campylobacter spp., yersinia spp. and salmonella spp. as zoonotic

Transcription

Aus dem Institut für Tierzucht und Tierhaltung
der Agrar- und Ernährungswissenschaftlichen Fakultät
der Christian-Albrechts-Universität zu Kiel
CAMPYLOBACTER SPP., YERSINIA SPP. AND
SALMONELLA SPP. AS ZOONOTIC PATHOGENS IN
PIG PRODUCTION
Dissertation
zur Erlangung des Doktorgrades
der Agrar- und Ernährungswissenschaftlichen Fakultät
der Christian-Albrechts-Universität zu Kiel
vorgelegt von
Master of Science
TANJA WEHEBRINK
aus Rahden, Nordrhein-Westfalen
Dekan: Prof. Dr. Joachim Krieter
Erster Berichterstatter: Prof. Dr. Joachim Krieter
Zweiter Berichterstatter: Prof. Dr. Edgar Schallenberger
Tag der mündlichen Prüfung: 3. Mai 2007
Die Dissertation wurde mit dankenswerter finanzieller Unterstützung
der H. Wilhelm Schaumann Stiftung, dem Ministerium für Soziales, Gesundheit, Familie,
Jugend und Senioren des Landes Schleswig-Holstein und der Arbeitsgruppe
Lebensmittelqualität und -sicherheit (QUASI) der Agrar- und Ernährungswissenschaftlichen
Fakultät der Christian-Albrechts-Universität zu Kiel angefertigt
TABLE OF CONTENTS
GENERAL INTRODUCTION
………………………………………………………………………………………………… 1
CHAPTER ONE
Campylobacter spp. und Yersinia spp. beim Schwein: ein Überblick
………………………………………………………………………………………………… 3
CHAPTER TWO
Prevalence of Campylobacter spp. and Yersinia spp. in the pig production
………………………………………………………………………………………………. 19
CHAPTER THREE
Campylobacter spp.: Risk factor analysis in fattening farms
………………………………………………………………………………………………. 37
CHAPTER FOUR
Simulation study on the epidemiology of Salmonella spp. in the pork supply chain
………………………………………………………………………………………………. 53
GENERAL DISCUSSION
………………………………………………………………………………………………. 73
GENERAL SUMMARY
………………………………………………………………………………………………. 85
ZUSAMMENFASSUNG
………………………………………………………………………………………………. 89
GENERAL INTRODUCTION
Any disease and/or infection which is naturally "transmissible from vertebrate animals to
man" is classified as a zooanthroponosis according to EU-directive 92/117 (1992). To date,
over 200 zooanthroponoses have been described, involving all types of agents bacteria,
parasites and viruses (Krauss et al., 2004). The main part of zoonotic agents is represented by
bacterial pathogens. Every year millions of people become sick because of food-borne
zoonoses such as salmonellosis, campylobacteriosis or yersiniosis causing fever, diarrhoea,
abdominal pain, malaise and nausea. Other bacterial zoonoses are: anthrax, brucellosis, E.
coli-infections, leptospirosis, plague, shigellosis and tularaemia. The second group of
zooanthroponoses causing pathogens are parasites. In Latin America for example, 100 out of
100,000 inhabitants are estimated to suffer from cysticercosis (World Health Organisation,
2007). Other parasitical zoonoses are echinococcosis/hydatidosis, toxoplasmosis and
trematodosis (Heeschen, 2005). The third class of zoonotic pathogens are viruses. Rabies is a
disease of carnivores and bats mainly transmitted to humans by bites. Almost all persons
severely exposed to rabid animals will die if left untreated. An estimated number of 55,000
persons, mainly children, die of this disease in the world every year (World Health
Organisation, 2007). Other viral zoonoses are avian influenza, Crimean-Congo haemorrhagic
fever, ebola and Rift Valley fever (Krauss et al., 2004).
As bacterial pathogens are mainly responsible for zoonoses the following thesis concentrates
on this important group, especially gram-negative enterobacteriaceae. Zooanthroponoses even
though the estimated number of unreported cases is much higher than of the reported ones.
These zooanthroponoses affect hundred thousands of people especially in developing
countries, although most of them can be prevented.
The aim of the present thesis was to contribute to a better understanding of the bacterial
zoonotic pathogens Campylobacter spp., Yersinia spp. and Salmonella spp. causing disease in
humans and animals and to use this information to assess and manage the risk to animals and
humans.
CHAPTER ONE summarises several studies emphasising the importance of Campylobacter
spp. and Yersinia spp. as widespread pathogens in the pig production chain. First, the
taxonomy and the pathogen character are described, and second, prevalence in the pig
production is reported.
1
The objective of CHAPTER TWO was to gather further information about the prevalence of
Campylobacter spp. and Yersinia spp. at different stages of the pig production chain via
cultural isolation. Samples were taken from sows, suckling piglets, growing and finishing
pigs, carcasses, raw meat, forage and their environment (separating plate, feeding trough).
A further purpose in CHAPTER THREE was to increase the knowledge about the sources of
infection from Campylobacter spp. and their qualitative and quantitative importance in pig
production. Analysis of the data from questionnaires from the corresponding pig farms
provided first indications of factors which may influence the prevalence of Campylobacter
spp. in herds.
CHAPTER FOUR includes an exploration of possible measures that can be implemented in
farrowing and fattening units to control the introduction and reduce the prevalence of
Salmonella in finishing pigs. A stochastic state-transition simulation model was established to
gather further information about the influence of the risk factors in the different pig
production stages on the Salmonella spp. prevalence in fattening pigs. Furthermore, the
influence of preventive arrangements of the immunisation of sows, and additionally, of
pathogen-free purchased gilts on the Salmonella spp. prevalence in the farrowing and
fattening unit were determined.
References
EU-directive 92/117 EWG des Rates vom 17. Dezember 1992 über Maßnahmen zum Schutz
gegen bestimmte Zoonosen bzw. ihre Erreger bei Tieren und Erzeugnissen tierischen
Ursprungs zur Verhütung lebensmittelbedingter Infektionen und Vergiftungen.
Amtsblatt L62 vom 15.3.1993.
Heeschen, W.H., 2005. Zoonosen und lebensmittelbedingte Erkrankungen. Systematische
Übersicht der wichtigsten Bakterien, Viren und Parasiten. Behr’s Verlag, Hamburg.
Krauss, H., Weber, A., Appel, M., Enders, B., Graevenitz, v.A., Isenberg, H.D., Schiefer,
H.G., Slenczka, W., Zahner, H., 2004. Zoonosen. Von Tier zu Mensch übertragbare
Infektionskrankheiten. 3. Auflage, Deutscher Ärzte-Verlag GmbH, Köln.
WHO, 2007. World Health Organisation, http://www.who.int/en.
2
Chapter One
Campylobacter spp. und Yersinia spp. beim Schwein:
ein Überblick
TANJA WEHEBRINK1, NICOLE KEMPER1, ELISABETH GROSSE BEILAGE2
and JOACHIM KRIETER1
1
Institute of Animal Breeding and Husbandry
Christian-Albrechts-University
D-24118 Kiel, Germany
2
University of Veterinary Medicine Hannover
Fieldstation for Epidemiology
D-49456 Bakum, Germany
Accepted for publication in Züchtungskunde
3
1.
Einleitung
Campylobacter spp.- und Yersinia enterocolitica- Infektionen zählen neben den Salmonella
spp.- Infektionen zu den häufigsten gemeldeten Infektionskrankheiten des Menschen, die
durch Lebensmittel übertragbar sind und Darminfektionen hervorrufen können. Im Jahr 2006
führten laut Robert Koch-Institut (2007) Infektionen durch Campylobacter spp. zu 51.764
Erkrankungsfällen in Deutschland. Bei Yersinia spp. lag die Höhe der Erkrankungsfälle im
gleichem Jahr bei 5.135. Besondere Bedeutung kommt hier vor allem den thermophilen
Spezies Campylobacter (C.) jejuni und C. coli zu, welche am häufigsten von an Enteritis
erkrankten Personen isoliert wurden. Yersinia (Y.) enterocolitica ist neben Y. pestis und Y.
pseudotuberculosis eine der drei humanpathogenen Yersinia-Spezies. Hier ist das Bioserovar
4/O:3 von besonderer Bedeutung, da dieses die Hauptursache humaner Yersiniosen im
europäischen Raum ist.
Beide Erkrankungen sind vor allem Kleinkindererkrankungen, bei der Campylobacteriose ist
eine zweite Erkrankungshäufung im frühen Erwachsenenalter zu erkennen. Hauptsächlich
äußern sich die Erkrankungen mit Durchfällen, aber auch schwere oder klinisch inapparente
Verläufe sind zu beobachten. Ebenso sind Spätfolgen, wie beispielsweise das Erythema
nodosum (Neubauer et al., 2001a), möglich. Bei Campylobacter spp. ist die geringe
Infektionsdosis von 500-800 Keimen noch hervorzuheben (Black et al., 1988). Für beide
Keime besteht seit Inkrafttreten des Infektionsschutzgesetzes im Jahr 2001 Meldepflicht. Da
beide Infektionen beim Schwein in der Regel symptomlos verlaufen (Bätza, 1996) und somit
weder im Bestand noch auf dem Schlachthof bei der Schlachttier- und Fleischuntersuchung
erkannt werden, ist es möglich, dass diese Zooanthroponosenerreger in die Lebensmittelkette
gelangen.
Der vorliegende Artikel liefert eine Literaturzusammenfassung über diese zwei wichtigen
Zooanthroponosenerreger, verdeutlicht die Erregereigenschaften und liefert einen Überblick
über die Prävalenzen in der Schweineproduktion.
2.
Geschichte und Taxonomie
2.2
Campylobacter-Spezies
Der Kinderarzt Theodor Escherich beschrieb 1886 spiralig gewundene Bakterien, welche er
aus dem Darminhalt von Säuglingen mit Diarrhoe isoliert hatte. Zwei Jahre später gelang ihm
die Isolierung von ebenfalls spiralförmigen Darmbakterien von an Durchfall erkrankten
Katzen, welche er Vibrio felinus nannte (Escherich, 1886). Im Jahre 1919 wurden diese
4
Bakterien auch bei abortierten Rinderfeten nachgewiesen und als Vibrio fetus bezeichnet
(Smith und Taylor, 1919). Jones et al. (1931) fanden Vibrionen bei an Winterdysenterie
erkrankten Kälbern und nannten sie aufgrund ihrer Ähnlichkeit zu Vibrio fetus, aber dem
Vorhandensein von andere Antigeneigenschaften, Vibrio jejuni. Weitere mikroaerophile
Mikroorganismen wurden im Colon von dysenterischen Schweinen gefunden und wegen ihrer
Vibrionenähnlichkeit mit der Bezeichnung Vibrio coli versehen (Doyle, 1944). King fand
1957 zwei Gruppen von Vibrionen in Blutkulturen von Patienten, die an einer
hämorrhagischen Darmentzündung erkrankt waren. Die eine Gruppe war Vibrio fetus sehr
ähnlich, die andere Gruppe beschrieb er als „related Vibrios“. Sebald und Veron (1963)
stellten fest, dass sich die DNA dieser beiden Gruppen von der DNA der Gattung Vibrio im
Guanin- und Cytosingehalt unterschied. Aufgrund dieser Erkenntnis wurde dieser neuen
Spezies der Genusname Campylobacter gegeben, der aus dem Griechischen stammt und
„gebogener Stab“ bedeutet. Die ersten Isolierungen aus Stuhlproben von an Durchfall
erkrankten Patienten gelangen Anfang der siebziger Jahre (Butzler et al., 1973). Die
Entwicklung verbesserter Nachweisverfahren für Campylobacter spp. führte zunehmend zu
einer weltweiten Wahrnehmung insbesondere von C. coli und C. jejuni als bakterielle
Enteritiserreger beim Menschen (Kist, 2002).
2.3
Yersinia-Spezies
Im Jahre 1934 wurde die erste anerkannte Beschreibung von Yersinia enterocolitica in den
USA durch MCiver und Pike (1934) verfasst. Sie berichteten unter den Namen
Flavobacterium pseudomallei über einen kleinen gramnegativen Kokkobazillus, welcher aus
zwei Gesichtsabzessen einer Farmbewohnerin isoliert worden war. Sie hielten es aber für
wahrscheinlicher, es mit einer atypischen Form eines bereits bekannten Erregers zu tun zu
haben als mit einer neuen Spezies. Fünf Jahre später schenkten Schleifstein und Coleman
(1939) der Beschreibung von MCiver und Pike Beachtung, als sie einen Keim untersuchten,
der Ähnlichkeit mit Actinobacillus lignieresii und Pasteurella pseudotuberculosis hatte. Der
Keim wurde aus dem Darminhalt isoliert, deshalb schlugen sie den Name Bacterium
enterocoliticum vor. Der Gattungsname Yersinia wurde im Jahre 1944 durch Van Loghem zu
Ehren von Alexandre Yersin, welcher 1894 in Hongkong während einer Pestepidemie den
Erreger der Pest (ehemals Pasteurella pestis, heute Yersinia pestis) entdeckte, begründet. Im
Jahre 1964 wurde das Bacterium enterocoliticum in Y. enterocolitica umbenannt und in die
Familie der Enterobacteriaceae eingegliedert (Fredriksen, 1964). Im Jahr 1980 wurden vier
Yersinia-Spezies etabliert: Y. enterocolitica, Y. intermedia, Y. frederiksenii und Y. kristensinii
5
(Brenner et al., 1980). Um eine Einteilung hinsichtlich Pathogenität und Epidemiologie der Y.
enterocolitica-Isolate zu erhalten, wurde eine Zuordnung zu Biovaren geschaffen. Wauters et
al. (1987) nahmen, aufgrund unterschiedlicher Substratverwertung, die Einteilung in sechs
Biovare vor: 1A, 1B, sowie Biovar 2 bis 5. Biovar 1A fasst den überwiegenden Teil der bis
dahin als apathogenen eingeschätzten Isolate zusammen. Die Biovare 2, 3, 4 und 5 enthalten
die pathogenen europäischen, die Biovare 1B die pathogenen in Amerika isolierten Stämme.
