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Establishment of serological herd profiles for zoonoses and production diseases in pigs by "meat juice multi-serology".

Identifieur interne : 000173 ( Main/Exploration ); précédent : 000172; suivant : 000174

Establishment of serological herd profiles for zoonoses and production diseases in pigs by "meat juice multi-serology".

Auteurs : Diana Meemken [Allemagne] ; Anna Helene Tangemann [Allemagne] ; Dieter Meermeier [Allemagne] ; Susanne Gundlach [Allemagne] ; Dieter Mischok [Allemagne] ; Matthias Greiner [Allemagne] ; Guenter Klein [Allemagne] ; Thomas Blaha [Allemagne]

Source :

RBID : pubmed:24411983

Descripteurs français

English descriptors

Abstract

The most important pork-borne zoonotic diseases in humans such as Salmonelloses and Yersinioses cause only latent infections in pigs. Thus, the infection of pigs does not result in apparent or palpable alterations in the pig carcasses. This is the major reason, why the traditional meat inspection with adspection, palpation and incision is not able to control the food safety risks of today. The objective of this paper is to evaluate a set of serological tests, which provides a classification of pig herds into "zoonoses risk categories" as demanded by EU law and into "herd health risk categories" by using meat juice as diagnostic specimen for ELISA tests. Serological data that were obtained by testing meat juice samples from various pig herds were analyzed as proof of the "meat juice multi-serology" concept. For that, at least 60 meat juice samples from 49 pig herds each were taken between September 2010 and March 2011 and tested for antibodies against zoonotic pathogens (Salmonella spp., Trichinella spp., Yersinia enterocolitica and Toxoplasma gondii) and against pathogens causing production diseases (Mycoplasma hyopneumoniae, influenza A virus subtype H1N1, influenza A virus subtype H3N2 and PRRSV). Apparent and true animal prevalence, herd prevalence values and intra-herd seroprevalence values as well as the predictive values for the herd and the animal prevalence values were calculated for each pathogen and each of the 49 randomly selected herds. The herd seroprevalence values (one seropositive sample per herd determined a "positive herd") for Y. enterocolitica, Salmonella spp., T. gondii, M. hyopneumoniae and PRRSV were higher than 80%, respectively, for the influenza A viruses between 60% and 14% and for Trichinella spp. 0%. Although all herds were located in the same area in the Northwest of Germany within a radius of 250 km, the intra-herd seroprevalence values for all tested pathogens, except for Trichinella spp., varied remarkably from herd to herd. In the case of Y. enterocolitica and T. gondii the intra-herd seroprevalence values varied even from zero to 100%. This shows that a serological risk categorization of pig herds regarding zoonoses and production diseases is meaningful if used for risk-based decisions in the framework of the new meat inspection concept and as part of the herd health management system. Thus, the development of a cost-efficient, time- and labour-saving test system for simultaneously detecting various antibodies should be the next step for an extensive implementation of the meat juice multi-serology concept.

DOI: 10.1016/j.prevetmed.2013.12.006
PubMed: 24411983


Affiliations:


