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Semi-quantitative risk assessment of African swine fever virus introduction in pig farms
A semi-quantitative risk assessment was developed to classify pig farms in terms of the probability of introduction of African swine fever virus (ASFV). Following on-farm data collection via a specific checklist, we applied a modified failure mode and effect analysis (FMEA) to calculate the risk pri...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9911915/ https://www.ncbi.nlm.nih.gov/pubmed/36777667 http://dx.doi.org/10.3389/fvets.2023.1017001 |
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author | Scollo, Annalisa Valentini, Francesco Franceschini, Giorgio Rusinà, Alessia Calò, Stefania Cappa, Veronica Bellato, Alessandro Mannelli, Alessandro Alborali, Giovanni Loris Bellini, Silvia |
author_facet | Scollo, Annalisa Valentini, Francesco Franceschini, Giorgio Rusinà, Alessia Calò, Stefania Cappa, Veronica Bellato, Alessandro Mannelli, Alessandro Alborali, Giovanni Loris Bellini, Silvia |
author_sort | Scollo, Annalisa |
collection | PubMed |
description | A semi-quantitative risk assessment was developed to classify pig farms in terms of the probability of introduction of African swine fever virus (ASFV). Following on-farm data collection via a specific checklist, we applied a modified failure mode and effect analysis (FMEA) to calculate the risk priority codes (RPC's), indicating increasing risk levels ranging from 1 to 5. The importance of biosecurity measures was attributed by experts. To consider geographic risk factors, we classified pig farms based on local density of farmed pigs, and on the estimated wild boar population density. The combination of RPC's with geographical risk factors resulted into a final ranking of pig farms in terms of the risk of ASFV introduction. Furthermore, the estimation of frequency and levels of non-compliance with biosecurity measures was used to identify weak points in risk prevention at farm level. The outcome of the risk assessment was affected by choices in assigning non-compliance scores and importance to specific components of biosecurity. The method was applied in 60 commercial farms in major pig production areas in Italy. Furthermore, we applied a reduced version of our checklist in 12 non-commercial/small commercial (≤20 pigs) farms in the northern Apennines. In commercial farms, highest RPC's were obtained for biosecurity measures associated with personnel practices and farm buildings/planimetry. Intervention should be addressed to training of personnel on biosecurity and ASF, to avoid contacts with other pig herds, and to improve practices in the entrance into the farm. Sharing trucks with other farms, and loading/unloading of pigs were other weak points. Fencing was classified as insufficient in 70% of the commercial farms. Among these farms, breeding units were characterised by the lowest risk of ASFV introduction (although differences among median ranks were not statistically significant: P-value = 0.07; Kruskal–Wallis test), and increasing herd size was not significantly correlated with a higher risk (Kendall's τ = −0.13; P-value = 0.14). Density of farmed pig was greatest in the main pig production area in northern Italy. Conversely, exposure to wild boars was greatest for non-commercial/small commercial farms on the Apennines, which were also characterised by non-compliance with critical biosecurity measures. |
format | Online Article Text |
id | pubmed-9911915 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99119152023-02-11 Semi-quantitative risk assessment of African swine fever virus introduction in pig farms Scollo, Annalisa Valentini, Francesco Franceschini, Giorgio Rusinà, Alessia Calò, Stefania Cappa, Veronica Bellato, Alessandro Mannelli, Alessandro Alborali, Giovanni Loris Bellini, Silvia Front Vet Sci Veterinary Science A semi-quantitative risk assessment was developed to classify pig farms in terms of the probability of introduction of African swine fever virus (ASFV). Following on-farm data collection via a specific checklist, we applied a modified failure mode and effect analysis (FMEA) to calculate the risk priority codes (RPC's), indicating increasing risk levels ranging from 1 to 5. The importance of biosecurity measures was attributed by experts. To consider geographic risk factors, we classified pig farms based on local density of farmed pigs, and on the estimated wild boar population density. The combination of RPC's with geographical risk factors resulted into a final ranking of pig farms in terms of the risk of ASFV introduction. Furthermore, the estimation of frequency and levels of non-compliance with biosecurity measures was used to identify weak points in risk prevention at farm level. The outcome of the risk assessment was affected by choices in assigning non-compliance scores and importance to specific components of biosecurity. The method was applied in 60 commercial farms in major pig production areas in Italy. Furthermore, we applied a reduced version of our checklist in 12 non-commercial/small commercial (≤20 pigs) farms in the northern Apennines. In commercial farms, highest RPC's were obtained for biosecurity measures associated with personnel practices and farm buildings/planimetry. Intervention should be addressed to training of personnel on biosecurity and ASF, to avoid contacts with other pig herds, and to improve practices in the entrance into the farm. Sharing trucks with other farms, and loading/unloading of pigs were other weak points. Fencing was classified as insufficient in 70% of the commercial farms. Among these farms, breeding units were characterised by the lowest risk of ASFV introduction (although differences among median ranks were not statistically significant: P-value = 0.07; Kruskal–Wallis test), and increasing herd size was not significantly correlated with a higher risk (Kendall's τ = −0.13; P-value = 0.14). Density of farmed pig was greatest in the main pig production area in northern Italy. Conversely, exposure to wild boars was greatest for non-commercial/small commercial farms on the Apennines, which were also characterised by non-compliance with critical biosecurity measures. Frontiers Media S.A. 2023-01-27 /pmc/articles/PMC9911915/ /pubmed/36777667 http://dx.doi.org/10.3389/fvets.2023.1017001 Text en Copyright © 2023 Scollo, Valentini, Franceschini, Rusinà, Calò, Cappa, Bellato, Mannelli, Alborali and Bellini. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Veterinary Science Scollo, Annalisa Valentini, Francesco Franceschini, Giorgio Rusinà, Alessia Calò, Stefania Cappa, Veronica Bellato, Alessandro Mannelli, Alessandro Alborali, Giovanni Loris Bellini, Silvia Semi-quantitative risk assessment of African swine fever virus introduction in pig farms |
title | Semi-quantitative risk assessment of African swine fever virus introduction in pig farms |
title_full | Semi-quantitative risk assessment of African swine fever virus introduction in pig farms |
title_fullStr | Semi-quantitative risk assessment of African swine fever virus introduction in pig farms |
title_full_unstemmed | Semi-quantitative risk assessment of African swine fever virus introduction in pig farms |
title_short | Semi-quantitative risk assessment of African swine fever virus introduction in pig farms |
title_sort | semi-quantitative risk assessment of african swine fever virus introduction in pig farms |
topic | Veterinary Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9911915/ https://www.ncbi.nlm.nih.gov/pubmed/36777667 http://dx.doi.org/10.3389/fvets.2023.1017001 |
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