Die tierpathogenen Stämme gehören stets zu den Biotypen 3 oder 5 (Aleksic und Bockemühl,
1990). Zusätzlich zur Einteilung in Biovare wird in der Routinediagnostik eine Einteilung in
Serovare vorgenommen. Die Serotypisierung basiert überwiegend auf O-Antigenen
(Oberflächenantigen), seltener auf den H- (Geißel-) oder F- (Fimbrien) Antigen. Für YersiniaSpezies wurden bis heute 60 O- Gruppen gefunden, wovon 28 auf Y. enterocolitica entfallen
(Aleksic und Bockemühl, 1990). Während bestimmte O- Antigene bei verschiedenen Spezies
vorkommen, sind die H- Antigene Spezies-spezifisch und können daher auch zur direkten
Identifizierung der Yersinia - Arten herangezogen werden. Bislang wurden 18 H- Faktoren
bei Y. enterocolitica definiert. Hier sind bestimmte Kombinationen von H- Antigenfaktoren
signifikant für pathogene Serotypen und können bei der Unterscheidung pathogener und
apathogener Stämme hilfreich sein. Nach Befunden von Aleksic und Bockemühl (1990) sind
die pathogenen Serotypen O:3, O:9 und O:5,27 von Y. enterocolitica stets mit den HAntigenen a,b; a,b,c; a,b,c,v; a,c; c oder b,c kombiniert. Der H- Antigenkomplex H: b,e,f,i
kommt hingegen bei den fast ausschließlich in den USA auftretenden pathogenen Serovaren
O:8; O:4,32; O:18; O:20 und O:21 von Y. enterocolitica vor (Aleksic und Bockemühl, 1990).
3.
Spezifische Eigenschaften
3.1
Campylobacter-Spezies
Nach Garrity et al. (2002) untergliedert sich die Familie der Campylobacteriaceae in Gattung
I Campylobacter, Gattung II Arcobacter und Gattung III Sulfurospirillum. Zur Zeit sind 16
Spezies und 6 Subspezies von Campylobacter spp. anerkannt (On et al., 2001). Die
humanpathogenen Campylobacter können in zwei Hauptgruppen eingeteilt werden: in die
Durchfallerreger wie C. jejuni, C. coli, C. lari, C. upsaliensis und in die Erreger
extraintestinaler Infektionen wie C. fetus (Hu und Kopecko, 2003).
Bakterien der Gattung Campylobacter sind gramnegative, schlanke, kommaförmige,
sporenlose Stäbchenbakterien, die ca. 0,2-0,5 µm breit und 0,5-5 µm lang sind (Rolle und
Mayr, 2002). Sie können eine oder mehrere helikale Windungen besitzen und maximal bis zu
6
acht µm Länge erreichen. Die Bildung kurzer Ketten ist ebenfalls möglich. Sie erscheinen
auch s-förmig und in älteren Kolonien können kokkoide Zellen auftreten. Charakteristisch ist
die korkenzieherartige Bewegung, die durch die polare monotriche Begeißelung entsteht.
Campylobacter spp. haben einen respiratorischen Stoffwechsel, verwerten Kohlenhydrate
weder fermentativ noch oxidativ (d.h. sie sind „asaccharolytisch“) und ernähren sich von
Zwischenprodukten aus dem Tricarbonsäurezyklus und von Aminosäuren (Anonymus, 1994).
Eisen wird ebenfalls von Campylobacter spp. als essentieller Nährstoff benötigt (PARK, 2002).
Die Vermehrung findet in Temperaturbereichen von 32°C bis 46°C bei mikroaerophilem
Klima mit ca. 5% O2, 10% CO2 und 85% N2 statt (Hunt et al., 2001). Vermutlich ist die
Mikroaerophilie auch ein Resultat der Adaption von Campylobacter spp. an die
atmosphärische Zustände im Darm von warmblütigen Tieren und Vögeln (Park, 2002). Die
minimale Wachstumstemperatur liegt bei thermophilen Campylobacter spp. bei 31°C bis
32°C. Unter 30°C sind die Keime nicht mehr wachstumsfähig. Somit ist eine Multiplikation
während der Handhabung oder Lagerung von Lebensmitteln bei Zimmertemperatur
ausgeschlossen (Jacobs-Reitsma, 2000). Die Ursache für die fehlende Vermehrung außerhalb
des Tierkörpers und unterhalb von 30°C kann möglicherweise an der fehlenden Produktion
von Kälteschockproteinen liegen (Parkhill et al., 2000). In kontaminierten Substraten haben
thermophile Campylobacter spp. bei niedrigen Temperaturen eine höhere Überlebensfähigkeit
als bei höheren Temperaturen. Während sie bei 4°C mehrere Wochen lebensfähig sind,
sterben sie bei Temperaturen von 55°C ab (Wundt und Kasper, 1982).
Die Keime sind sehr empfindlich gegenüber Trockenheit. Sie überleben nur kurze Zeit in
trockener Atmosphäre. Bei aW-Werten kleiner als 0,97 sterben die Keime schnell ab.
Lebensfähige Keime können nur von feuchten Oberflächen isoliert werden. Die Kombination
aus Temperatur und Luftfeuchtigkeit scheint eine essentielle Rolle für das Überleben der
Keime zu spielen (Doyle und Roman, 1982).
Der pH-Wert des umgebenden Milieus beeinflusst das Überleben von Campylobacter spp. in
Abhängigkeit von der Zeit und der Temperatur. Das pH-Optimum liegt bei Werten zwischen
6,5 und 7,5, das Maximum bei pH 9. Werte von über pH 9 und unter pH 4 führen zum
raschen Absterben, besonders bei höheren Temperaturen (Gill und Harris, 1983).
Campylobacter spp. lassen sich leicht durch ultraviolette Strahlen und Röntgenstrahlen
abtöten. Gegen UV-Strahlen ist C. jejuni empfindlicher als Escherichia coli und Y.
enterocolitica (Butler et al., 1987).
Thermophile Campylobacter spp. können unter schwierigen Umgebungsbedingungen einen
besonderen Zustand einnehmen, in dem sie lebensfähig aber nicht kultivierbar sind. Dieses
7
viable-but-nonculturable-Stadium (VBNC) ist auch bei anderen humanpathogenen Erregern
wie z.B. Escherichia coli, Salmonella enteritidis, Vibrio cholerae und Legionella
pneumophila bekannt (Tholozan et al., 1999). Einige Autoren beschreiben diese Form als eine
Art Schutzzustand, bei dem sich die Keime in einem Ruhestadium befinden und später, unter
besseren Bedingungen, wieder wachsen können. Andere Verfasser bezeichnen dieses Stadium
als eine degenerative Form des beginnenden Zelltodes. Die Bakterien bleiben in diesem
Zustand aber infektionsfähig.
Bei der Identifizierung der unterschiedlichen Campylobacter-Spezies wird zwischen
genotypischen und phänotypischen Methoden unterschieden (Nachamkin et al., 2000). Bei
den phänotypischen Methoden handelt es sich um relativ einfache, oft angewandte Tests, die
auf dem Nachweis von biochemischen Reaktionen, verschiedenen Wachstumsparametern,
Resistenzprofilen gegenüber Antibiotika und serologischen Verfahren beruhen. Jedoch
verhalten sich Campylobacter spp. biochemisch inert, was die Differenzierung und
Unterscheidung der Spezies erschwert. Die einzige Reaktion zur biochemischen Reaktion der
beiden Spezies C. jejuni und C. coli ist die Hippurathydrolyse. Genotypische Methoden
basieren auf dem Nachweis stabiler chromosonaler Unterschiede, die reproduzierbar und stark
diskriminierend sind. Vor allem für die Typisierung von Stämmen und für die
epidemiologische Fragestellung eignen sich diese Methoden gut.
3.2
Yersinia-Spezies
Yersinia ist eine Gattung innerhalb der Familie der Enterobacteriaceae und umfasst derzeit
elf verschiedene Spezies. Yersinia pestis, der Erreger des „schwarzen Todes", einer Infektion,
die im Mittelalter epidemisch auftrat, ist heute aus unseren Breitengraden verschwunden
(Kayser et al., 1993), während Y. pseudotuberculosis und vor allem Y. enterocolitica als
Erreger der menschlichen Yersiniose in den letzten Jahren zunehmend an Bedeutung
gewonnen hat (Bottone, 1999). Yersinia enterocolitica ist jedoch nicht ausschließlich als
humanpathogener Erreger einzustufen. Neben pathogenen Vertretern dieser Spezies existieren
noch eine Reihe von apathogenen Umweltisolaten, die diagnostisch abgegrenzt werden
müssen (Neubauer et al., 2001b).
Yersinia enterocolitica ist ein gramnegatives, fakultativ anaerobes, pleomorphes, peritrich
begeißeltes Stäbchenbakterium, das eine Länge von 1,0-5,0 µm erreicht. Yersinien sind
oxidasenegativ, katalasepositiv und reduzieren Nitrat und Nitrit (Aleksic und Bockemühl,
1990). Sie kommen ubiquitär vor und bilden keine Kapseln oder Sporen (Knapp, 1988).
8
Bei unter 28°C sind sie beweglich, darüber jedoch nicht, da die Geißeln in der Regel nur bei
Temperaturen unter 30°C gebildet werden (Rolle und Mayr, 2002). Yersinia enterocolitica ist
psychrotrop, das bedeutet, dass eine Vermehrung bei Kühlungstemperaturen bis 0°C möglich
ist. Die optimale Wachstumstemperatur beträgt +30°C, wobei die Obergrenze der
Vermehrungsfähigkeit bei +43°C liegt.
Zur Bestimmung des Serotys sind zwischenzeitlich kommerzielle Test erhältlich, die auf einer
Agglutinationsreaktion beruhen. In der Diagnostik des weltweit am häufigsten beim
Menschen isolierten Serovars Y. enterocolitica Serotyp O:3 ist eine biochemische
Charakterisierung zusätzlich zur Serotypisierung unumgänglich, um eine sichere Aussage
über die klinische Relevanz eines Isolates (insbesondere bei klinischem Material und
Umweltproben) treffen zu können, da dieses Serovar auch bei anderen verwandten YersinienSpezies oder Stämme des Biotyps 1A anzutreffen ist (Hoofar und Holmvig, 1999). Die
bakteriologische Diagnostik pathogener Y. enterocolitica-Isolate ist bis heute mit hohem
zeitlichen Aufwand verbunden, und mögliche Diagnosen können aufgrund mangelnder
Spezifität und Sensitivität der zur Zeit verfügbaren Testsysteme immer nur unter Vorbehalt
gestellt werden oder bedürfen in ihrer Interpretation eines hohen Maßes an Expertise. Bis
heute ist trotz der hohen zoonotischen Bedeutung des Erregers keine einheitliche Methode
zum
bakteriologischen
Nachweis
pathogener
Y.
enterocolitica-Isolate
beschrieben.
Erschwerend kommt hinzu, dass allein die Vielzahl der bis heute beschriebenen
Untersuchungen zu widersprüchlichen Ergebnissen führt (Arnold, 2002).
4.
Prävalenzen und epidemiologische Aspekte in der Schweineproduktion
4.1
Campylobacter spp. und Yersinia spp. beim Schwein
Thermophile Campylobacter spp. scheinen keine Bedeutung für Erkrankungen bei Schweinen
zu haben (Altekruse und Swerdlow, 2002). Der Keim ist wahrscheinlich der normalen
Darmflora zuzurechnen (Görgen et al., 1983). Beim Schwein ist C. coli die verbreitetste
Spezies mit Nachweisraten von bis zu 100%. Einzelne Untersuchungen zeigen aber auch, dass
C. jejuni in bestimmten Beständen sehr häufig isoliert werden kann (Young et al., 2000).
Viele Untersuchungen belegen, dass sich Campylobacter spp. häufig aus dem Kot gesunder
Schweine isolieren lassen. Zu diesem Ergebnis kam auch Gaull (2002), der bei der Beprobung
von Mast- und Schlachtschweinen Nachweisraten zwischen 70% und 93% ermittelten.
Ähnliche Prävalenzen stellte auch Weijtens (1996) in einer Studie fest, in der er
Mastschweine im Verlauf einer Mastperiode auf Campylobacter spp. untersuchte. Dabei
9
wurde bei 98% der elf Wochen alten Schweine Campylobacter spp. aus dem Kot isoliert,
wobei ein Rückgang auf 85% zum Zeitpunkt der Schlachtung zu verzeichnen war. Die
Ursache für den Rückgang liegt möglicherweise in der stabileren Darmflora älterer Tiere, die
das Wachstum von Campylobacter spp. behindert. Aber auch ein Futterwechsel während der
Mast könnte als Erklärung hierfür angeführt werden. Es konnte beobachtet werden, dass
einzelne
Tiere
an
aufeinander
folgenden
Beprobungsterminen
unterschiedliche
Untersuchungsergebnisse aufwiesen. Dass Schweine während der Mast eine CampylobacterFreiheit erlangen und sich anschließend reinfizieren, scheint jedoch unwahrscheinlich.
Vielmehr ist von einer intermittierenden Ausscheidung auszugehen, die auf einer heterogenen
Verteilung des Erregers infolge chemischer Anziehungskräfte beruht. Da sowohl
Untersuchungen von Weijtens (1996) und Gaull (2002) gezeigt haben, dass Schweine schon
zu Beginn der Mastperiode Campylobacter spp. im Kot aufweisen, ist der primäre
Infektionszeitpunkt bereits im Ferkelalter zu suchen. Sauen in Ferkelerzeugerbetrieben weisen
häufig hohe Infektionsraten von bis zu 100% auf und können durch erregerhaltige
Ausscheidung einen massiven Infektionsdruck in ihrer Umwelt aufbauen (Weijtens, 1996).
Während die Ferkel zum Zeitpunkt der Geburt noch Campylobacter-frei sind, steigen die
Prävalenzen schon in den ersten Lebenswochen erheblich an. Wenn auch die Aufstallung der
Ferkel zunächst einen Einfluss auf die Höhe der Prävalenz in den ersten Lebenswochen zu
haben scheint (Ferkel in Ställen mit Fußbodenheizung weisen geringere Belastungen auf),
relativieren sich die Unterschiede am Ende der Aufzuchtphase und erreichen Nachweisraten
von 90% und mehr (Gaull, 2002).
Das Schwein ist seit langem als Reservoir von humanpathogenen Yersinia enterocolitica der
Serovare O.3, O:9 und O:5,27 bekannt (Johannessen et al., 2000). Beim Schwein selbst tritt
die Yersiniose überwiegend bei Jungtieren klinisch apparent auf. Ältere Tiere gelten als
asymptomatische Träger des Keims (Neubauer et al., 2001b). Serologische Untersuchungen
in Norwegen zeigen, dass 86% der untersuchten reinen Mastbestände positiv waren,
wohingegen die Herdenprävalenz bei geschlossenem System mit 53,1% erheblich niedriger
lag (Skjerve et al., 1998). Die Yersinia spp.-Infektion wird durch Zukauf und anschließender
fäkal-orale Kontamination sowie durch infiziertes Sperma oder Abortmaterial nach
intrauteriner Infektion verbreitet. Nach Ansicht der Autoren ist das Transportfahrzeug eine
wichtige Kontaminationsquelle. Auch der Einsatz von Stroheinstreu birgt nach ihrer
Auffassung ein erhöhtes Risiko. Dagegen konnte nach ihrer Auswertung die Herdenprävalenz
durch den Einsatz einer Unterdruckventilation sowie einer manuellen Fütterung gesenkt
werden. Skjerve et al. (1998) kamen zu dem Schluss, dass die Risikominimierung für eine Y.
