Loading…
Impact of palmiped farm density on the resilience of the poultry sector to highly pathogenic avian influenza H5N8 in France
We analysed the interplay between palmiped farm density and the vulnerability of the poultry production system to highly pathogenic avian influenza (HPAI) H5N8. To do so, we used a spatially-explicit transmission model, which was calibrated to reproduce the observed spatio-temporal distribution of o...
Saved in:
Published in: | Veterinary research (Paris) 2023-07, Vol.54 (1), p.56-56, Article 56 |
---|---|
Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c598t-58c08a00733620b3ba244dd06b6be305f4ce1213a76d6347d0c0dd9fb8dbf1893 |
---|---|
cites | cdi_FETCH-LOGICAL-c598t-58c08a00733620b3ba244dd06b6be305f4ce1213a76d6347d0c0dd9fb8dbf1893 |
container_end_page | 56 |
container_issue | 1 |
container_start_page | 56 |
container_title | Veterinary research (Paris) |
container_volume | 54 |
creator | Bauzile, Billy Durand, Benoit Lambert, Sébastien Rautureau, Séverine Fourtune, Lisa Guinat, Claire Andronico, Alessio Cauchemez, Simon Paul, Mathilde C Vergne, Timothée |
description | We analysed the interplay between palmiped farm density and the vulnerability of the poultry production system to highly pathogenic avian influenza (HPAI) H5N8. To do so, we used a spatially-explicit transmission model, which was calibrated to reproduce the observed spatio-temporal distribution of outbreaks in France during the 2016-2017 epidemic of HPAI. Six scenarios were investigated, in which the density of palmiped farms was decreased in the municipalities with the highest palmiped farm density. For each of the six scenarios, we first calculated the spatial distribution of the basic reproduction number (R
), i.e. the expected number of farms a particular farm would be likely to infect, should all other farms be susceptible. We also ran in silico simulations of the adjusted model for each scenario to estimate epidemic sizes and time-varying effective reproduction numbers. We showed that reducing palmiped farm density in the densest municipalities decreased substantially the size of the areas with high R
values (> 1.5). In silico simulations suggested that reducing palmiped farm density, even slightly, in the densest municipalities was expected to decrease substantially the number of affected poultry farms and therefore provide benefits to the poultry sector as a whole. However, they also suggest that it would not have been sufficient, even in combination with the intervention measures implemented during the 2016-2017 epidemic, to completely prevent the virus from spreading. Therefore, the effectiveness of alternative structural preventive approaches now needs to be assessed, including flock size reduction and targeted vaccination. |
doi_str_mv | 10.1186/s13567-023-01183-9 |
format | article |
fullrecord | <record><control><sourceid>gale_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_f7c7f9fe17d84e808f7d0bbcff36a31b</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A756751304</galeid><doaj_id>oai_doaj_org_article_f7c7f9fe17d84e808f7d0bbcff36a31b</doaj_id><sourcerecordid>A756751304</sourcerecordid><originalsourceid>FETCH-LOGICAL-c598t-58c08a00733620b3ba244dd06b6be305f4ce1213a76d6347d0c0dd9fb8dbf1893</originalsourceid><addsrcrecordid>eNptks1u1DAUhSMEoqXwAiyQJTawSLHjxHZWaFRRZqQKNrC2HP9MPErsYDsjDbw8TqeMOhXKwvHxuV_ie09RvEXwGiFGPkWEG0JLWOESZgGX7bPiElUtLVuKyPNH7xfFqxh3ECKCm_plcYFpjWHVVpfFn804CZmAN2ASw2gnrYARYQRKu2jTAXgHUq9B0NEOVjupF-uiTH4eUjiAqGXyASQPervth0PmpN5vtbMSiL0VDlhnhlm73wKsm28sb8FtEJn0unhhxBD1m4f1qvh5--XHzbq8-_51c7O6K2XTslQ2TEImIKQYkwp2uBNVXSsFSUc6jWFjaqlRhbCgRBFcUwUlVKo1HVOdQazFV8XmyFVe7PgU7CjCgXth-b3gw5aLkKwcNDdUUtMajahitWaQmYzrOmkMJgKjLrM-H1nT3I1aSe1SEMMZ9PzE2Z5v_Z4jiHFNIMmEj0dC_6RuvbrjiwbrPEuK8B5l74eHrwX_a9Yx8dFGqYdBOO3nyCuWW9ISWsFsff_EuvNzcLmvi4vRFqHcwZNrK_Jt82B8_km5QPmK5jA1CMM6u67_48qP0qOV3mljs35WUB0LZPAxBm1OF0OQL1nlx6zynFV-n1W-jOXd41aeSv6FE_8F4zfjgw</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2838791107</pqid></control><display><type>article</type><title>Impact