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Le document en format XML

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<div type="abstract" xml:lang="en">The most important pork-borne zoonotic diseases in humans such as Salmonelloses and Yersinioses cause only latent infections in pigs. Thus, the infection of pigs does not result in apparent or palpable alterations in the pig carcasses. This is the major reason, why the traditional meat inspection with adspection, palpation and incision is not able to control the food safety risks of today. The objective of this paper is to evaluate a set of serological tests, which provides a classification of pig herds into "zoonoses risk categories" as demanded by EU law and into "herd health risk categories" by using meat juice as diagnostic specimen for ELISA tests. Serological data that were obtained by testing meat juice samples from various pig herds were analyzed as proof of the "meat juice multi-serology" concept. For that, at least 60 meat juice samples from 49 pig herds each were taken between September 2010 and March 2011 and tested for antibodies against zoonotic pathogens (Salmonella spp., Trichinella spp., Yersinia enterocolitica and Toxoplasma gondii) and against pathogens causing production diseases (Mycoplasma hyopneumoniae, influenza A virus subtype H1N1, influenza A virus subtype H3N2 and PRRSV). Apparent and true animal prevalence, herd prevalence values and intra-herd seroprevalence values as well as the predictive values for the herd and the animal prevalence values were calculated for each pathogen and each of the 49 randomly selected herds. The herd seroprevalence values (one seropositive sample per herd determined a "positive herd") for Y. enterocolitica, Salmonella spp., T. gondii, M. hyopneumoniae and PRRSV were higher than 80%, respectively, for the influenza A viruses between 60% and 14% and for Trichinella spp. 0%. Although all herds were located in the same area in the Northwest of Germany within a radius of 250 km, the intra-herd seroprevalence values for all tested pathogens, except for Trichinella spp., varied remarkably from herd to herd. In the case of Y. enterocolitica and T. gondii the intra-herd seroprevalence values varied even from zero to 100%. This shows that a serological risk categorization of pig herds regarding zoonoses and production diseases is meaningful if used for risk-based decisions in the framework of the new meat inspection concept and as part of the herd health management system. Thus, the development of a cost-efficient, time- and labour-saving test system for simultaneously detecting various antibodies should be the next step for an extensive implementation of the meat juice multi-serology concept.</div>
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<ELocationID EIdType="pii" ValidYN="Y">S0167-5877(13)00388-7</ELocationID>
<Abstract>
<AbstractText>The most important pork-borne zoonotic diseases in humans such as Salmonelloses and Yersinioses cause only latent infections in pigs. Thus, the infection of pigs does not result in apparent or palpable alterations in the pig carcasses. This is the major reason, why the traditional meat inspection with adspection, palpation and incision is not able to control the food safety risks of today. The objective of this paper is to evaluate a set of serological tests, which provides a classification of pig herds into "zoonoses risk categories" as demanded by EU law and into "herd health risk categories" by using meat juice as diagnostic specimen for ELISA tests. Serological data that were obtained by testing meat juice samples from various pig herds were analyzed as proof of the "meat juice multi-serology" concept. For that, at least 60 meat juice samples from 49 pig herds each were taken between September 2010 and March 2011 and tested for antibodies against zoonotic pathogens (Salmonella spp., Trichinella spp., Yersinia enterocolitica and Toxoplasma gondii) and against pathogens causing production diseases (Mycoplasma hyopneumoniae, influenza A virus subtype H1N1, influenza A virus subtype H3N2 and PRRSV). Apparent and true animal prevalence, herd prevalence values and intra-herd seroprevalence values as well as the predictive values for the herd and the animal prevalence values were calculated for each pathogen and each of the 49 randomly selected herds. The herd seroprevalence values (one seropositive sample per