10
enterocolitica-Infektion durch die strikte Trennung von infizierten und nicht-infizierten
Beständen zu erreichen ist. Bottone (1997) isolierte von klinisch gesunden Schweinen
pathogene Y. enterocolitica. Dabei lag die Isolationsrate aus dem Rachen weit höher als jene
aus dem Kot. Im Jahr 2000 wurden in Süddeutschland an einem Schlachthof 50
Schlachtschweine untersucht, hierbei konnten in 60% der Tonsillen und 10% der Kotproben
Y. enterocolitica 4/O:3 nachgewiesen werden (Fredriksson-Ahomaa et al., 2000). Weitere
Daten, die aus Deutschland stammten, wurden 2004 erfasst. Dabei waren 45,5% der
untersuchten Schweinemastbestände in Bayern serologisch positiv (Hensel et al., 2004).
Verlaufsuntersuchungen vom Ferkel bis zum adulten Tier liegen bislang noch nicht vor, aber
es ist bekannt, dass bei Sauen viel seltener Y. enterocolitica aus den Tonsillen zu isolieren ist.
So untersuchten Korte et al. (2004) Tonsillen von Mastschweinen und Sauen von sieben
verschiedenen Schlachthöfen. Während bei den Mastschweinen 56% positiv waren, konnte
bei den Sauenproben nur bei 14% der Erreger nachgewiesen werden.
4.2
Campylobacter spp. und Yersinia spp. im Schweinefleisch
In Lebensmittelproben wurden in Deutschland im Jahr 2001 nach Mitteilung von elf
Bundesländern
in
einer
von
insgesamt
159
untersuchten
Schweinefleischproben
Campylobacter spp. nachgewiesen. Von 16 Anlassproben wies keine ein positives Ergebnis
auf (Hartung, 2002). In den USA untersuchten Zhao et al. (2001) Fleischprodukte aus 59
Fleischtheken verschiedener Supermarktketten auf das Vorkommen von Campylobacter spp..
Dabei war in 1,7% der Proben vom Schwein der Erreger nachweisbar. Oosterom et al. (1985)
gehen davon aus, dass positive Campylobacter-Nachweise am Schlachtkörper weniger durch
den ursprünglichen Keimgehalt im Darm der Tiere hervorgerufen werden, sondern vielmehr
Kreuzkontaminationen durch Oberflächen und Arbeitsgeräte in der Schlachthalle darstellen.
Deutlich stärker als das Fleisch dieser Tierart sind ihre Lebern belastet. So konnten Kramer et
al. (2000) in 71,1% der Schweinelebern thermophile Campylobacter nachweisen. Als Ursache
für diese hohe Prävalenz vermuteten sie eine Kreuzkontamination, da die Lebern zu mehreren
Kilogramm in jeweils einem Paket unter Luftabschluss verpackt wurden.
Die Nachweisrate von Y. enterocolitica in rohem Schweinefleisch ist mit Ausnahme von
Schweinezungen und –innereien gering (Beer, 1995), die Prävalenz im Hackfleisch, für
welches in manchen Regionen Kopffleisch und Tonsillen verwendet werden, ist jedoch hoch
(Tauxe et al. 1987). Über das Vorkommen von Y. enterocolitica in hitzebehandelten
Schweinefleischprodukten liegen nur wenige Studien vor (Hank, 2003). Bisher wurden keine
pathogenen Stämme aus hitzebehandelten Produkten isoliert. Dennoch wurden apathogene Y.
11
enterocolitica Stämme nachgewiesen. Dies zeigt, dass bei mangelhafter Hygiene eine
Kreuzkontamination von rohen zu hitzebehandelten Produkten möglich ist.
5.
Schlussfolgerung
Wie die gezeigten Studien verdeutlichen, sind Campylobacter spp. und Yersinia spp. Keime,
die in Schweinebeständen in Europa weit verbreitet sind und daher ein Risiko für die
Gesundheit des Menschen darstellen. Daher sind weitere infektionsepidemiologische Studien
notwendig, um das vom Schwein ausgehende Gefahrenpotential für die menschliche
Campylobacter spp.- und Yersinia spp. -Infektion abschätzen zu können. Hierbei sind
Langzeitstudien erforderlich, um offene Fragen bezüglich der Epidemiologie und der
Eintragsquellen beider Erreger zu klären.
Auch
fehlen
Informationen über die
Erregerprävalenz in der gesamten Produktionskette beim Schwein. Diese sind notwendig, um
festzustellen, auf welcher Produktionsstufe eine Erregerbekämpfung sinnvoll ist, um den
Eintrag zu minimieren. Es sollte geklärt werden ob der Einsatz einer Impfung zur
Erregerreduktion auf Bestandsebene praktikabel ist, oder eine Änderung der Schlachttechnik
einen positiven Einfluss hat. Da Campylobacter-Keime in der Lage sind, den VBNC-Status
einzunehmen,
kann
die
Frage
des
Überlebens
des
Erregers
auf
der
Schlachttierkörperoberfläche nicht völlig geklärt werden. Über die Mechanismen und
Bedeutung des VBNC-Status bei Campylobacter spp. sollten weitere Untersuchungen
vorgenommen werden. Zur Zeit gibt es weder für Campylobacter spp. noch für Yersinia spp.
einen „Gold Standard“ in der Analysetechnik. Dies erschwert die Vergleichbarkeit der
verschiedenen Studien untereinander. Somit ist zusätzlich die Entwicklung für eine sichere,
schnelle, einfach durchführbare und kostengünstige Erregerdiagnostik unabdingbar.
Zusammenfassung
Die vorliegende Arbeit diente als Literaturübersicht über Campylobacter spp. und Yersinia
spp. in der Schweineproduktionskette. Es wurde zum einen die Systematik und die
Erregereigenschaften dieser zwei weltweit bedeutenden Zooanthroponoserreger dargestellt.
Zum anderen wurde über die herrschende Prävalenzen in der Produktionskette beim Schwein
berichtet. Es wird deutlich, dass Schweine häufig Träger humanpathogener Campylobacter
spp. und Yersinia spp. sind und eine Kontamination ihres Fleisches während des
Schlachtprozesses möglich ist. Allerdings sind humanpathogene Campylobacter spp. und
Yersinien spp. relativ selten im Fleisch nachweisbar. Eine größere Gefahr stellen Innereien
12
dar. Um Schweinefleisch noch sicherer zu machen, sollte in Zukunft versucht werden, die
Epidemiologie
des
Erregers
genauer
aufzuklären,
um
somit
die
Ursache
der
Erregerausbreitung zu erkennen und geeignete Gegenmaßnahmen ergreifen zu können.
Schlüsselwörter: Campylobacter spp., Yersinia spp., Schwein, Literaturübersicht
Abstract
This review summarises several studies emphasising the importance of Campylobacter spp.
and Yersinia spp. in the pig production chain as widespread pathogens. First, taxonomy and
pathogen character of these world-wide important pathogens were described, and second,
prevalence in the pig production was reported. Obviously, pigs are often carriers of
Campylobacter spp. and Yersinia spp. causing infections in humans. Contamination during
the slaughtering process is possible. However, pathogenic Campylobacter spp. and Yersinia
spp. are comparatively infrequently isolated from meat. A bigger health risk is represented by
entrails. Concluding, to increase pork safety, further epidemiological studies are urgently
needed to determine the origin of pathogens and to take counteractive measures.
keywords: Campylobacter spp., Yersinia spp., pigs, review article
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18
CHAPTER TWO
Prevalence of Campylobacter spp. and Yersinia spp. in the
pig production
JOACHIM KRIETER1
1
2
Submitted for publication in Berliner und Münchner Tierärztliche Wochenschrift
19
Abstract
The aim of this study was to determine the prevalence of Campylobacter spp. and Yersinia
spp. in a total of 1,040 faecal samples taken from animals at different ages from four
farrowing and twelve fattening herds. In the farrowing unit, faeces were collected from 68
sows (faecal samples) and 256 suckling piglets (rectal swab samples). Further samples were
collected from 362 growing and 354 finishing pigs (rectal swab samples). Additionally, 56
feed and environmental samples were collected.
During the slaughtering process, 122 pigs and their carcasses respectively, were sampled three
times. First, rectal samples were taken with swabs during the lairage. Second, the samples
were taken from the carcass before entering the chilling room. The same method was repeated
in the chilling room twelve hours after starting the chilling.
Finally, 86 raw meat samples were taken from 34 retail stores.
Campylobacter spp. were isolated in sows (33.8%), piglets (80.9%), growing (89.2%) and
finishing (64.7%) pigs. Yersinia spp. were detected in growing (15.2%) and finishing (13.3%)
pigs only. During lairage, Campylobacter spp. were identified from pig faeces from all farms
whereas Yersinia spp. were detected in pigs from just two herds. After twelve hours of
chilling neither Campylobacter spp. nor Yersinia spp. were detected. In raw meat samples,
Campylobacter spp. were isolated from one liver sample and Yersinia enterocolitica from two
meat samples (mince and cutlet). Common slaughter techniques and hygiene procedures may
be effective tools to reduce the risk of contamination and recontamination of meat products
since Campylobacter spp. and Yersinia spp. were found only sporadically in raw meat
samples.
keywords: Campylobacter spp., Yersinia spp., cultural isolation, pig production chain,
zoonotic pathogens
20
1.
Introduction
Campylobacter (C.) spp. are among the most common bacterial causes of enteric diseases
worldwide. Members of the genus Campylobacter colonize the gastrointestinal tract of a
broad range of animals as commensals. In contrast, they are associated with disease in
humans. In Germany, the Robert Koch-Institute registered 61,823 cases of people suffering
from campylobacteriosis in 2005 (Robert Koch-Institut, 2006). Out of the 16 species within
the genus Campylobacter, the thermophilic species C. jejuni and C. coli are of special
importance as zoonotic agents with regard to human health. Infections with C. spp. in humans
are mainly related to consumption of contaminated food, especially chicken products.
Another important source of food-borne infections is raw or insufficiently cooked pork.
Furthermore, surface water used for drinking purposes can serve as a source of infection.
Besides Salmonella spp. and Campylobacter spp., Yersinia (Y.) spp. is another important
zoonotic pathogen from the list of human diseases (Aleksic and Bockemühl, 1990) with 5,600
registered infections in Germany in 2005 (Robert Koch-Institut, 2006). Together with Y.
pestis and Y. pseudotuberculosis, Y. enterocolitica represents pathogenic Yersinia species
with a certain risk to human health. Most cases of yersiniosis in Europe are related to
bioserovar 4/O:3 Y. enterocolitica is thought to be a significant food-borne pathogen,
although pathogenic isolates have been isolated from food infrequently, except from edible
pig offal (De Boer, 1995). In case-control studies, a correlation has been demonstrated
between the consumption of raw or undercooked pork and yersiniosis (Satterthwaite et al.,
1999). The main infection source for Y. enterocolitica bioserovar 4/O:3 is raw pig meat, for
pigs serving as natural carriers of this bioserovar (Fredriksson-Ahomaa et al., 2001).
Both infections are infant diseases with a clear infection peak in children up to two years and
a second incidence peak for campylobacteriosis in early adulthood. Diarrhoea is symptomatic
for both campylobacteriosis and yersiniosis, but severe or clinically unapparent courses of
disease are possible as well. In contrast to its importance as a human pathogen, the
understanding of the pathomechanisms of Campylobacter spp.-associated diseases is still
relatively poor (Vlient and Ketley, 2001). In the same way, this applies for the epidemiology
of Y. enterocolitica infections, as it is complex and poorly understood (Fredriksson-Ahomaa
and Korkeala, 2003).
The objective of this study was to gather further information about the prevalence of
Campylobacter spp. and Yersinia spp. at different stages of the pig production chain via
cultural isolation. Samples were taken from sows, suckling piglets, growing and finishing
pigs, carcasses, raw meat, forage and their environment (separating plate, feeding trough).
21
2.
Materials and Methods
2.1
Materials
Table 1 shows the number of herds at every stage of the production chain and the number of
samples taken.
Table 1
Study design
production stage
number
farrowing units
fattening units
slaughterhouse
retail
4 herds
12 herds
4 herds
34 retail stores
of samples
sows
68
-
-
-
256
-
-
-
pigs
-
716
366
-
forage
8
26
-
-
10
12
6
-
-
-
-
86
piglets
environment
raw meat samples
2.1.1 Farrowing and fattening units
During the period from November 2004 till June 2005 data were collected from four
farrowing and twelve fattening herds. The ZNVG (Vermarktungsgemeinschaft für Zucht- und
Nutzvieh, Neumünster) supplied a list of several farms. The herds for the present study were
selected based on the herd size and the relationships between farrowing and fattening. Due to
practical limitations, the study design was arranged in the following way: The number of
sows in the farrowing herds was between 150 to 650 sows and the fattening herds had
fattening places for 350 to 2000 animals. In three cases, a supply relationship between
farrowing and fattening unit existed. In all herds, pigs were kept under conventional
conditions.
The sampling size for each herd was calculated on the herd size and expected prevalence
according to the formula from Noordhuizen et al. (1997). The expected prevalence of
Campylobacter spp. and Yersinia spp., taken from literature, was appointed by the sows and
22
fattening pigs with 80% and 60% respectively and in the retails with 0.2% or rather 2%. The
absolute accuracy was 14% and the probability of error was 5%.
In the farrowing unit, faeces were collected in the farrowing house from 68 sows (faecal
samples) and 256 suckling piglets (rectal swab samples). In three herds, 17 sows and
additionally 85 or 86 suckling piglets (five or six piglets per litter) per herd were sampled and
in one herd only 17 sows. The selection of piglets was random and the time of sampling the
piglets was before weaning. Every pig was given a numbered ear tag enabling individual
identification at all times.
In the fattening unit, samples (rectal swab samples) were collected from 362 growing and 354
finishing pigs. In twelve herds, between 29 and 31 animals were sampled per herd. Eight pigs
died during the fattening period. The observation of 91 pigs from the farrowing unit could be
continued over the whole fattening period.
