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Integration of Epidemiological and Genomic Data to Investigate H5N1 HPAI Outbreaks in Northern Italy in 2021–2022
Between October 2021 and April 2022, 317 outbreaks caused by highly pathogenic avian influenza (HPAI) H5N1 viruses were notified in poultry farms in the northeastern Italian regions. The complete genomes of 214 strains were used to estimate the genetic network based on the similarity of the viruses....
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9865711/ https://www.ncbi.nlm.nih.gov/pubmed/36678449 http://dx.doi.org/10.3390/pathogens12010100 |
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author | Fornasiero, Diletta Fusaro, Alice Zecchin, Bianca Mazzucato, Matteo Scolamacchia, Francesca Manca, Grazia Terregino, Calogero Dorotea, Tiziano Mulatti, Paolo |
author_facet | Fornasiero, Diletta Fusaro, Alice Zecchin, Bianca Mazzucato, Matteo Scolamacchia, Francesca Manca, Grazia Terregino, Calogero Dorotea, Tiziano Mulatti, Paolo |
author_sort | Fornasiero, Diletta |
collection | PubMed |
description | Between October 2021 and April 2022, 317 outbreaks caused by highly pathogenic avian influenza (HPAI) H5N1 viruses were notified in poultry farms in the northeastern Italian regions. The complete genomes of 214 strains were used to estimate the genetic network based on the similarity of the viruses. An exponential random graph model (ERGM) was used to assess the effect of ‘at-risk contacts’, ‘same owners’, ‘in-bound/out-bound risk windows overlap’, ‘genetic differences’, ‘geographic distances’, ‘same species’, and ‘poultry company’ on the probability of observing a link within the genetic network, which can be interpreted as the potential propagation of the epidemic via lateral spread or a common source of infection. The variables ‘same poultry company’ (Est. = 0.548, C.I. = [0.179; 0.918]) and ‘risk windows overlap’ (Est. = 0.339, C.I. = [0.309; 0.368]) were associated with a higher probability of link formation, while the ‘genetic differences’ (Est. = −0.563, C.I. = [−0.640; −0.486]) and ‘geographic distances’ (Est. = −0.058, C.I. = [−0.078; −0.038]) indicated a reduced probability. The integration of epidemiological data with genomic analyses allows us to monitor the epidemic evolution and helps to explain the dynamics of lateral spreads casting light on the potential diffusion routes. The 2021–2022 epidemic stresses the need to further strengthen the biosecurity measures, and to encourage the reorganization of the poultry production sector to minimize the impact of future epidemics. |
format | Online Article Text |
id | pubmed-9865711 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98657112023-01-22 Integration of Epidemiological and Genomic Data to Investigate H5N1 HPAI Outbreaks in Northern Italy in 2021–2022 Fornasiero, Diletta Fusaro, Alice Zecchin, Bianca Mazzucato, Matteo Scolamacchia, Francesca Manca, Grazia Terregino, Calogero Dorotea, Tiziano Mulatti, Paolo Pathogens Article Between October 2021 and April 2022, 317 outbreaks caused by highly pathogenic avian influenza (HPAI) H5N1 viruses were notified in poultry farms in the northeastern Italian regions. The complete genomes of 214 strains were used to estimate the genetic network based on the similarity of the viruses. An exponential random graph model (ERGM) was used to assess the effect of ‘at-risk contacts’, ‘same owners’, ‘in-bound/out-bound risk windows overlap’, ‘genetic differences’, ‘geographic distances’, ‘same species’, and ‘poultry company’ on the probability of observing a link within the genetic network, which can be interpreted as the potential propagation of the epidemic via lateral spread or a common source of infection. The variables ‘same poultry company’ (Est. = 0.548, C.I. = [0.179; 0.918]) and ‘risk windows overlap’ (Est. = 0.339, C.I. = [0.309; 0.368]) were associated with a higher probability of link formation, while the ‘genetic differences’ (Est. = −0.563, C.I. = [−0.640; −0.486]) and ‘geographic distances’ (Est. = −0.058, C.I. = [−0.078; −0.038]) indicated a reduced probability. The integration of epidemiological data with genomic analyses allows us to monitor the epidemic evolution and helps to explain the dynamics of lateral spreads casting light on the potential diffusion routes. The 2021–2022 epidemic stresses the need to further strengthen the biosecurity measures, and to encourage the reorganization of the poultry production sector to minimize the impact of future epidemics. MDPI 2023-01-06 /pmc/articles/PMC9865711/ /pubmed/36678449 http://dx.doi.org/10.3390/pathogens12010100 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Fornasiero, Diletta Fusaro, Alice Zecchin, Bianca Mazzucato, Matteo Scolamacchia, Francesca Manca, Grazia Terregino, Calogero Dorotea, Tiziano Mulatti, Paolo Integration of Epidemiological and Genomic Data to Investigate H5N1 HPAI Outbreaks in Northern Italy in 2021–2022 |
title | Integration of Epidemiological and Genomic Data to Investigate H5N1 HPAI Outbreaks in Northern Italy in 2021–2022 |
title_full | Integration of Epidemiological and Genomic Data to Investigate H5N1 HPAI Outbreaks in Northern Italy in 2021–2022 |
title_fullStr | Integration of Epidemiological and Genomic Data to Investigate H5N1 HPAI Outbreaks in Northern Italy in 2021–2022 |
title_full_unstemmed | Integration of Epidemiological and Genomic Data to Investigate H5N1 HPAI Outbreaks in Northern Italy in 2021–2022 |
title_short | Integration of Epidemiological and Genomic Data to Investigate H5N1 HPAI Outbreaks in Northern Italy in 2021–2022 |
title_sort | integration of epidemiological and genomic data to investigate h5n1 hpai outbreaks in northern italy in 2021–2022 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9865711/ https://www.ncbi.nlm.nih.gov/pubmed/36678449 http://dx.doi.org/10.3390/pathogens12010100 |
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