of palmiped farm density on the resilience of the poultry sector to highly pathogenic avian influenza H5N8 in France</title><source>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</source><source>PubMed Central</source><creator>Bauzile, Billy ; Durand, Benoit ; Lambert, Sébastien ; Rautureau, Séverine ; Fourtune, Lisa ; Guinat, Claire ; Andronico, Alessio ; Cauchemez, Simon ; Paul, Mathilde C ; Vergne, Timothée</creator><creatorcontrib>Bauzile, Billy ; Durand, Benoit ; Lambert, Sébastien ; Rautureau, Séverine ; Fourtune, Lisa ; Guinat, Claire ; Andronico, Alessio ; Cauchemez, Simon ; Paul, Mathilde C ; Vergne, Timothée</creatorcontrib><description>We analysed the interplay between palmiped farm density and the vulnerability of the poultry production system to highly pathogenic avian influenza (HPAI) H5N8. To do so, we used a spatially-explicit transmission model, which was calibrated to reproduce the observed spatio-temporal distribution of outbreaks in France during the 2016-2017 epidemic of HPAI. Six scenarios were investigated, in which the density of palmiped farms was decreased in the municipalities with the highest palmiped farm density. For each of the six scenarios, we first calculated the spatial distribution of the basic reproduction number (R
), i.e. the expected number of farms a particular farm would be likely to infect, should all other farms be susceptible. We also ran in silico simulations of the adjusted model for each scenario to estimate epidemic sizes and time-varying effective reproduction numbers. We showed that reducing palmiped farm density in the densest municipalities decreased substantially the size of the areas with high R
values (> 1.5). In silico simulations suggested that reducing palmiped farm density, even slightly, in the densest municipalities was expected to decrease substantially the number of affected poultry farms and therefore provide benefits to the poultry sector as a whole. However, they also suggest that it would not have been sufficient, even in combination with the intervention measures implemented during the 2016-2017 epidemic, to completely prevent the virus from spreading. Therefore, the effectiveness of alternative structural preventive approaches now needs to be assessed, including flock size reduction and targeted vaccination.</description><identifier>ISSN: 1297-9716</identifier><identifier>ISSN: 0928-4249</identifier><identifier>EISSN: 1297-9716</identifier><identifier>DOI: 10.1186/s13567-023-01183-9</identifier><identifier>PMID: 37430292</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Analysis ; Animal biology ; Animals ; Avian influenza ; Bird flu ; control ; Epidemics ; Farms ; France ; France - epidemiology ; Infections ; Influenza ; Influenza A Virus, H5N8 Subtype ; Influenza in Birds - epidemiology ; Influenza in Birds - prevention & control ; Life Sciences ; Livestock farms ; mechanistic model ; Microbiology and Parasitology ; Poultry ; Poultry industry ; Prevention ; simulations ; Surveillance ; Veterinary medicine and animal Health</subject><ispartof>Veterinary research (Paris), 2023-07, Vol.54 (1), p.56-56, Article 56</ispartof><rights>2023. The Author(s).</rights><rights>COPYRIGHT 2023 BioMed Central Ltd.</rights><rights>2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Attribution - NonCommercial</rights><rights>The Author(s) 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c598t-58c08a00733620b3ba244dd06b6be305f4ce1213a76d6347d0c0dd9fb8dbf1893</citedby><cites>FETCH-LOGICAL-c598t-58c08a00733620b3ba244dd06b6be305f4ce1213a76d6347d0c0dd9fb8dbf1893</cites><orcidid>0000-0002-1146-9256 ; 0000-0001-6901-373X ; 0000-0002-9481-3461 ; 0000-0002-8245-9290 ; 0000-0001-9186-4549 ; 0000-0003-2940-8547 ; 0000-0002-3542-7245 ; 0000-0002-8855-3341 ; 0000-0003-0669-1394</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10334606/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2838791107?