Additionally, 56 environmental and feed samples were collected in both production stages.
The environmental samples were taken from the separating plate and the feeding trough. Feed
samples consisted of forage for piglets, for sows in early and late pregnancy, and for pigs at
the beginning or end of fattening, respectively.
2.1.2 Slaughterhouse
All investigations concerning slaughter pigs and carcasses were carried out at a commercial
abattoir. The slaughterhouse was visited four times for samplings in the period from April
until June 2005. Four herds, sampled at different times, were the origin of the pigs
investigated at the slaughterhouse. Altogether, 122 pigs were sampled three times during the
slaughtering process. First, rectal samples were taken with swabs during the lairage. Second,
for the carcass surface, swabs moistened with a 0.9% NaCl dilution were used to sample an at
least 100cm2 large sampling field on the belly by rubbing with the necessary compression.
The samples were taken from the carcass before entering the chilling room. Third, the same
method was repeated in the chilling room twelve hours after beginning the chilling process.
During the slaughter process environmental samples were taken from diverse equipment
(knives, saws etc.).
Twenty-nine out of the 122 pigs at slaughterhouse level had also been sampled as piglets and
as fatting pigs representing a complete sampling passage at every step of the production
chain.
23
2.1.3 Retail
From June till July 2005, 86 raw meat samples were taken from 34 retail stores in two
different towns. In 13 butcher’s shops, twelve mince 13 escalope and two liver samples were
bought. In 21 discount shops, the sample material composed on the one hand of 16 mince, 19
escalope, one liver and one kidney portion from the self-service counter, and on the other
hand of eleven mince and eleven escalope samples from the sales counter.
2.2
Methods
After collection, samples were stored at 4°C and taken to the laboratory (Zentrale Einrichtung
Medizinaluntersuchungsamt und Krankenhaushygiene, Hygiene-Institut, Kiel) within four
hours and processed directly after arrival. Cultural methods were used to test all samples for
Campylobacter spp. and Yersinia spp., including differentiation of subspecies.
2.2.1 Detection of Campylobacter spp.
To isolate Campylobacter species, 1g of faeces or the swab sample was inoculated in 9ml
Preston broth (Oxoid). After incubation for 24 hours in a microaerophilic atmosphere (5%
oxygen, 10% carbon dioxide, 3% hydrogen and 82% nitrogen) at 37°C, a loop of the enriched
suspension was plated on Preston agar (Oxoid) and incubated for 48 hours under the abovementioned microaerobic conditions at 37°C. Campylobacter-like colonies were analysed by
Gram staining and catalase and oxidase tests (Hippurathydrolysis: ISO 10272, 1995,
modified), and biochemical reactions were assessed (ApiCampy; bioMerieux).
2.2.2 Detection of Yersinia spp.
Cultural isolation of Yersinia spp. was performed by adding 1g of faeces or the swab sample
to 9ml of Gram-negative broth (Becton & Dickinson) and incubating for 48 hours at 21°C.
One loop of broth was then plated on Yersinia-selective agar (Difco, CIN-Agar; CIN =
Cefsulodin-Irgasan-Novobiocin) and incubated for another 48 hours at 21°C. Colonies with
the typical bull’s eye appearance were subcultured on blood agar and Gram-stained and
biochemical tests were subsequently carried out by using API 20E (bioMerieux). Serum
agglutination was performed with isolates identified as Y. enterocolitica to detect serovars
O:3 and O:9 (ISO 10273, 1994, modified).
24
2.2.3 Statistical evaluation
Calculation of the animal prevalence and the 95% confidence intervals within the production
stage was performed with the PROC SURVEYMEANS procedure from the software package
SAS® (2002).
3.
Results
3.1
Farrowing unit
In three of the four herds at the farrowing level, Campylobacter spp. was isolated from the
sow samples. Overall, Campylobacter spp. (total) were isolated in 33.8% (n = 23) of the sows
and in 80.9% (n = 207) of the piglets (Table 2). In six cases (2.3%), both pathogens, C. coli
and C. jejuni, were simultaneously isolated from the piglet samples and one sow (1.5%) was
infected with both subspecies too. No Yersinia spp. were detected in any of these samples in
the farrowing unit.
Table 2
Prevalence of Campylobacter spp. and Yersinia spp. in sows and suckling piglets
sows (n = 68)
Campylobacter coli
Campylobacter jejuni
Campylobacter total
2
Yersinia spp.
1
95% Confidence Interval
suckling piglets (n = 256)
%
95% C.I.1
%
30.9
19.6-42.1
71.1
65.5-76.7
4.4
0-9.4
12.1
8.1-16.1
33.8
22.3-45.4
80.9
76.0-85.7
0
2
0
95% C.I.
-
Campylobacter total = C. coli and/or C. jejuni
Regarding the risks of vertical infection, Figure 1 points out that an infected sow does not
necessarily lead to infected piglets or that an uninfected sow automatically means a pathogenfree piglet. For example, in herd ‘3’ sows (n = 17) were free from Campylobacter spp. and
Yersinia spp., but in the piglets (n = 85) C. coli was isolated in 21.2% (n = 18) and C. jejuni in
36.5% (n = 31) of cases.
25
C. coli
prevalence (%)
100
C. jejuni
C. total¹
80
60
40
20
0
sow
piglet
sow
herd 1
piglet
sow
herd 2
piglet
herd 3
sow
herd 4
farrowing unit
1
C. total = C. coli and/or C. jejuni
Figure 1
Prevalence of the different pathogens in farrowing unit section (total sampled: 17 sows and 85
piglets per farm)
Additionally, Figure 2 shows the relationship between infected or non-infected sows and their
piglets in detail on the basis of the litters. Out of the 68 regarded litters, in 1.5% of the cases
neither sows nor piglets were infected. In 23.5%, Campylobacter spp. was detected in sows
and the whole tested piglets per litter. Notable is the fact that non- infected sows have
nevertheless infected piglets so piglets from non-infected sows were positive for
Campylobacter spp..
rel. frequency (%)
35
30
infected sow
25
not infected sow
20
15
10
5
0
0
1
2
3
4
5
6
number of infected piglets
Figure 2
Relationship between Campylobacter total (C. coli and/or C. jejuni) infected sows and
infected piglets (n = 68 litters)
26
Campylobacter spp. and Yersinia spp. were not isolated neither in feed nor in environmental
samples.
3.2
Fattening unit
Campylobacter spp. were detected in all herds in growing and finishing pigs. Yersinia
enterocolitica O:3 were detected in the faeces of growing pigs in three of the twelve herds
only. Yersinia spp. were isolated in finishing pigs in six of the twelve herds. The prevalence
of Campylobacter spp. (total) and Yersinia spp. (total) in growing pigs were 89.2% (n = 323)
and 15.2% (n = 55), respectively (Table 3). While the prevalence of Campylobacter spp. was
slightly lower (64.7%; n = 229) in finishing pigs, that of Yersinia spp. was nearly the same
(13.3%; n = 47) as in growing pigs. Table 3 shows the decrease in prevalence of C. coli and
C. jejuni and Yersinia spp. during the fattening period. Furthermore, it illustrates the minor
role of Yersinia spp. in fattening herds.
Table 3
Prevalence of Campylobacter spp. and Yersinia spp. in growing and fattening pigs
growing pigs (n = 362)
finishing pigs (n = 354)
%
95% C.I.1
%
71.3
66.6-76.0
28.0
23.3-32.7
25.7
21.2-30.2
42.1
36.9-47.3
2
89.2
86.0-92.4
64.7
59.4-69.4
Yersinia enterocolitica O:3
11.1
7.8-14.3
12.2
8.7-15.6
0.3
0-0.8
0
-
0
-
1.1
0-2.2
3.9
1.9-5.9
0
-
15.2
11.5-18.9
13.3
9.7-16.8
Campylobacter coli
Campylobacter total
Yersinia paratuberculosis
Yersinia enterocolitica
Yersinia total3
95% C.I.
1
2
Yersinia total = Y. enterocolitica O:3 and/or Y. enterocolitica O:9 and/or
Y. paratuberculosis and/or Y. enterocolitica
3
In 28 cases (7.7%), both pathogens, C. coli and C. jejuni, were simultaneously isolated from
the piglet samples at the beginning of the fattening period. Twenty finishing pigs (5.6%) were
infected with both subspecies, too.
27
Campylobacter spp. total (C. coli and/or C. jejuni) was detected at both sampling times from
206 (28.8%) pigs and Yersinia spp. total (Y. enterocolitica O:3 and/or Y. enterocolitica O:9
and/or Y. paratuberculosis and/or Y. enterocolitica) from two pigs (0.3%) during the whole
fattening period.
Campylobacter spp. and Yersinia spp. were not isolated neither in feed nor in environmental
samples.
3.3
Slaughterhouse
During lairage, Campylobacter spp. were isolated from faeces of pigs (n = 68) from all farms
but Yersinia spp. were detected in pigs (n = 7) from two herds only. Before chilling
Campylobacter spp. were isolated from swabs taken from the carcass surface of pigs (n = 24)
from three farms. Yersinia spp. were detected in pigs (n = 1) from only one herd. After twelve
hours of chilling, neither Campylobacter spp. nor Yersinia spp. were isolated from swabs.
The prevalence of Campylobacter spp. (total) decreased during the three sampling phases
from 55.7% (lairage) to 19.7% (before chilling) to 0% (after 12 h chilling), and those of
Yersinia (total) fell from 5.7% to 0.8% to 0% (Table 4).
Table 4
Prevalence of Campylobacter spp. and Yersinia spp. in the slaughterhouse
lairage
n = 122
before chilling
after chilling
%
95% C.I.1
%
95% C.I.
%
95% C.I.
Campylobacter coli
27.9
19.8-35.9
10.7
5.1-16.2
0
-
36.9
28.2-45.6
9.8
4.5-15.2
0
-
Campylobacter total2
55.7
46.8-64.7
19.7
12.5-26.8
0
-
5.7
1.6-9.9
0.8
0-2.4
0
-
Yersinia total3
5.7
1.6-9.9
0.8
0-2.4
0
-
1
2
Yersinia total = Y. enterocolitica O:3 and/or Y. enterocolitica O:9 and/or
3
In lairage, eleven pigs (9.0%) were carriers of C. coli and C. jejuni and before chilling one
animal (0.8%). During both sampling times (lairage and before chilling), Campylobacter total
28
was detected in 13 pigs (5.3%). Campylobacter spp. and Yersinia spp. were not isolated in
equipment samples.
3.4
The production chain from the piglet to the carcass after chilling
From 91 pigs, it was possible to obtain information from the farrowing to the fattening unit.
Out of these, data from 29 animals were acquired at the different stages of the pig production
chain. Figure 3 illustrates the declining tendency of Campylobacter spp. in the whole
production chain and the low prevalence of Yersinia spp. in fattening herds.
prevalence (%)
100
80
C. total¹
60
Y. total²
40
20
0
piglets
growing
pigs
finishing
pigs
lairage³
before
chilling³
after
chilling³
production chain
1
Y. total = Y. enterocolitica O:3 and/or Y. enterocolitica O:9 and/or
3
n = 29
2
Figure 3
Prevalence of the different pathogens in the whole pig production chain (n = 91)
In the farrowing unit, C. coli was detected in 69.2% (n = 63) and C. jejuni in 12.1% (n = 11)
of cases.
During the fattening period, the prevalence of C. coli decreased from 54 growing pigs
(59.3%) to eleven finishing pigs (12.4%). The prevalence of C. jejuni rose from 15 growing
pigs (16.5%) to 43 finishing pigs (48.3%). In the same period, three growing pigs (3.3%) were
carriers of Y. enterocolitica and four finishing pigs (4.5%) were carriers of Y. enterocolitica
O:3.
29
In lairage, eleven pigs (37.9%) were infected with C. coli and five pigs (17.2%) with C.
jejuni. Additionally C. coli was detected on two carcasses before chilling (6.9%).
Only in four piglets (4.4%), four growing (4.4%) and five finishing pigs (5.5%) were both
pathogens C. coli and C. jejuni detected simultaneously.
From the 91 pigs, Campylobacter spp. total could be identified in 33 (36.3%) animals during
the farrowing and fattening unit. Seven pigs (24.1%) were carriers of Campylobacter spp.
total as piglet, growing and finishing pigs and as living pigs in lairage. From only one pig
could Campylobacter spp. be isolated in all steps of the production chain from piglet to
carcass before chilling.
3.5
Retail
Campylobacter coli was isolated from only one liver sample, and Y. enterocolitica, from two
meat samples (mince and cutlet). The pathogens could not be detected in the other 83
samples.
4.
Discussion
The aim of this study was to gather further information about the prevalence of
Campylobacter spp. and Yersinia spp. at the different stages of the pig production chain by
using culture isolation methods.
The results from the farrowing unit point out that compared with sows (33.8%) the prevalence
of their piglets is very high (80.9%). Alter et al. (2005) did not find such a high detection rate.
Whereas no Campylobacter spp. was detectable in the faeces of piglets on the day of birth,
Campylobacter spp. incidence rose within seven days to 32.8%. After transfer to the nursery
unit, the prevalence increased to 56.6%. Jensen et al. (2006) detected high prevalence of
Campylobacter spp. in organic outdoor pigs. All pigs (n = 47) shed Campylobacter (103-107
CFUg-1 faeces) from the age of 8-13 weeks. C. jejuni was found in 29% of pigs in three
consecutive trails and always in minority to C. coli (0.3%-46%). On the basis of the results
from the present project, it becomes obvious that there is no relationship between infected
sows and the infection of their piglets with Campylobacter spp.. This fact clarifies that
sampling of sows alone is useless without taking the piglets into account. Yersinia spp. seems
to play a negligible role in farrowing herds. This is in accordance with another study detecting
Yersinia spp. only during the fattening period but not in sows and piglets (Kasimir, 2005).
The fact that Y. enterocolitica was not isolated in the farrowing unit but first at the beginning
30
of the fattening period is evidence that the cause of infection has to be looked for in the
fattening unit.
