 

DOI:

 

10.3390/v9060110

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Modeling the spatio-temporal dynamics of PRRS cases at farm level using geographical distance and pig trade network matrices

BMC Vet Res. 2017 Jun 7;13(1):163. doi: 10.1186/s12917-017-1076-6.

Modeling the spatio-temporal dynamics of porcine reproductive & respiratory syndrome cases at farm level using geographical distance and pig trade network matrices.

Amirpour Haredasht S1, Polson D2, Main R3, Lee K1, Holtkamp D3, Martínez-López B4.

Author information

1

Center for Animal Disease Modeling and Surveillance (CADMS), Department of Medicine & Epidemiology, School Veterinary Medicine, University of California, 2108 Tupper Hall, one Shields Avenue, Davis, California, 95616, USA.

2

Boehringer-Ingelheim Vetmedica Inc, Saint Joseph, Missouri, USA.

3

Department of Veterinary Diagnostic and Production Animal Medicine, College of Veterinary Medicine, Iowa State University, Ames, USA.

4

Center for Animal Disease Modeling and Surveillance (CADMS), Department of Medicine & Epidemiology, School Veterinary Medicine, University of California, 2108 Tupper Hall, one Shields Avenue, Davis, California, 95616, USA. beamartinezlopez@ucdavis.edu.

Abstract

BACKGROUND: 

Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically devastating infectious diseases for the swine industry. A better understanding of the disease dynamics and the transmission pathways under diverse epidemiological scenarios is a key for the successful PRRS control and elimination in endemic settings. In this paper we used a two step parameter-driven (PD) Bayesian approach to model the spatio-temporal dynamics of PRRS and predict the PRRS status on farm in subsequent time periods in an endemic setting in the US. For such purpose we used information from a production system with 124 pig sites that reported 237 PRRS cases from 2012 to 2015 and from which the pig trade network and geographical location of farms (i.e., distance was used as a proxy of airborne transmission) was available. We estimated five PD models with different weights namely: (i) geographical distance weight which contains the inverse distance between each pair of farms in kilometers, (ii) pig trade weight (PT ji ) which contains the absolute number of pig movements between each pair of farms, (iii) the product between the distance weight and the standardized relative pig trade weight, (iv) the product between the standardized distance weight and the standardized relative pig trade weight, and (v) the product of the distance weight and the pig trade weight.

RESULTS: 

The model that included the pig trade weight matrix provided the best fit to model the dynamics of PRRS cases on a 6-month basis from 2012 to 2015 and was able to predict PRRS outbreaks in the subsequent time period with an area under the ROC curve (AUC) of 0.88 and the accuracy of 85% (105/124).

CONCLUSION: 

The result of this study reinforces the importance of pig trade in PRRS transmission in the US. Methods and results of this study may be easily adapted to any production system to characterize the PRRS dynamics under diverse epidemic settings to more timely support decision-making.

KEYWORDS: 

Bayesian approach; Decision making; Disease dynamics; Parameter-driven model; Risk assessment; Risk-based surveillance

PMID:

 

28592317

 

DOI:

 

10.1186/s12917-017-1076-6