herd determined a "positive herd") for Y. enterocolitica, Salmonella spp., T. gondii, M. hyopneumoniae and PRRSV were higher than 80%, respectively, for the influenza A viruses between 60% and 14% and for Trichinella spp. 0%. Although all herds were located in the same area in the Northwest of Germany within a radius of 250 km, the intra-herd seroprevalence values for all tested pathogens, except for Trichinella spp., varied remarkably from herd to herd. In the case of Y. enterocolitica and T. gondii the intra-herd seroprevalence values varied even from zero to 100%. This shows that a serological risk categorization of pig herds regarding zoonoses and production diseases is meaningful if used for risk-based decisions in the framework of the new meat inspection concept and as part of the herd health management system. Thus, the development of a cost-efficient, time- and labour-saving test system for simultaneously detecting various antibodies should be the next step for an extensive implementation of the meat juice multi-serology concept.</AbstractText>
<CopyrightInformation>Copyright © 2013 Elsevier B.V. All rights reserved.</CopyrightInformation>
</Abstract>
<AuthorList CompleteYN="Y">
<Author ValidYN="Y">
<LastName>Meemken</LastName>
<ForeName>Diana</ForeName>
<Initials>D</Initials>
<AffiliationInfo>
<Affiliation>Institute for Food Quality and Food Safety, University of Veterinary Medicine Hannover, Foundation, Bischofsholer Damm 15, D-30173 Hannover, Germany. Electronic address: Diana.meemken@tiho-hannover.de.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Tangemann</LastName>
<ForeName>Anna Helene</ForeName>
<Initials>AH</Initials>
<AffiliationInfo>
<Affiliation>Field Station for Epidemiology, University of Veterinary Medicine Hannover, Foundation, Buescheler Str. 9, D-49456 Bakum, Germany.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Meermeier</LastName>
<ForeName>Dieter</ForeName>
<Initials>D</Initials>
<AffiliationInfo>
<Affiliation>Veterinary Authority for Meat Inspection of Paderborn, Aldegreverstraße 10-14, D-33102 Paderborn, Germany.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Gundlach</LastName>
<ForeName>Susanne</ForeName>
<Initials>S</Initials>
<AffiliationInfo>
<Affiliation>Agricultural Analytic and Research Institute of North Rhine-Westphalia, Germany (LUFA NRW), Nevinghoff 40, D-48147 Münster, Germany.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Mischok</LastName>
<ForeName>Dieter</ForeName>
<Initials>D</Initials>
<AffiliationInfo>
<Affiliation>Veterinary Service Westfleisch e.G., Brockhoffstraße 11, D-48143 Münster, Germany.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Greiner</LastName>
<ForeName>Matthias</ForeName>
<Initials>M</Initials>
<AffiliationInfo>
<Affiliation>Institute for Food Quality and Food Safety, University of Veterinary Medicine Hannover, Foundation, Bischofsholer Damm 15, D-30173 Hannover, Germany; Federal Institute for Risk Assessment (BfR), Max-Dohrn-Straße 8-10, 10589 Berlin, Germany.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Klein</LastName>
<ForeName>Guenter</ForeName>
<Initials>G</Initials>
<AffiliationInfo>
<Affiliation>Institute for Food Quality and Food Safety, University of Veterinary Medicine Hannover, Foundation, Bischofsholer Damm 15, D-30173 Hannover, Germany.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Blaha</LastName>
<ForeName>Thomas</ForeName>
<Initials>T</Initials>
<AffiliationInfo>
<Affiliation>Field Station for Epidemiology, University of Veterinary Medicine Hannover, Foundation, Buescheler Str. 9, D-49456 Bakum, Germany.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList>
<PublicationType UI="D016428">Journal Article</PublicationType>
<PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic">
<Year>2013</Year>
<Month>12</Month>
<Day>25</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo>
<Country>Netherlands</Country>
<MedlineTA>Prev Vet Med</MedlineTA>
<NlmUniqueID>8217463</NlmUniqueID>
<ISSNLinking>0167-5877</ISSNLinking>
</MedlineJournalInfo>
<ChemicalList>
<Chemical>
<RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D000906">Antibodies</NameOfSubstance>
</Chemical>
</ChemicalList>
<CitationSubset>IM</CitationSubset>
<MeshHeadingList>
<MeshHeading>
<DescriptorName UI="D000003" MajorTopicYN="N">Abattoirs</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D000818" MajorTopicYN="N">Animals</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D000906" MajorTopicYN="N">Antibodies</DescriptorName>