On the basis of the results in the fattening unit, it becomes obvious that a stable gut flora from
older pigs can cause a decrease in prevalence. Other studies e.g. from Weijtens et al. (1993;
1999) approve this effect. In this study, the amount of Campylobacter was at 104 cfu/g
excrement at the beginning of the fattening period and about 102 cfu/g excrement at the end of
the fattening period. Also Young et al. (2000) detected a higher prevalence in 14-day-old
piglets compared to gilts. In the present project, the detection rates from Y. enterocolitica in
growing and finishing pigs are moderate (15.2% vs. 13.3%). The low Yersinia-prevalence in
this production stage can be attributed to the persistence of Yersinia spp. in the palatine tonsil
and intermittent shedding. A robust gut flora in older pigs might be the reason for lower
pathogen prevalence due to competition. Pilon et al. (2000) sampled faeces from 20 different
farms. The prevalence of Y. enterocolitica were between 0% and 46.9%. Bush et al. (2003)
detected 12.8% Y. enterocolitica in 2664 faecal samples and Kasimir (2005) described
isolation rates between 0% and 65.4%. However, factors influencing the shedding of
pathogens can rarely be determined definitely, but pigs carrying certain pathogens are
consequently an infection source.
Neither in the environmental nor in the feed samples were Campylobacter spp. and Yersinia
spp. isolated. One reason therefore can be found in the method of detection. Especially for
environmental and animal feed samples, the cultivation method seems to be inferior compared
to Polymerase-Chain-Reaction (PCR), because the low numbers of pathogenic strains in these
samples can often be suppressed by a distinct satellite flora (Fredriksson-Ahomaa and
Korkeala, 2003).
Despite the high prevalence in lairage (Campylobacter total: 55.7%) at the slaughterhouse,
none of the examined pathogens was detected after chilling. Apparently, the chilling of
carcasses and the associated dehydration of the surface area reduce the number of
Campylobacter spp. In this way, an effective minimisation of the infection risk via the food
store chains is possible. But a residual risk attributed to the VBNC status (viable but non
culturable) status could not be denied, enabling certain strains to be still viable without being
identifiable through cultivation. Malakauskas et al. (2006) showed that 28 (63.6%) of the 44
samples collected at the slaughterhouse were contaminated by Campylobacter spp. 23.4% (28
of 120) isolates were identified as C. jejuni (19 from carcasses and nine from slaughter line
surface) and 76.6% (92 of 120) isolates as C. coli (28 from faeces, 47 from carcasses and 17
from slaughter line surfaces). The results suggest that cross-contamination originated in the
31
gastro-intestinal tract of the slaughtered pigs and that the cross-contamination happened
during the slaughter process (Malakauskas et al., 2006). The prevalence of Yersinia spp. in the
slaughterhouse were low (lairage: 5.7% vs. before chilling: 0.8%). One reason for this effect
is that Yersinia spp. persists in the tonsils and will be shed with the faeces discontinuously.
For consumer protection purposes it is noteworthy that in the present project C. coli was
isolated from one liver sample only. The prevalence of Yersinia spp. in raw meat samples
were very low, too. Further studies confirm this result. For example, Arnold et al. (2004)
detected the pathogen in 0.5% of mince samples and Fredriksson-Ahomaa et al. (2001) in
12%. A higher rate was detected only in samples from offal, tongues and palatine tonsils
(Fredriksson-Ahomaa et al., 2001). The low detection rate of Yersinia spp. in raw meat can
also be due to methodological difficulties. In food samples, analysed by cultivation methods
and PCR, the PCR technology recorded a higher prevalence (Fredriksson-Ahomaa and
Kokkeala 2003). Other detection methods are for example DNA hybridisation,
immunofluorescence tests and serotyping. In conclusion, it has to be stated that none of the
methodologies published hitherto is sufficient regarding the reliable detection of pathogenic
Yersinia spp. strains. Therefore, only conditionally fast and safe enrichment and cultivation
methods are available at the moment to detect yersiniosis. With regard to hygiene, one major
point of concern is the ability of Yersinia spp. to survive in raw meat for a long time because
they are viable at temperatures of 4°C. Lack of reasonable care in kitchen hygiene, especially
in private households, can easily lead to cross-contaminations.
Besides C. coli, C. jejuni was laboratory-confirmed in this examination. The isolation of C.
jejuni from pig samples was described by other studies as well. For example, Stich-Groh
(1982) and Young et al. (2000) identified 23.4% and 76.3% respectively, Campylobacter spp.
as C. jejuni. In these assays, hippurathydrolysis served as a confirmation method. This
technique is based on the ability of C. jejuni to hydrolyse hippurat, a biochemical reaction C.
coli is not capable of. One major problem of this method is the possible loss of this ability
during the life span of C. jejuni, causing false positive results with regard to C. coli. But it can
be possible that in some farms or in geographical regions C. jejuni is described as common in
pigs (Kasimir, 2005).
5.
Conclusion
The aim of this study was to analyse the prevalence of Campylobacter spp. and Yersinia spp.
at the different stages of the pig production chain via cultural examination. Samples were
32
taken from sows, suckling piglets, growing and finishing pigs, carcasses, raw meat, forage
and their environment (separating plate, feeding trough).
High prevalence of Campylobacter spp. were found in suckling, growing and finishing pigs.
The observed prevalence from the farrowing unit confirm the conclusion that a pathogen-free
sow does not necessarily mean pathogen-free piglets. Yersinia spp. infections in farrowing
units can be neglected. Additionally it can be pointed out that the prevalence of both
pathogens decrease with the increasing age of animals in the fattening unit. The fact that both
examined pathogens were found only sporadically in food indicates that common slaughter
techniques and hygiene procedures are effective tools to reduce the risks for contamination or
recontamination of meat products.
The most important risk factors responsible for the spread of Campylobacter spp. and
Yersinia spp. in the farrowing and fattening unit should be identified in further studies.
Acknowledgements
This research was financially supported by the H. Wilhelm Schaumann Stiftung, the
Ministerium für Soziales, Gesundheit, Familie, Jugend und Senioren des Landes SchleswigHolstein and the Arbeitsgruppe Lebensmittelqualität und -sicherheit (QUASI) from the
Faculty of Agricultural and Nutritional Science, Christian-Albrechts-University, Kiel.
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35
36
CHAPTER THREE
Campylobacter spp.: Risk factor analysis in fattening pig
farms
and JOACHIM KRIETER1
1
2
Accepted for publication in Archives of Animal Breeding
37
Abstract
There is a lack of information about the prevalence and origins of the important zoonotic
pathogen Campylobacter spp. in the different stages of the pig production chain. The aim of
this study was to gather further information about the sources of infection with
Campylobacter spp. and their qualitative and quantitative importance in pig production. For
statistical analysis, 1,040 results from the bacteriological examination for Campylobacter spp.
were evaluated with questionnaires from four farrowing and twelve fattening units. The
prevalence was determined via faeces and swab samples with regard to certain farm
production parameters. Thereby 30.8% of the sows and 80.9% of their piglets were carriers of
Campylobacter spp.. In the fattening unit, the prevalence at the beginning of the fattening
period was 89.2% and at the end 64.7%. As a result of the small sample size in the farrowing
unit it was not possible to perform a risk analysis which yielded significant conclusions. In the
fattening stage, the following risk factors had a significant effect (p≤0.05) on Campylobacter
spp. prevalence: sampling time, number of fattening places per herd, mixed farming, floor
space design, feed origin, antibacterial and anthelmintic treatment. These results show that
housing and management have a possible influence on the Campylobacter spp. prevalence
and should be investigated further.
keywords: Campylobacter coli / jejuni, pig, fattening units, risk analysis, odds ratio
Zusammenfassung
Titel der Arbeit: Campylobacter spp.: Risikoanalyse in Schweinemastbetrieben
Über die Prävalenzen und Eintragsquellen des Zoonosenerregers Campylobacter spp. in den
verschiedenen Produktionsstufen der Schweineerzeugung existieren bisher nur wenige
Informationen. Die vorliegende Studie soll zur Aufdeckung produktionsspezifischer
Risikofaktoren und ihrer Analyse hinsichtlich der qualitativen und quantitativen Bedeutung
beitragen. Für die statistische Analyse wurden 1.040 Ergebnisse der bakteriologischen
Untersuchung auf Campylobacter spp. im Zusammenhang mit den Informationen aus einem
Fragebogen aus vier Ferkelerzeuger- und zwölf Mastbetrieben ausgewertet. Die Prävalenzen
des Erregers wurden mit Hilfe von Kot- und Abstrichtupferproben vor dem Hintergrund
verschiedener Betriebsbedingungen ermittelt. Dabei wurden bei 33,8% der Sauen und bei
80,9% der Ferkel Campylobacter spp. nachgewiesen. In der Produktionsstufe Mast betrug die
Prävalenz am Mastanfang 89,2% und am Mastende 64,7%. Aufgrund des geringen
Datenmaterials konnte auf der Produktionsstufe Ferkelerzeugung keine Risikoanalyse
durchgeführt werden. Folgende Faktoren hatten auf den Mastbetrieben einen signifikanten
38
Einfluss (p≤0,05) auf die Campylobacter Prävalenz: Zeitpunkt der Probeentnahme, Anzahl
Mastplätze,
Mischbetrieb,
Bodengestaltung,
Futterherkunft,
Einstallbehandlung
und
anthelminthische Behandlung. Die Ergebnisse veranschaulichen, dass eine Reduzierung der
Campylobacter spp. Prävalenz durch betriebliche Haltungs- und Managementfaktoren
möglich ist. Dieses Phänomen sollte weiter untersucht werden.
Schlüsselwörter: Campylobacter coli / jejuni, Schwein, Mastbetriebe, Risikoanalyse, Odds
Ratio
1.
Introduction
Infections caused by Campylobacter spp. (C.) are prevalent worldwide. Campylobacter jejuni
and C. coli are by far the most common Campylobacter species infecting humans. Both
species are associated with clinically indistinguishable diarrhoea in humans (Nachamkin,
2003). In Germany, the Robert Koch-Institute registered 61,823 cases of humans suffering
from such an infection in 2005. However, C. jejuni is implicated in about 85% of the cases of
human campylobacteriosis, with the remaining cases being primarily caused by C. coli
(Friedman et al., 2000).
Campylobacter spp. are part of the normal gut microflora in many food-producing animal
species, including chickens, turkeys, swine, cattle and sheep (Blaser, 1997). For instance, C.
jejuni is more commonly isolated from chickens and cattle, while C. coli is more common
among swine (Young et al., 2000). Transmission to humans appears to occur primarily
through the consumption of contaminated poultry products, unpasteurised milk products and
meat products (Effler et al., 2001; Friedman et al., 2004). In addition to the consumption of
undercooked meat, cross-contamination to other food products may play a significant role in
the number of illnesses observed. The infective dose (number of organisms sufficient to cause
infection) in humans can be very low. Only 800 colony-forming units of specific strains can
lead to Campylobacter infection (Black, 1988).
According to the regulations of the “White Paper on Food Safety” (Europäisches Weissbuch
zur Lebensmittelsicherheit, 2000), the farmer and the participating manufacturing industry in
the food production should have the main responsibility for food safety. Now and in future,
this adds up to the demand for preventive measures in primary production following the
principle “from the producer to the consumer”. This leads to a consolidated need for the
detection of relations between pathogen prevalence in the herds and the herd management and
husbandry. Determination of various important entry routes and spreading factors provides
useful decision guidance for all production units in the meat production chain to minimise the
39
transmission of zoonotic pathogens. For these reasons, this study was conducted with the aim
to determine the prevalence of Campylobacter spp. in farrowing and fattening units by the
collection of faeces and rectal swabs. Further risk factors for the occurrence of
Campylobacter spp. in farrowing and fattening units should be observed via environmental
and feed samples from the checked herds and questionnaires in the corresponding pig farms.
2.
Material and Methods
Four farrowing and twelve fattening farms provided the basis for the present study. The
sampling size on every farm was calculated according to the formula from Noordhuizen et al.
(1997). In total, 1.040 faecal or swab samples respectively from pigs of all ages from
farrowing and fattening units were analysed. Additionally, 56 environmental and feed
samples were collected.
Cultural methods were used to test all samples for Campylobacter spp., including the
differentiation of subspecies. The bacterial detection of Campylobacter spp. proceeds from
ISO 10272 (1995) with following biochemical differentiation of C. coli and C. jejuni.
Calculation of the intraherd and animal prevalence and the 95%-confidence intervals within
the production stage was performed with the PROC SURVEYMEANS procedure from SAS®
(2002).
On every farrowing and fattening farm, data collection was carried out with the aid of a
questionnaire. Besides the general farm information, detailed data about the housing system,
management, state of health and aspects of disease surveillance were acquired. In
consideration of the bacteriological results, these data contributed to a hazard analysis to
detect the origin and spread of Campylobacter spp. infections.
The statistical analysis was performed with a generalised linear model. At first the
management-specific parameters were tested respectively with the χ2-test regarding the
influence on the pathogen prevalence. Every parameter having a value p<0.3 in the χ2-test and
an adequate distribution was included in the generalised linear model. The GENMOD
procedure from the software package SAS® (2002) was reviewed for significance (p≤0.05).
For the estimation, a binomial distribution and a logistic link function (i.e. logistic regression)
were assumed. As a result of the small sample size in the farrowing unit, it was not possible to
perform a risk analysis which yielded significant conclusions. From the fattening unit, the
following fixed effects were considered in the model: sampling time (growing pigs, finishing
pigs), herd organisation (number of fattening places, mixed farming), housing system and
40
forage (floor space design, feed origin) and health (antibacterial and anthelmintic treatment).
The estimates (ê) from the risk factors were transformed into odds ratios (OR = exp (ê)) and
the 95%-confidence intervals were calculated. A low absolute frequency in the least sub
classes from some factors did not allow a statistical analysis with logistic regression. For the
factors having a p-value ≤0.05 in the χ2-test, the odds ratios and 95%-confidence intervals
were calculated separately.
3.
Results
3.1
Prevalence
3.1.1 Sows and suckling pigs
Campylobacter (C.) spp. were isolated in 33.8% of the sows and in 80.9% of the piglets
(Figure 1). Neither pathogen was isolated from the environmental and feed samples.
sows (n = 68)
suckling pigs (n = 256)
prevalence (%)
100
80.9
71.1
80
60
40
33.8
30.9
20
4.4
12.1
0
C. coli
C. jejuni
C. total¹
pathogen
1
Figure 1
Prevalence of Campylobacter spp. in sows and suckling pigs (Prävalenz von Campylobacter
spp. bei Sauen und Saugferkeln)
Table 1 shows the prevalence of Campylobacter spp. in pigs of the farrowing unit at herd
level. Notable is the fact that in herd 4 no sows are carriers of the pathogen but some of their
piglets are. In herd 3, no piglets were sampled, therefore no results for this production stage
appear in Table 1.