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25752,27923,27924,37011,37012,44589,53790,53792</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37430292$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.inrae.fr/hal-04183713$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Bauzile, Billy</creatorcontrib><creatorcontrib>Durand, Benoit</creatorcontrib><creatorcontrib>Lambert, Sébastien</creatorcontrib><creatorcontrib>Rautureau, Séverine</creatorcontrib><creatorcontrib>Fourtune, Lisa</creatorcontrib><creatorcontrib>Guinat, Claire</creatorcontrib><creatorcontrib>Andronico, Alessio</creatorcontrib><creatorcontrib>Cauchemez, Simon</creatorcontrib><creatorcontrib>Paul, Mathilde C</creatorcontrib><creatorcontrib>Vergne, Timothée</creatorcontrib><title>Impact of palmiped farm density on the resilience of the poultry sector to highly pathogenic avian influenza H5N8 in France</title><title>Veterinary research (Paris)</title><addtitle>Vet Res</addtitle><description>We analysed the interplay between palmiped farm density and the vulnerability of the poultry production system to highly pathogenic avian influenza (HPAI) H5N8. To do so, we used a spatially-explicit transmission model, which was calibrated to reproduce the observed spatio-temporal distribution of outbreaks in France during the 2016-2017 epidemic of HPAI. Six scenarios were investigated, in which the density of palmiped farms was decreased in the municipalities with the highest palmiped farm density. For each of the six scenarios, we first calculated the spatial distribution of the basic reproduction number (R
), i.e. the expected number of farms a particular farm would be likely to infect, should all other farms be susceptible. We also ran in silico simulations of the adjusted model for each scenario to estimate epidemic sizes and time-varying effective reproduction numbers. We showed that reducing palmiped farm density in the densest municipalities decreased substantially the size of the areas with high R
values (> 1.5). In silico simulations suggested that reducing palmiped farm density, even slightly, in the densest municipalities was expected to decrease substantially the number of affected poultry farms and therefore provide benefits to the poultry sector as a whole. However, they also suggest that it would not have been sufficient, even in combination with the intervention measures implemented during the 2016-2017 epidemic, to completely prevent the virus from spreading. Therefore, the effectiveness of alternative structural preventive approaches now needs to be assessed, including flock size reduction and targeted vaccination.</description><subject>Analysis</subject><subject>Animal biology</subject><subject>Animals</subject><subject>Avian influenza</subject><subject>Bird flu</subject><subject>control</subject><subject>Epidemics</subject><subject>Farms</subject><subject>France</subject><subject>France - epidemiology</subject><subject>Infections</subject><subject>Influenza</subject><subject>Influenza A Virus, H5N8 Subtype</subject><subject>Influenza in Birds - epidemiology</subject><subject>Influenza in Birds - prevention & control</subject><subject>Life Sciences</subject><subject>Livestock farms</subject><subject>mechanistic model</subject><subject>Microbiology and Parasitology</subject><subject>Poultry</subject><subject>Poultry industry</subject><subject>Prevention</subject><subject>simulations</subject><subject>Surveillance</subject><subject>Veterinary medicine and animal Health</subject><issn>1297-9716</issn><issn>0928-4249</issn><issn>1297-9716</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNptks1u1DAUhSMEoqXwAiyQJTawSLHjxHZWaFRRZqQKNrC2HP9MPErsYDsjDbw8TqeMOhXKwvHxuV_ie09RvEXwGiFGPkWEG0JLWOESZgGX7bPiElUtLVuKyPNH7xfFqxh3ECKCm_plcYFpjWHVVpfFn804CZmAN2ASw2gnrYARYQRKu2jTAXgHUq9B0NEOVjupF-uiTH4eUjiAqGXyASQPervth0PmpN5vtbMSiL0VDlhnhlm73wKsm28sb8FtEJn0unhhxBD1m4f1qvh5--XHzbq8-_51c7O6K2XTslQ2TEImIKQYkwp2uBNVXSsFSUc6jWFjaqlRhbCgRBFcUwUlVKo1HVOdQazFV8XmyFVe7PgU7CjCgXth-b3gw5aLkKwcNDdUUtMajahitWaQmYzrOmkMJgKjLrM-H1nT3I1aSe1SEMMZ9PzE2Z5v_Z4jiHFNIMmEj0dC_6RuvbrjiwbrPEuK8B5l74eHrwX_a9Yx8dFGqYdBOO3nyCuWW9ISWsFsff_EuvNzcLmvi4vRFqHcwZNrK_Jt82B8_km5QPmK5jA1CMM6u67_48qP0qOV3mljs35WUB0LZPAxBm1OF0OQL1nlx6zynFV-n1W-jOXd41aeSv6FE_8F4zfjgw</recordid><startdate>20230710</startdate><enddate>20230710</enddate><creator>Bauzile, Billy</creator><creator>Durand, Benoit</creator><creator>Lambert, Sébastien</creator><creator>Rautureau, Séverine</creator><creator>Fourtune, Lisa</creator><creator>Guinat, Claire</creator><creator>Andronico, Alessio</creator><creator>Cauchemez, Simon</creator><creator>Paul, Mathilde