<QualifierName UI="Q000032" MajorTopicYN="N">analysis</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D003430" MajorTopicYN="N">Cross-Sectional Studies</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D004797" MajorTopicYN="N">Enzyme-Linked Immunosorbent Assay</DescriptorName>
<QualifierName UI="Q000662" MajorTopicYN="Y">veterinary</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D005858" MajorTopicYN="N" Type="Geographic">Germany</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D008460" MajorTopicYN="N">Meat</DescriptorName>
<QualifierName UI="Q000382" MajorTopicYN="Y">microbiology</QualifierName>
<QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D015995" MajorTopicYN="N">Prevalence</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D016036" MajorTopicYN="N">Seroepidemiologic Studies</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D013552" MajorTopicYN="N">Swine</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D013553" MajorTopicYN="N">Swine Diseases</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName>
<QualifierName UI="Q000382" MajorTopicYN="N">microbiology</QualifierName>
<QualifierName UI="Q000469" MajorTopicYN="N">parasitology</QualifierName>
<QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D015047" MajorTopicYN="N">Zoonoses</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName>
<QualifierName UI="Q000382" MajorTopicYN="N">microbiology</QualifierName>
<QualifierName UI="Q000469" MajorTopicYN="N">parasitology</QualifierName>
<QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName>
</MeshHeading>
</MeshHeadingList>
<KeywordList Owner="NOTNLM">
<Keyword MajorTopicYN="N">Antibody detection</Keyword>
<Keyword MajorTopicYN="N">Pig herd health</Keyword>
<Keyword MajorTopicYN="N">Pre-harvest food safety</Keyword>
<Keyword MajorTopicYN="N">Serological surveillance</Keyword>
</KeywordList>
</MedlineCitation>
<PubmedData>
<History>
<PubMedPubDate PubStatus="received">
<Year>2013</Year>
<Month>06</Month>
<Day>14</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="revised">
<Year>2013</Year>
<Month>12</Month>
<Day>10</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="accepted">
<Year>2013</Year>
<Month>12</Month>
<Day>11</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="entrez">
<Year>2014</Year>
<Month>1</Month>
<Day>14</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="pubmed">
<Year>2014</Year>
<Month>1</Month>
<Day>15</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="medline">
<Year>2014</Year>
<Month>10</Month>
<Day>16</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
</History>
<PublicationStatus>ppublish</PublicationStatus>
<ArticleIdList>
<ArticleId IdType="pubmed">24411983</ArticleId>
<ArticleId IdType="pii">S0167-5877(13)00388-7</ArticleId>
<ArticleId IdType="doi">10.1016/j.prevetmed.2013.12.006</ArticleId>
</ArticleIdList>
</PubmedData>
</pubmed>
<affiliations>
<list>
<country>
<li>Allemagne</li>
</country>
<region>
<li>Basse-Saxe</li>
<li>Berlin</li>
<li>District de Münster</li>
<li>Rhénanie-du-Nord-Westphalie</li>
</region>
<settlement>
<li>Berlin</li>
<li>Hanovre</li>
<li>Münster</li>
</settlement>
</list>
<tree>
<country name="Allemagne">
<region name="Basse-Saxe">
<name sortKey="Meemken, Diana" sort="Meemken, Diana" uniqKey="Meemken D" first="Diana" last="Meemken">Diana Meemken</name>
</region>
<name sortKey="Blaha, Thomas" sort="Blaha, Thomas" uniqKey="Blaha T" first="Thomas" last="Blaha">Thomas Blaha</name>
<name sortKey="Greiner, Matthias" sort="Greiner, Matthias" uniqKey="Greiner M" first="Matthias" last="Greiner">Matthias Greiner</name>
<name sortKey="Gundlach, Susanne" sort="Gundlach, Susanne" uniqKey="Gundlach S" first="Susanne" last="Gundlach">Susanne Gundlach</name>
<name sortKey="Klein, Guenter" sort="Klein, Guenter" uniqKey="Klein G" first="Guenter" last="Klein">Guenter Klein</name>
<name sortKey="Meermeier, Dieter" sort="Meermeier, Dieter" uniqKey="Meermeier D" first="Dieter" last="Meermeier">Dieter Meermeier</name>
<name sortKey="Mischok, Dieter" sort="Mischok, Dieter" uniqKey="Mischok D" first="Dieter" last="Mischok">Dieter Mischok</name>
<name sortKey="Tangemann, Anna Helene" sort="Tangemann, Anna Helene" uniqKey="Tangemann A" first="Anna Helene" last="Tangemann">Anna Helene Tangemann</name>
</country>
</tree>
</affiliations>
</record>

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