41
Table 1
Prevalence of Campylobacter spp. in pigs of the farrowing unit at herd level (Prävalenz von
Campylobacter spp. in der Ferkelerzeugung auf Betriebsebene)
sows1
herd 1
herd 2
herd 3
herd 4
suckling pigs2
prevalence (%)
95% C.I.3
23.5
1.1-46.0
C. coli
-
prevalence (%)
96.5
92.5-100.0
C. jejuni
-
C. total4
23.5
1.1-46.0
96.5
92.5-100.0
C. coli
94.1
81.6-100.0
95.3
90.8-99.9
-
C. total
81.6
81.6-100.0
C. coli
5.9
0-18.4
-
-
C. jejuni
17.6
0-37.9
-
-
C. total
17.6
0-37.9
-
-
C. coli
not sampled
not sampled
21.2
12.3-30.0
C. jejuni
not sampled
not sampled
36.5
26.0-46.9
C. total
not sampled
not sampled
50.6
39.7-61.4
n = 17 per herd
3
2
4
-
-
C. jejuni
1
-
-
95% C.I.
95.3
90.8-99.9
n = 85 or 86 per herd
3.1.2 Fattening pigs
The prevalence of Campylobacter spp. in growing pigs was 89.2% and in finishing pigs
slightly lower with 64.7% (Figure 2). Neither pathogen was isolated from the environmental
and feed samples.
42
growing pigs (n = 362)
finishing pigs (n = 354)
prevalence (%)
100
80
89.2
71.3
64.7
60
40
42.1
28.0
25.7
20
0
C. coli
C. jejuni
C. total¹
pathogen
1
Figure 2
Prevalence of Campylobacter spp. in growing and finishing pigs (Prävalenz von
Campylobacter spp. am Mastanfang bzw. Mastende)
Campylobacter spp. were detected on all farms in growing and finishing pigs (Figure 3). Herd
10 was the farm with the lowest Campylobacter spp. prevalence (54.8% in growing pigs and
19.4% in finishing pigs). In herd 9, no growing pig was pathogen-free (n = 29). There was
still a high prevalence at the second sampling time in comparison to the other herds with
81.5%. Nearly the same results were achieved by herd 12 with 100% (n = 31) carriers of
Campylobacter spp. at the beginning of fattening period and 80.6% at the end of growing
time. In every herd the prevalence decreased from the first sampling time to the second. Only
in herd 3 did the prevalence increase from 75.9% to 86.2%.
43
growing pigs
finishing pigs
prevalence (%)
C . total1
100
80
60
40
20
0
1
2
3
4
5
6
7
8
9
10
11
12
herd2
1
2
herd = 29 to 31 sampled pigs per herd
Figure 3
Prevalence of Campylobacter spp. in the fattening pigs at herd level (Prävalenz von
Campylobacter spp. bei Mastschweinen auf Betriebsebene)
3.2
Risk factors
For the statistical risk factor analysis in the fattening unit, 716 results from the bacteriological
examination were evaluated in context with the questionnaire data from the twelve fattening
herds. Twenty factors were tested regarding their influence on the prevalence of
Campylobacter. Significant effects were shown for the following factors: sampling time,
number of fattening places, mixed farming, floor space design, feed origin, antibacterial and
anthelmintic treatments (Table 2).
44
Table 2
Significant risk factor and further risk factors: fattening unit (Signifikante Risikofaktoren und
weitere Einflussfaktoren bei Mastschweinen)
prevalence (%)
OR1
95% C.I.2
89.2
64.7
4.64
1
3.11-6.93
-
80.0
74.3
1.44
1
1.00-2.08
-
74.6
82.0
0.61
1
0.41-0.92
-
74.4
74.8
84.7
0.35
0.56
1
0.20-0.95
0.32-0.97
-
70.3
79.4
0.41
1
0.24-0.68
-
74.6
79.7
0.66
1
0.45-0.96
-
83.9
74.8
1.99
1
1.25-3.18
-
source3
own piglets
steadier farrowing herds
purchase breeding herds
73.3
76.1
90.3
0.26
0.32
1
0.09-0.75
0.13-0.76
-
feed consistency3
meal
granule
pellets
70.3
81.0
78.0
0.63
1.23
1
0.42-0.96
0.60-2.54
-
blank dwell time3
>10 days
<10 days
90.5
74.5
3.53
1
1.82-6.86
-
risk factor
p-value
date
sampling time
growing pigs
finishing pigs
<.0001
herd organisation
number of fattening places
< 1000 places
> 1000 places
mixed farming
stall separated
stall not separated
housing system and forage
floor space design
fully slatted floor
<50% slatted floor
plan floor without bedding
feed origin
own forage
purchase forage
health
antibacterial treatment
yes
no
anthelmintic treatment
yes
no
1
odds ratio
2
0.052
0.015
0.001
0.001
0.028
0.003
3
45
further risk factor in the fattening unit
Over the fattening period the Campylobacter spp. prevalence decreased. At the beginning the
odds ratio increased by a factor of 4.46 (Table 2).
The risk factor fattening places per herd was differentiated between farms size under 1000
pigs and alternatively over 1000 pigs. The bacteriological results show that pigs from farms
with less than 1000 fattening places had a prevalence of 80.0% and those from larger farms a
prevalence of 74.3%. The chance to isolate Campylobacter spp. from pigs from smaller herds
increased by a factor of 1.44.
Housing in separated stalls is another preventive influence. When the animals on mixed farms
were kept in separated stalls the chance of a positive bacteriological result decreased
(OR = 0.61).
Pigs which were kept on a plan floor without bedding had the highest prevalence in
comparison to the other flooring systems. In this housing system, the chance of obtaining a
positive result was highest.
An antibacterial treatment at the beginning of the fattening period was implemented on seven
herds. The following antibiotics were used for this treatment: Amoxicillin, Tetracycline and
Sulfonamide. The chance of a positive finding decreased when the animals were treated with
antibacterial substances during this time period (OR = 0.66).
On four herds, anthelmintics were used at the beginning of fattening period. The appliance of
Ivermectin, Flubendazol and Levamisolhydrochlorid was adopted for deworming. The chance
of obtaining a positive result rose by a factor of 1.99 when anthelmintics were administered.
Further risk factors ‘source of piglets’, ‘feed consistency’ and ‘blank dwell time’ had an
influence on the prevalence of Campylobacter spp., too. The chance of obtaining a positive
result from the bacteriological investigation was smaller from fattening pigs in a closed herd
system (OR = 0.26). Furthermore, the following cases were preventive: feeding meal
(OR = 0.63) instead of granule or pellets and blank dwell time under 10 days.
4.
Discussion
The results from the present study prove that Campylobacter spp. are of increasing
importance in farrowing and fattening units: high prevalence of Campylobacter spp. were
found in suckling, growing and finishing pigs (Wehebrink, 2006). Other studies also confirm
these results (Kasimir, 2005; Gaull, 2002).
The occurrence of Campylobacter spp. in subsequent samples of pigs and sows was often
variable in this analysis. As known from further studies the Campylobacter spp. prevalence
may vary because the physiological status of the animal and external factors can influence the
46
intestinal flora. The ability of Campylobacter spp. to colonise the intestinal tract of pigs is
probably subject to the various factors influencing the colonisation resistance of the gut
(Ruckebusch et al., 1991). Furthermore, the virulence of the Campylobacter spp. strains
(re)infecting the pigs may also alter the bacteriological results (Weijtens et al., 1999).
The prevalence estimates on basis of bacterial findings must be questioned critically. Because
of the intermittent shedding at animal level the bacterial detection in faecal samples can create
a false image of the prevalence at herd level. Additionally, during sampling and laboratory
processing, the pathogen’s sensibility to environmental influences can decrease the detection
rate.
The bacteriological analysis showed that in some herds as far as 100% of the pigs had contact
with Campylobacter spp.. In contrast to Young et al. (2000), a successful abatement strategy
can be doubted due to high general prevalence and the infection of piglets during the first
weeks of life.
Based on the zoonotic directive (Nr. 2160/2003), a monitoring for Campylobacter spp. is
mandatory. It should take place at an adequate stage of the food chain. Control has to be
directed primarily at the prevention of colonisation of farm animals by means of the
implementation of Good Hygienic Practice (GHP), biosecurity measures and husbandry
practices incorporating Hazard Analysis Critical Control Point (HACCP) based on risk
management systems (Whyte et al., 2002). Because of this, the objective of this study was to
obtain more information about the risk factors influencing the prevalence of this pathogen. As
a result of the small sample size in the farrowing unit, it was not possible to perform a risk
analysis which yielded significant conclusions. In the fattening unit the attention was focused
additionally on risk factors which do not reach the significant limitation of the 5% probability
error because of the small sample size. Effects which exceeded the housing and management
factors were not acquired in the questionnaire and could not consequently be regarded in the
evaluation. Because of this the results should only be regarded as tendencies.
One important influencing factor could be the sampling time. Because of the steady state of
immunity the chance of a positive Campylobacter spp. result is higher in growing pigs than to
finishing pigs. Additionally, transport stress, changing the forage and status conflicts can raise
the faecal shedding of this pathogen in growing pigs.
In contrast to recent studies, risk factor analysis in the fattening unit demonstrated a
significant influence on the Campylobacter spp. detection rate for the ‘number of fattening
places’. The chance of obtaining a positive Campylobacter spp. result is higher when animals
are held in smaller herds (<1000 places). This result did not conform to Gaull (2002). He
47
detected that the factor ‘number of animals’ hardly has any influence on Campylobacter spp.positive animals.
Separating the herds in ‘mixed farming’ is a useful method to decrease pathogen transmission.
In contrast to our study, Boes et al. (2005) could not assert this effect: investigation of the
occurrence and diversity of C. jejuni infections in finisher pigs in herds with combined cattle
or poultry production and herds only producing pigs showed no evidence of transmission of
C. jejuni from cattle or poultry to pigs in mixed production herds. Herd prevalence of C.
jejuni was 8.3%, whereas C. jejuni and C. coli were isolated from 0.8% and 92.0% of pigs,
respectively. In mixed production herds, C. jejuni predominated in cattle (42.7%) and poultry
(31.6%), whereas C. jejuni was only isolated from 1.3% to 2.5% of pigs in these herds.
A lower Campylobacter spp. detection rate is not promoted by a plan floor without bedding
and purchase forage. One reason for the higher prevalence in housing systems with plan floor
is the intensive contact of the pigs with their faeces for a longer time. With regard to
purchased forage, the origin is often uncertain: whether the forage comes directly from the
forage producer or whether several forage chandlers are interposed, increasing the risk of
contamination, remains often unknown.
A further result from the questionnaire analysis was that an arranged antibacterial treatment
but no anthelmintic treatment was preventive against Campylobacter spp. infections. These
results must be questioned critically because it is not known first which health status in detail
can be found in the different herds and, second, what the antimicrobial resistance of
Campylobacter spp. is. Further studies will be needed to explain these two risk factors.
Despite the fact that forage in granule form is heated during the manufacturing process, the
chance of obtaining a positive Campylobacter spp. result rose by a factor of 1.23 in this form
of forage feeding.
The fact that a blank dwell time under ten days is better for the pathogen prevalence than a
blank dwell time over ten days can be related to recontamination after disinfection and
cleaning.
Other studies found risks factors which could not be proven in this study. For example, Gaull
(2002) discovered that a factor such as different ‘husbandry’ hardly has any influence on
Campylobacter spp.-positive animals. ‘Feed’ and ‘number of pig delivering farms’ are not
risk factors either (Weijtens et al., 1993). Schuppers et al. (2005) detected that important risk
factors contributing to the prevalence of resistance strains were shortened tails, lameness, skin
lesions, feed without whey, and ad libitum feeding. Multiple antimicrobial resistance was
more likely in farms which only partially used an all-in all-out system, or a continuous-flow
48
system compared to a strict all-in all-out animal-flow. Presence of lameness, ill-thrift, and
scratches at the shoulder in the herd also increased the odds for multiple resistance. Thus, the
results from Schuppers et al. (2005) showed that on finishing farms which maintained a good
herd health status and optimal farm management the prevalence of antimicrobial resistance
was also more favourable.
In the present study, only a few factors could be identified as potential risk factors. For further
clarification of risk factors comprehensive assessment and transmission devolution studies are
required.
Acknowledgement
References
Black, R.E.; Levine, M.M., Clements, M.L., Hughes, T.P., Blaser, M.J., 1988. Experimental
Campylobacter jejuni infection in humans. J. Infect. Dis. 157 (3), 472-479.
Blaser, M.J., 1997. Epidemiologic and clinical features of Campylobacter jejuni infections. J.
Infect. Dis. 176 (Suppl. 2), 103-105.
Boes, J., Nersting, L., Nielsen, E.M., Kranker, S., Enøe, C., Wachmann, H.C., Baggesen,
D.L., 2005, Prevalence and Diversity of Campylobacter jejuni in Pig Herds on Farms
with and without Cattle or Poultry. J. Food Prot. 68, 722-727.
Effler, P., Ieong, M.C., Kimura, A., Nakata, M., Burr, R., Cremer, E., 2001. Sporadic
Campylobacter jejuni infections in Hawaii: associations with prior antibiotic use and
commercially prepared chicken. J. Infect. Dis.183 (7), 1152-1155.
Friedman, C.R., Neimann, J., Wegener, H.C., Tauxe, R.V., 2000. Epidemiology of
Campylobacter jejuni infections in the United States and other industrialized nations.
In: Nachamkin, I.; Blaser, M.J.: Campylobacter. 2nd ed. Washington, D.C., American
Society for Microbiology Press., 121-138.
49
Friedman, C.R., Hoekstra, R.M., Samuel, M., Marcus, R., Bender, J., Shiferaw, B., 2004. Risk
factors for sporadic Campylobacter infections in the United States: a case-control study
in FoodNet sites. Clin. Infect. Dis. 38 (Suppl. 3), 285-296.
Gaull, F., 2002. Vorkommen thermophiler Campylobacter spp. bei Schweinen im Betrieb und
auf dem Schlachthof, auf Putenschlachttierkörpern und in Lebensmitteln tierischen
Ursprungs – Typisierung der Isolate mit molekularbiologischen Fingerprintingmethoden
und Vergleich der Isolate untereinander und mit humanen Isolaten. (Diss. med. vet.).
Univ. Leipzig.
International Organization for Standardization, 1995. International Standard 10272.
Kasimir, S., 2005. Verlaufsuntersuchungen zum Vorkommen potentiell humanpathogener
Univ. Leipzig.
Nachamkin, I., 2003. Campylobacter and Arcobacter. In: Murray, P.R., Baron, E.J., Pfaller,
M.A., Jorgensen, J.H., Yolken, R.H.: Manual of clinical microbiology, ASM Press,
Washington, DC, 902-914.