C</creator><creator>Vergne, Timothée</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><general>BMC</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88I</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>1XC</scope><scope>VOOES</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-1146-9256</orcidid><orcidid>https://orcid.org/0000-0001-6901-373X</orcidid><orcidid>https://orcid.org/0000-0002-9481-3461</orcidid><orcidid>https://orcid.org/0000-0002-8245-9290</orcidid><orcidid>https://orcid.org/0000-0001-9186-4549</orcidid><orcidid>https://orcid.org/0000-0003-2940-8547</orcidid><orcidid>https://orcid.org/0000-0002-3542-7245</orcidid><orcidid>https://orcid.org/0000-0002-8855-3341</orcidid><orcidid>https://orcid.org/0000-0003-0669-1394</orcidid></search><sort><creationdate>20230710</creationdate><title>Impact of palmiped farm density on the resilience of the poultry sector to highly pathogenic avian influenza H5N8 in France</title><author>Bauzile, Billy ; Durand, Benoit ; Lambert, Sébastien ; Rautureau, Séverine ; Fourtune, Lisa ; Guinat, Claire ; Andronico, Alessio ; Cauchemez, Simon ; Paul, Mathilde C ; Vergne, Timothée</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c598t-58c08a00733620b3ba244dd06b6be305f4ce1213a76d6347d0c0dd9fb8dbf1893</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Analysis</topic><topic>Animal biology</topic><topic>Animals</topic><topic>Avian influenza</topic><topic>Bird flu</topic><topic>control</topic><topic>Epidemics</topic><topic>Farms</topic><topic>France</topic><topic>France - epidemiology</topic><topic>Infections</topic><topic>Influenza</topic><topic>Influenza A Virus, H5N8 Subtype</topic><topic>Influenza in Birds - epidemiology</topic><topic>Influenza in Birds - prevention & control</topic><topic>Life Sciences</topic><topic>Livestock farms</topic><topic>mechanistic model</topic><topic>Microbiology and Parasitology</topic><topic>Poultry</topic><topic>Poultry industry</topic><topic>Prevention</topic><topic>simulations</topic><topic>Surveillance</topic><topic>Veterinary medicine and animal Health</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bauzile, Billy</creatorcontrib><creatorcontrib>Durand, Benoit</creatorcontrib><creatorcontrib>Lambert, Sébastien</creatorcontrib><creatorcontrib>Rautureau, Séverine</creatorcontrib><creatorcontrib>Fourtune, Lisa</creatorcontrib><creatorcontrib>Guinat, Claire</creatorcontrib><creatorcontrib>Andronico, Alessio</creatorcontrib><creatorcontrib>Cauchemez, Simon</creatorcontrib><creatorcontrib>Paul, Mathilde C</creatorcontrib><creatorcontrib>Vergne, Timothée</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest Science Journals</collection><collection>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Veterinary research (Paris)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bauzile, Billy</au><au>Durand, Benoit</au><au>Lambert, Sébastien</au><au>Rautureau, Séverine</au><au>Fourtune, Lisa</au><au>Guinat, Claire</au><au>Andronico, Alessio</au><au>Cauchemez, Simon</au><au>Paul, Mathilde C</au><au>Vergne, Timothée</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Impact of palmiped farm density on the resilience of the poultry sector to highly pathogenic avian influenza H5N8 in France</atitle><jtitle>Veterinary research (Paris)</jtitle><addtitle>Vet Res</addtitle><date>2023-07-10</date><risdate>2023</risdate><volume>54</volume><issue>1</issue><spage>56</spage><epage>56</epage><pages>56-56</pages><artnum>56</artnum><issn>1297-9716</issn><issn>0928-4249</issn><eissn>1297-9716</eissn><abstract>We