Machine-learning algorithms to identify key biosecurity practices and factors associated with breeding herds reporting PRRS outbreak

Author links open overlay panelGustavo S.Silvaa1GustavoMachadob1Kimberlee L.BakeraDerald J.HoltkampaDaniel C.L.Linharesa

a

Veterinary Diagnostic and Production Animal Medicine Department, College of Veterinary Medicine, Iowa State University, Ames, Iowa, United States

b

Department of Population Health and Pathobiology, North Carolina State University, College of Veterinary Medicine, Raleigh, North Carolina, United States

Received 5 April 2019, Revised 12 August 2019, Accepted 19 August 2019, Available online 20 August 2019.

https://doi.org/10.1016/j.prevetmed.2019.104749Get rights and content

Abstract

Investments in biosecurity practices are made by producers to reduce the likelihood of introducing pathogens such as porcine reproductive and respiratory syndrome virus (PRRSv). The assessment of biosecurity practices in breeding herds is usually done through surveys. The objective of this study was to evaluate the use of machine-learning (ML) algorithms to identify key biosecurity practices and factors associated with breeding herds self-reporting (yes or no) a PRRS outbreak in the past 5 years. In addition, we explored the use of the positive predictive value (PPV) of these models as an indicator of risk for PRRSv introduction by comparing PPV and the frequency of PRRS outbreaks reported by the herds in the last 5 years. Data from a case control study that assessed biosecurity practices and factors using a survey in 84 breeding herds in U.S. from 14 production systems were used. Two methods were developed, method A identified 20 variables and accurately classified farms that had reported a PRRS outbreak in the previous 5 years 76% of the time. Method B identified six variables which 5 of these had already been selected by model A, although model B outperformed the former model with an accuracy of 80%. Selected variables were related to the frequency of risk events in the farm, swine density around the farm, farm characteristics, and operational connections to other farms. The PPVs for methods A and B were highly correlated to the frequency of PRRSv outbreaks reported by the farms in the last 5 years (Pearson r = 0.71 and 0.77, respectively). Our proposed methodology has the potential to facilitate producer’s and veterinarian’s decisions while enhancing biosecurity, benchmarking key biosecurity practices and factors, identifying sites at relatively higher risk of PRRSv introduction to better manage the risk of pathogen introduction.

Keywords

biosecurity practices and factors

PRRSv outbreaks

risk index

machine learning

decision-making

Processing fluids for longitudinal monitoring of PRRSV in herds undergoing virus elimination

Porcine Health Manag. 2019 Aug 1;5:18. doi: 10.1186/s40813-019-0125-x. eCollection 2019.

Use of processing fluid samples for longitudinal monitoring of PRRS virus in herds undergoing virus elimination.

Trevisan G1, Jablonski E2, Angulo J2, Lopez WA1, Linhares DCL1.

Author information

1

1Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, Iowa USA.

2

2Zoetis, Parsippany, New Jersey USA.

Abstract

This was an observational study that prospectively followed 29 breeding herds for 65 weeks in the U.S.A. that became infected with porcine reproductive and respiratory syndrome virus (PRRSv). The herds operated in a four-week batch farrowing system and adopted a load-close-expose strategy using a modified-live virus vaccine to achieve PRRSv stability. The purpose of this study was to describe time to stability (TTS) based on RT-qPCR testing for PRRSv RNA on processing fluid samples in herds undergoing PRRSv elimination, after implementing herd closure and mass exposure to a PRRS modified-live virus (MLV) vaccine. For the purpose of this study, stability was defined as consistently producing PRRSv-negative pigs. Study herds were monitored until two consecutive piglet batches tested PRRSv RT-qPCR negative, then 30 due-to-wean piglet sera from the second batch were tested for PRRSv RNA by RT-qPCR. Once the farm re-opened, sera from incoming naïve gilts were tested for anti-PRRSv antibodies by ELISA at 30- and 60-days post-entry to confirm negative status to PRRSv. Day zero was the day of whole-herd exposure to a commercial PRRS vaccine virus. Twenty-eight of 29 herds (96.55%) achieved TTS within the study period. TTS ranged from 18 to 55 weeks with a median of 27 weeks. Serum from due-to-wean piglets was collected on 28 farms, of which 26 (92.85%) obtained PRRSv RT-qPCR-negative results on the first collection. At the end of the observational period, 16 sow farms successfully re-introduced PRRSv-naïve gilts with no detected serologic response. In conclusion, the median time to achieve TTS in breeding herds being operated in a four-week batch farrowing system undergoing PRRSv elimination using load-close-expose with attenuated virus vaccine was 27 weeks. Also, processing fluid-based monitoring of breeding herds under PRRS elimination was practical and reliable to assess PRRSv stability.

KEYWORDS: 

Herd closure; Porcine reproductive and respiratory syndrome virus; Processing fluid; Time to stability

PMID:

 

31388438

 

PMCID:

 

PMC6670174

 

DOI:

 

10.1186/s40813-019-0125-x

Free PMC Article

Aerosol Detection and Transmission of PRRSV: What Is the Evidence, and What Are the Knowledge Gaps?

Viruses. 2019 Aug 3;11(8). pii: E712. doi: 10.3390/v11080712.

Aerosol Detection and Transmission of Porcine Reproductive and Respiratory Syndrome Virus (PRRSV): What Is the Evidence, and What Are the Knowledge Gaps?

Arruda AG1, Tousignant S2, Sanhueza J3, Vilalta C3, Poljak Z4, Torremorell M3, Alonso C5, Corzo CA3.

Author information

Abstract

In human and veterinary medicine, there have been multiple reports of pathogens being airborne under experimental and field conditions, highlighting the importance of this transmission route. These studies shed light on different aspects related to airborne transmission such as the capability of pathogens becoming airborne, the ability of pathogens to remain infectious while airborne, the role played by environmental conditions in pathogen dissemination, and pathogen strain as an interfering factor in airborne transmission. Data showing that airborne pathogens originating from an infectious individual or population can infect susceptible hosts are scarce, especially under field conditions. Furthermore, even though disease outbreak investigations have generated important information identifying potential ports of entry of pathogens into populations, these investigations do not necessarily yield clear answers on mechanisms by which pathogens have been introduced into populations. In swine, the aerosol transmission route gained popularity during the late 1990's as suspicions of airborne transmission of porcine reproductive and respiratory syndrome virus (PRRSV) were growing. Several studies were conducted within the last 15 years contributing to the understanding of this transmission route; however, questions still remain. This paper reviews the current knowledge and identifies knowledge gaps related to PRRSV airborne transmission.

KEYWORDS: 

aerosol; airborne; porcine reproductive and respiratory syndrome; porcine reproductive and respiratory syndrome virus (PRRSV); transmission

PMID:

 

31382628

 

DOI:

 

10.3390/v11080712