Noordhuizen, M., Frankena, K., Graat, E., 1997. Animal health care and public health issues.
In: World Congress on Food Hygiene, The Hague/Netherlands, Proc., 59.
Robert Koch-Institut, 2006. Epidemiologisches Bulletin Nr. 3.
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digestive tract. In Physiology of Small and Large Animals ed. Ruckebusch, Y.; Phaneuf,
L.P., Dunlop, R., Philadelphia: Becker, 198-208.
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Schuppers, M.E., Stephan, R., Ledergerber, U., Danuser, J., Bissing-Choisat, B., Stärk,
K.D.C., Regula, G., 2005. Clinical herd health, farm management and antimicrobial
resistance in Campylobacter coli on finishing pig farms in Switzerland. Prev. vet. Med.
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Verordnung (EG) NR. 2160/2003, des Europäischen Parlaments und des Rates vom 17.
November 2003 zur Bekämpfung von Salmonellen und bestimmten anderen durch
Lebensmittel übertragbaren Zoonoseerregern.
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Wehebrink, T., Kemper, N., grosse Beilage, E., Krieter, J. (2006). Prevalence of
Campylobacter spp. and Yersinia spp. in the pig production. Prev. Vet. Med.
(submitted).
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Whyte, P., Bolton, D., O’Mahony, H., Collins, J.D., 2002. Development and Application of
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51
52
CHAPTER FOUR
Simulation study on the epidemiology of Salmonella spp. in
the pork supply chain
TANJA WEHEBRINK, NICOLE KEMPER
and JOACHIM KRIETER
53
Abstract
Pork can be regarded as an important source of food-borne salmonellosis. The objective of
this research was to gain insight into the epidemiological effects of different strategies in the
farrowing and finishing units to improve the food safety of pork with respect to the
prevalence of Salmonella spp. in finishing pigs. Therefore a stochastic transition model was
designed depending on prevalence in the population (sows = 0.5% to 65%; rearing pigs = 2%
to 95%), infection risks (farmer = 0% to 10%; rodents = 0% to 5%; feed = 0% to 10%; and
dust = 0% to 5%), the immunisation schedule of sows (yes/no) and the purchase of pathogenfree gilts (yes/no). The simulation model generated an integrated pig production chain with
linkages between the stages farrowing, rearing and fattening. Within each herd, dynamic
patterns of Salmonella infections were simulated. The simulation covered a time interval of
24 months.
The results in the present study showed that preventive measures must first be introduced in
the fattening unit because at this production stage preventive measures regarding the different
risk factors had the highest influence on the prevalence of Salmonella spp.. The risk factor
‘farmer’ represented an exception as the influence of this factor was higher in the rearing unit
(22.8% vs. 17.1%). The distribution over management interventions in the finishing stages
was in the following order: farmer (p-value: 0.0004-0.0443), feed (p-value: 0.03-0.46), dust
(p-value: 0.33-0.66) and rodents (p-value: 0.71-0.92). Immunisation against Salmonella spp.
in sows represents a good strategy to decrease prevalence of Salmonella spp. in the fattening
unit.
keywords: farrowing and fattening unit, Monte Carlo Simulation, risk factors, Salmonella spp.
54
1.
Introduction
In industrialised countries, Salmonella enterica is a frequent cause of food-borne infections
(Gebreyes et al., 2006). About 15-25% of all human salmonellosis cases worldwide can be
attributed to the consumption of contaminated pork and pork products (van Pelt and
Valkenburgh, 2001). Up to now, more than 2,500 serovars of Salmonella enterica have been
recognized (Farmer, 1999). Two non-host-adapted serovars common in animals and humans
are S. (Salmonella) Enteritidis and S. Typhimurium, which have been reported as two of the
top food-borne infections in developed countries (Poppe et al., 2002). In Germany, 52,245
salmonellosis cases were registered in 2005. Compared with cases in 2004, a decrease of
8.3% was assessed. Salmonella Enteritidis was analysed in 68% and S. Typhimurium in 25%
of the infections (Bätza, 2006).
Contamination of pork products is related to asymptomatic intestinal carriage of Salmonella
spp. by living pigs arriving at the slaughterhouse. To reduce the risk of pork contamination,
some countries have established monitoring programs to identify pig farms with a high
proportion of market hogs carrying Salmonella spp., followed by steps towards the reduction
of the on-farm prevalence (Christensen et al., 2002). These actions will be mandatory in the
future and especially in Europe, where several laws have recently been announced. In this
context, directive 92/117/EEC was abolished and replaced by directive 2003/99/EC on the
monitoring of zoonoses and zoonotic agents (Anonymous, 2003). Furthermore, a regulation
for the control of Salmonella spp. in pig production was established (Anonymous, 2007).
Control of Salmonella spp. in pork can be accomplished at all levels of production including
pre-harvest (farm level). In order to limit and control Salmonella spp. occurrence in a swine
herd, it is initially necessary to conduct epidemiological studies, first to determine the
prevalence of Salmonella spp. and identify possible risk factors, and consequently to
implement and monitor control programs (Mousing et al., 1997). Since it is not possible to
test all individual interventions in practice, computer simulation is an attractive way to
explore the effect of prevalence variations (Dijkhuizen and Morris, 1997).
The present research included an exploration of possible measures that can be implemented in
a farrowing and fattening unit to control the introduction and reduce the prevalence of
Salmonella in finishing pigs. A stochastic state-transition simulation model was established to
gather further information about the influence of the risk factors in the different pig
influence of preventive arrangements of the immunisation of sows, and additionally, of
55
pathogen-free purchased gilts on the Salmonella spp. prevalence in the farrowing and
fattening unit were determined.
2.
Materials and Methods
2.1
General conception
In accordance with Krieter (2004), the simulation model includes an integrated pig production
chain with vertical linkages between the three stages farrowing, rearing and fattening of pigs.
Herd size at the farrowing stage was set to 210 productive sows, at the fattening level 1,500
places per farm were assumed implying 2.7 production cycles per year. In the farrowing
stage, feeder pigs were produced, which are passed on to the fattening stage at a live weight of
28 kg. Animals were slaughtered at a live weight of 115 kg. The model starts with the
generation of the sows’ performance. The production cycle was 150 days, based on the
gestation of 115 days, lactation length of 28 days and seven days from weaning to breeding.
Because of these facts, the number of litters per sow and year was 2.3. Litter size and piglet
mortality was simulated over ten litters with non-linear patterns for litter size born alive and
piglet mortality (Brandt, 1984). An average of 10.2 piglets were born alive and piglet
mortality varied between 13.3% and 18.1%. The culling percentage of sows was defined by a
40% replacement rate. The purchased gilts were integrated into the herd with 180 days.
Postweaning mortality was 1%, during fattening the mortality rate rose to 3%. The simulation
model includes possible crowding effects (e.g. stress, higher infection risk) between the
different stages of the production chain. After weaning, three litters were housed in one large
group within the farrowing farm at one time. In the fattening unit, the piglets were split into
two batches after transport. As shown by van der Wolf (2000), the in-herd Salmonella spp.
prevalence fluctuates within a given period. To make allowances for this variation, the
duration of the simulation was extended to 24 months.
2.2
Entry and spread of Salmonella spp. in the farrowing and fattening unit
The model considered several alternatives for Salmonella spp. entry in the production chain
(Table 1). The assumptions were based on literature about Salmonella spp. in the pork chain
(van der Wolf, 2000; Stege et al., 2001; Meyer et al., 2005). The probability of an infection
due to the risk factors varied between stages and depended on the prevalence in the
population. An important source of Salmonella spp. entry of all stages was the acquisition of
infected animals from the preliminary stage. Latently infected animals entering the herd
56
unnoticed due to the lack of clinical symptoms can intermittently shed Salmonella spp. via
their faeces. The farmer himself is the highest risk factor. For example, he can introduce
Salmonella spp. in the barn via boots, overalls and other implements and he is additionally
responsible for the spread of the pathogen in the herd. The feasibility of an infection due to
the farmer was simulated from 0% to 15%. Another living vector are rodents. In the model, it
was assumed that rodents mainly initialise and maintain the contamination cycle at the farm.
The probability of an infection due to rodents ranged from 0% to 5 %.
The occurrence of Salmonella spp. in feed is mostly a consequence of recontamination during
production, transport or storage. The probability of an infection due to feedstuff ranged from
0% to 10%.
The concluding risk factor in the simulation program is dust. The pathogen Salmonella spp. is
able to survive in dust at room temperature for four years (Selbitz, 2002). Thus, dust is
responsible for a re-infection of a cleaned and disinfected barn. The chance of a positive result
from the pigs ranged from 0% to 5% (Table 1). These four assumed risk factors were higher
in breeding farms compared to finishing farms (due to e.g. all-in all-out, cleaning and
disinfection).
Table 1
Description of the model inputs
Description of variables
mean
Production
farrowing unit
sows
piglet number born alive per litter1, piglet
mortality (piglets), %
lactation period, days
weaning-to-oestrus interval, days
litters per sow and year, n
replacement rate, %
rearing unit (7 to 28kg live weight)
mortality, %
production cycle
finishing unit (>28 to 115kg live weight)
mortality, %
production cycle
57
210
10.2
15.3
28
7
2.3
40
1
6.1
3
2.7
min
max
8.6
13.3
11.5
18.1
Table 1
Description of the model inputs (cont.)
Salmonella spp. introduction
farrowing unit
sows
prevalence replacement gilts, %
probability of an infection due to, %
biotic vector:
farmer
rodents
abiotic vector:
feed
dust
rearing unit (weaning piglet)
biotic vectors:
farmer
rodents
abiotic vectors:
feed
dust
fattening unit
biotic vectors:
farmer
rodents
abiotic vectors:
feed
dust
-2
0
90
-2
-2
-2
-2
0
0
0
0
15
5
10
5
-2
-2
-2
-2
0
0
0
0
10
1
2
2
-2
-2
-2
-2
0
0
0
0
10
2.5
10
5
10
20
95
90
Salmonella spp. transmission
farrowing unit
sows, piglets – suckling period
probability – excretion of S. spp. via faeces by infected sows
probability – infection of piglets by sows infected
rearing unit
crowding, no. litters per pen
crowding factor, c3
probability for the infection from pen to pen, %
fattening unit
crowding, no. pen per pen (weaning)
crowding factor, c3
probability for the infection from pen to pen, %
1
2
-2
-2
3
0.50
30
2
0.80
60
depending on parity, weighted with frequency of parity distribution
3
depending on the prevalence
explanation, see text
In the stochastic state-transition model, groups of pigs move through the pork supply chain
and may become infected with Salmonella spp.. A pig can have two states with respect to
Salmonella spp. over the expected 24 months with four transitions respectively: free stays
free, free changes to infected, infected changes to free or infected stays infected. The
transmission of Salmonella spp. in the vertical production chain depends on the Salmonella
spp. status of the sow at the farrowing unit. Suckling piglets can be infected by perinatal
58
contamination and the faeces of the sow. The probability that infected sows excreted
Salmonella spp. with the faeces ranged between 10% and 95%, depending on the general
Salmonella status of the farm. The risk of a piglet becoming infected by the contaminated
faeces of the sow varied from 20% to 90%. Each alteration of the stage caused an increase in
prevalence due to crowding. Crowding was considered from lactation to weaning and from
weaning to finishing. Two patterns of the spread of infection within units were taken into
account. First, if a pen had a known number of animal infected (nj) after arrival, the
proportion of infected animals (pui) was updated with:
pui = ni/N+c[ni/N(1-exp-(1-ni/N))]
N is the total number of animals per pen and c the weighting factor depending on the stage
considered. Parameter c diminishes the probability of spreading the infection at the weaning
stage (0.50) and increases the risk at the fattening level (0.80). Secondly, infections spread
from adjacent pen to adjacent pen within a barn due to faeces and other vectors (e.g. boots,
overalls and other implements). The probability of pen-to-pen transmission was set at 30% at
weaning and 60% at finishing. The Salmonella transmission from barn to barn was neglected
in the model.
2.3
Simulation scenarios
The data in Table 2 represent the different scenarios of Salmonella spp. introduction, e.g. by
sows, weaning piglets and fattening pigs.
The basic scenario has approximately the same values as the ‘low scenario’. Additionally,
‘middle scenarios’ and ‘high scenarios' of a probability of infection due to biotic and abiotic
vectors were simulated.
59
Table 2
Parameters of simulation scenarios
parameter
low
Salmonella spp. introduction
farrowing unit
sow
biotic vectors:
farmer
rodents
abiotic vectors:
feed
dust
immunisation schedule (sows)
purchase of gilts
rearing unit
weaning piglet
biotic vectors:
farmer
rodents
abiotic vectors:
feed
dust
fattening unit
pig
biotic vectors:
farmer
rodents
abiotic vectors:
feed
dust
2.4
value
middle
high
0.50
0.25
0
0.30
10.00
10.00
7.00
1.50
5.00
2.50
15.00
4.00
10.00
4.90
0.50
0.25
0.05
0.07
5.00
0.75
1.00
1.75
10.00
1.00
2.00
1.90
0.80
0.15
0.50
0.13
6.50
1.75
5.50
3.50
9.50
2.50
10.00
5.0
Statistical analysis
The significance of systematic environmental effects on the prevalence of Salmonella spp.
was investigated in a generalized linear model. The following risk factors were considered in
the model: farmer, rodents, feed and dust with four classes respectively and two fixed effects
were additionally assumed: immunisation of sows (yes/no) and purchase of pathogen-free
gilts (yes/no) (see Table 2). The analysis was performed with the SAS procedure GENMOD
(SAS® 2002). For the estimation, a gamma distribution and a logistic link function (i.e.
logistic regression) were assumed. In total, 100 farms were simulated with 100 replicates.
60
3.
Results
3.1
Basic situation
Figure 1 presents the prevalence of the animals from the farrowing to the fattening unit in
consideration of the baseline parameters. In the farrowing unit, the prevalence from sows
prevalence (%)
(17.1%) and suckling piglets (14.4%) was higher than in the following production stages.
20
Salmonella spp.
17.1
14.4
15
12.3
11.9 *
10
5
0
suckling
piglets
sows
weaning pigs
fattening
pigs
pig production
*standard error
Figure 1
Prevalence (LS-Means) of Salmonella spp. in the basic situation
3.2
Simulation scenarios
Farmer
The risk factor ‘farmer’ is a synonym for a very complex introduction- and spread-risk.