analysed the interplay between palmiped farm density and the vulnerability of the poultry production system to highly pathogenic avian influenza (HPAI) H5N8. To do so, we used a spatially-explicit transmission model, which was calibrated to reproduce the observed spatio-temporal distribution of outbreaks in France during the 2016-2017 epidemic of HPAI. Six scenarios were investigated, in which the density of palmiped farms was decreased in the municipalities with the highest palmiped farm density. For each of the six scenarios, we first calculated the spatial distribution of the basic reproduction number (R
), i.e. the expected number of farms a particular farm would be likely to infect, should all other farms be susceptible. We also ran in silico simulations of the adjusted model for each scenario to estimate epidemic sizes and time-varying effective reproduction numbers. We showed that reducing palmiped farm density in the densest municipalities decreased substantially the size of the areas with high R
values (> 1.5). In silico simulations suggested that reducing palmiped farm density, even slightly, in the densest municipalities was expected to decrease substantially the number of affected poultry farms and therefore provide benefits to the poultry sector as a whole. However, they also suggest that it would not have been sufficient, even in combination with the intervention measures implemented during the 2016-2017 epidemic, to completely prevent the virus from spreading. Therefore, the effectiveness of alternative structural preventive approaches now needs to be assessed, including flock size reduction and targeted vaccination.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>37430292</pmid><doi>10.1186/s13567-023-01183-9</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-1146-9256</orcidid><orcidid>https://orcid.org/0000-0001-6901-373X</orcidid><orcidid>https://orcid.org/0000-0002-9481-3461</orcidid><orcidid>https://orcid.org/0000-0002-8245-9290</orcidid><orcidid>https://orcid.org/0000-0001-9186-4549</orcidid><orcidid>https://orcid.org/0000-0003-2940-8547</orcidid><orcidid>https://orcid.org/0000-0002-3542-7245</orcidid><orcidid>https://orcid.org/0000-0002-8855-3341</orcidid><orcidid>https://orcid.org/0000-0003-0669-1394</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1297-9716 |
ispartof | Veterinary research (Paris), 2023-07, Vol.54 (1), p.56-56, Article 56 |
issn | 1297-9716 0928-4249 1297-9716 |
language | eng |
recordid | cdi_doaj_primary_oai_doaj_org_article_f7c7f9fe17d84e808f7d0bbcff36a31b |
source | Publicly Available Content Database (Proquest) (PQ_SDU_P3); PubMed Central |
subjects | Analysis Animal biology Animals Avian influenza Bird flu control Epidemics Farms France France - epidemiology Infections Influenza Influenza A Virus, H5N8 Subtype Influenza in Birds - epidemiology Influenza in Birds - prevention & control Life Sciences Livestock farms mechanistic model Microbiology and Parasitology Poultry Poultry industry Prevention simulations Surveillance Veterinary medicine and animal Health |
title | Impact of palmiped farm density on the resilience of the poultry sector to highly pathogenic avian influenza H5N8 in France |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-12T05%3A24%3A14IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Impact%20of%20palmiped%20farm%20density%20on%20the%20resilience%20of%20the%20poultry%20sector%20to%20highly%20pathogenic%20avian%20influenza%20H5N8%20in%20France&rft.jtitle=Veterinary%20research%20(Paris)&rft.au=Bauzile,%20Billy&rft.date=2023-07-10&rft.volume=54&rft.issue=1&rft.spage=56&rft.epage=56&rft.pages=56-56&rft.artnum=56&rft.issn=1297-9716&rft.eissn=1297-9716&rft_id=info:doi/10.1186/s13567-023-01183-9&rft_dat=%3Cgale_doaj_%3EA756751304%3C/gale_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c598t-58c08a00733620b3ba244dd06b6be305f4ce1213a76d6347d0c0dd9fb8dbf1893%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2838791107&rft_id=info:pmid/37430292&rft_galeid=A756751304&rfr_iscdi=true |