For example, a farmer can introduce Salmonella spp. in the barn via boots, overalls and other
implements. Additionally, he can be responsible for the spread of the pathogen in the herd
because he is a biotic vector for cross-contaminations. Figure 2 shows the farmer’s influence
with different probability of infection (0.5%-15.0%) in the farrowing / rearing / fattening unit
on the prevalence of Salmonella spp. in fattening pigs.
61
prevalence fattening
pigs (%)
farrowing unit
rearing unit
fattening unit
30
22.8
25
17.1
20
15
11.2
11.7
17.1
15.0
11.8
*
13.7
12.7
10
5
0
low
middle
high
probability of an infection (%)
*standard error
Figure 2
Salmonella spp. prevalence (LS-Means) in fattening pigs depending on the risk factor
‘farmer’ at the different production stages
In total, the increasing of Salmonella spp. from the fattening pigs during the different
scenarios was moderate (11.7% vs. 12.7% vs. 13.7%) when the infection source was in the
farrowing unit. A huge influence on the pathogen prevalence was when the introduction
happened in the rearing unit. In this case, the prevalence rose from 11.2% over 17.1% to
22.8%.
In every production stage, the farmer was a significant risk factor (p-value = 0.0055 farrowing
unit; p-value = 0.0004 rearing unit; p-value = 0.0443 fattening unit) on the Salmonella spp.
prevalence in fattening pigs.
Rodents
Another biotic vector are rodents. In the model, it was assumed that rodents mainly initialise
and maintain the contamination cycle at the farm. Rodents had no significant influence on the
prevalence in fattening pigs (p-value: 0.71-0.92). Figure 3 shows that the Salmonella spp.
prevalence of fattening pigs only varied slightly during the different scenarios (between
11.1% to 12.8%). Apparently, there is no impact as to where the introduction takes place and
with which tendency (0.25%-4.0% probability of an infection).
62
pigs (%)
farrowing unit
14
12
10
8
6
4
2
0
rearing unit
fattening unit
11.7 11.1 11.3
11.8 11.6 12.3
12.4 11.9 12.8
*
low
middle
high
*standard error
Figure 3
Salmonella spp. prevalence (LS-Means) in fattening pigs depending on the risk factor
‘rodents’ at the different production stages
Feed
The occurrence of Salmonella spp. in feed is mostly a consequence of recontamination during
production, transport or storage. Feed only had a significant influence (p-value = 0.03) in the
fattening unit. The highest prevalence was reached in the scenario when the fattening pigs
were contaminated with feed (Figure 4). Although the sows had nearly the same infection
probabilities in the middle (5.0% vs. 5.5%) and high scenarios (10.0% vs. 10.0%), the
prevalence in fattening pigs was at 12.1% (middle infection probability) and 13.0% (high
infection probability) not as high as when the infection happened in the fattening unit. The
Salmonella spp. prevalence reached in this case 15.6% and 17.1%.
63
prevalence fattening pigs
(%)
farrowing unit
rearing unit
20
15
fattening unit
17.1
15.6
11.5
11.5
10.5
12.1 11.9
*
13.0 13.2
10
5
0
low
middle
high
*standard error
Figure 4
Salmonella spp. prevalence (LS-Means) in fattening pigs depending on the risk factor ‘feed’
at the different production stages
Dust
The pathogen Salmonella spp. is able to survive in dust at room temperature for four years.
Thus, dust is responsible for a re-infection of a cleaned and disinfected barn. Dust had no
significant influence on the prevalence in fattening pigs (p-value: 0.33-0.66). Figure 5 points
out that the highest prevalence (14.3%) was reached when the barn was not strictly cleaned in
the fattening unit.
64
pigs (%)
farrowing unit
16
14
12
10
8
6
4
2
0
11.5 10.7 11.5
low
rearing unit
12.7 13.3
12.1
fattening unit
14.3
12.3
middle
12.9
*
high
*standard error
Figure 5
Salmonella spp. prevalence (LS-Means) in fattening pigs depending on the risk factor ‘dust’
at the different production stages
Preventive measures
Additionally, in the farrowing unit, it was simulated which preventive measure is more
effective. Figure 6 clarifies that the sow immunisation is more crucial than the purchase of
pathogen-free gilts. The prevalence in animals in the scenario with ‘purchase of pathogen-free
gilts’ were between 2.6% and 4.3% higher compared to the scenario ‘sow immunisation’.
Neither the immunisation nor the purchase of pathogen-free gilts had a significant influence
(p-value = 0.76 vs. p-value = 0.85) on the Salmonella spp. prevalence in the pig production.
65
immunisation
prevalence (%)
20
pathogen free gilts
15.6
13.0
15
11.8
10
10.3
10.4
7.5
7.0
7.3
*
5
0
suckling piglets
sows
weaning pigs
fattening pigs
production stage
*standard error
Figure 6
The effects of immunisation and purchase of pathogen-free gilts (LS-Means)
4.
Discussion
The simulation model generates an integrated production chain starting with the purchase of
sows at the farrowing unit and closing with the finishing pig in the fattening unit. At each
stage, Salmonella spp. may enter the production chain by different vectors (e.g. latently
infected animals, feed etc.), the transmission is affected be the status of the sow, crowding
effects and pen-to-pen infections. Assumptions about the entry and spread of Salmonella spp.
were derived from the literature.
Due to the lack of further information in the literature about the different parameters and their
infection probabilities, for instance the crowding effect, various scenarios were simulated
within biological limits. Based on the simulation of best- and worst-case scenarios,
parameters representing the most important effects influencing or lowering the prevalence in
fattening pigs were determined. Finally, these parameters were adjusted to the prevalence at
the different production stages as known from the literature.
The estimated prevalence in the basic scenario is confirmed by numerous prevalence studies.
For instance, in a Lower-Saxonian study by Quante (2000), in 79 out of 88 examined farms,
less than 20% of the sows were serologically tested positive, in seven 20%-40% and on two
farms more than 40% were positive. Meyer et al. (2005) analysed 1,498 blood samples of
sows serologically, showing positive results for 17.1% of the samples. Regarding fattening
66
pigs, on 96 farms Stege et al. (2000) showed at least one positive serological sample in 65.6%
of the farms. The average intraherd prevalence was 2%, the highest Salmonella spp.
prevalence was reached with 32% positively tested animals. In another study, 11% of 1,760
tested blood samples from fattening pigs reacted ELISA positive (van der Wolf, 2000). Meyer
et al. (2005) reported 301 (11.4%) positive serological results out of 2,642 blood samples
from fattening pigs.
The aim of the present paper focused on further information about the influence of the risk
factors (biotic vectors = farmer, rodents; abiotic vectors = forage, dust) in the different pig
influence of preventive arrangements of immunisation of sows, and additionally, of pathogenfree purchased gilts on the Salmonella spp. prevalence in the farrowing and fattening unit
were determined.
The results in the present study clarify that the greatest influence on the Salmonella spp.
detection rate is in the fattening unit. This conforms with an expert survey in the Netherlands
and Denmark by van der Gaag (2002). The ranking of the management interventions in the
primary stages shows that most of the emphasis is placed on reducing or preventing the
spread of Salmonella spp. within the farm. Two stages in the chain (finishing and
slaughtering) are expected to be able to most effectively improve the food safety of pork with
respect to Salmonella spp. (van der Gaag, 2002).
The interaction between Salmonella spp., host, and environment is influenced by various
factors. Thus, especially in the rearing unit, the farmer plays a major role in Salmonella spp.
transmission in this unit and later Salmonella spp. prevalence in the fatting unit (11.2%22.8%). One reason for this has to be seen in the incompletely developed immune response in
the pigs at an age between 21 and 80 days. Maternal immunoglobulines transferred to the
piglets with the colostrum are supposed to have vanished at this point of time while the
individual antibody production is only slowly increasing. Especially in the fattening unit, the
crowding effect has to be regarded, implicating a higher infection risk between the different
stages of the production chain.
Entry of pathogens can be brought about via abiotic factors such as contaminated equipment
and other vectors. Additional spreading of Salmonella spp. is provoked by crosscontamination during daily work processes (Blaha, 1993). This fact is confirmed by other and
the presented research. Barber et al. (2002) and Rajic et al. (2005) reported that Salmonella
spp. were detected in 11% and 39% of boot samples, respectively. However, as part of
67
hygienic-lock facilities combined with all-in all-out production (Lo Fo Wong et al., 2004),
clean farmers’ boots might contribute to reducing the risk of Salmonella spp. infections.
Further potential risk factors for Salmonella spp. are rodents and wild birds (Zheng et al.,
2007). Wild fauna as well as other domestic animals living on the farm or in the surrounding
environment may introduce and transmit Salmonella spp. through direct contact with pigs, or
by faecal contamination of feed or farm equipment. Rodents are known to be carriers of
Salmonella spp. (Leirs et al., 2004). Reported prevalence of Salmonella spp. positive rodents
were between 4% and 30% (Böhm, 1993). Contrary to these facts, in the present simulation
rodents had hardly any influence on the prevalence The Salmonella spp. prevalence in
fattening pigs was in every scenario at a low level (11.7%-12.8%) and there were no high
variations. The prevalence in fattening pigs rose with the respected increase in the infection
probability in the fattening unit from 11.5% over 15.6% to 17.1%. The reason for this has to
be seen in the estimated low entry risk and the impact at a relatively late stage of the
simulation.
In addition to the presented Monte Carlo simulation, many studies have shown that the type of
feed appears to be strongly associated with the presence of Salmonella spp.. For example,
Cook and Miller (2005) reported that farms feeding home-mixed rations had a lower
seroprevalence of Salmonella spp. (OR = 0.77) in a study including 1,806 farms. On the other
hand, Harris et al. (1997) found a higher prevalence of Salmonella spp.-contaminated
homemade feed than purchased feed on farm. The quality and hygiene of homemade feed
might vary in the studies, and furthermore, Harris et al. (1997) investigated only 30 farms.
Purchased feed might constitute a risk of introducing Salmonella spp. in the herd. The
importance of the risk factor feed could be confirmed in the present study.
Another risk factor is dust. It can be responsible for re-infection of cleaned and disinfected
barns because the pathogen is able to survive in dust at room temperature for four years
(Selbitz, 2002). In the present study, dust had a higher influence on the prevalence in fattening
pigs than rodents, stressing the fact that strict cleaning of barns is a basis for good health
management.
The immunity scenario showed that the immunisation of sows is an opportunity for
Salmonella spp. abatement. The Salmonella-Typhimurium-alive vaccine is well established
and effective due to the fact that 70% of Salmonella infections in pigs are related to S.
Typhimurium (Enneking, 2005). In this scenario, immunisations are the preferable method of
reduction of infections. In practice, in most cases these measures are not economically
justifiable and only appropriate in problem herds.
68
The results of the simulation show that the purchase of pathogen-free gilts is only reasonable
with the simultaneous improvement of hygiene and management conditions.
The presented Monte Carlo simulation takes into consideration the multi-factorial sources of
Salmonella spp. infection. In order to control Salmonella spp. in pigs, quantified possible risk
factors are needed to develop effective management strategies in pig herds (Zheng, et al.
2007). Additionally the simulation study indicated that most single intervention and control
measures are not effective enough to reduce or remove a Salmonella spp. infection or
contamination from a herd. It is therefore recommended that a herd-specific intervention and
control strategy be formulated, based on a combination of measures which are both practically
and economically feasible in a herd. A multi-factorial infection such as a Salmonella spp.
infection requires a multi-level approach of intervention and control, i.e. between and within
herds, as well as between and within pigs. The results from the presented study suggest that
improvements to all steps from stable to table need to be considered, and the most
economically optimal solution should be chosen. To identify this, an economic optimisation
model should be carried out, probably individually for each production stage.
5.
Conclusion
A stochastic state-transition simulation model was established to gather further information
about the influence of the risk factors at the different pig production stages on the Salmonella
spp. prevalence in fattening pigs.
risk factors had the highest influence on the prevalence of Salmonella spp.. The risk factor
‘farmer’ represented an exception as the influence of this factor was higher in the rearing unit.
The distribution over management interventions in the finishing stages was in the following
order: farmer, feed, dust and rodents. Immunisation against Salmonella spp. in sows
represents a good strategy to decrease the prevalence in the fattening unit. The results of this
simulation emphasise once more the outstanding importance of optimised hygiene
management.
69
Acknowledgements
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Quante, U., 2000. Untersuchungen zum Vorkommen von Salmonellen bei Zuchtschweinen.
(Diss. med. vet.). Tierärztl. Hochschule Hannover.
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Prevalence of subclinical Salmonella enterica infection in Danish finishing pig herds.
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72
GENERAL DISCUSSION
Introduction
Pork can be regarded as an important source for food-borne campylobacteriosis, yersiniosis
and salmonellosis. All these agents are carried by pigs without any clinical signs, food
products represent a potential source of human infections. In order to control these pathogens
in pigs a quantification of possible risk factors and the development of effective management
strategies in pig herds is needed. The aim of the present thesis was to contribute to a better
understanding of these bacterial pathogens causing disease both in humans and animals and to
use this information to assess and manage the risk to animals and humans.
A purpose of this thesis was to increase the knowledge about the epidemiology of the
occurrence of Campylobacter spp. and Yersinia spp. in farrowing and fattening herds with
particular emphasis on bacteriological findings. Analysis of the data from questionnaires
provided first indications of factors which may influence the prevalence of Campylobacter
spp. and Yersinia spp. in herds.
Another objective of this thesis was to gain insight into the epidemiological effects of
different strategies in the farrowing and finishing units to improve the food safety of pork
with respect to the prevalence of Salmonella spp. in finishing pigs. Therefore a stochastic
transition model was designed depending on farm size, prevalence in the population, rearing,
infection risks, the immunisation schedule of sows and the purchase of pathogen-free gilts.
The simulation model generates an integrated pig production chain with linkages between the
stages farrowing, rearing and fattening with Monte Carlo methods.
The outline of the GENERAL DISCUSSION is focused in the first section on the results from the
bacteriological analysis of Campylobacter spp. and the indicated risk factors. In the second
section, the main emphasis is laid on the prevalence of Yersinia spp. and in the third section
on the different measures to prevent the spread of Salmonella spp. simulated with a stochastic
transition model.
Campylobacter spp.
The results from the thesis (CHAPTER TWO) prove that Campylobacter spp. are of increasing
importance in farrowing and fattening units. High prevalence of Campylobacter spp. were
found in suckling (80.9%), growing (89.2%) and finishing pigs (64.7%). Other studies also
confirm these results (Görgen et al., 1983; Weijtens et al., 1993; Gaull, 2002).
73
In the farrowing unit the prevalence of piglets (80.9%) was very high compared with the
prevalence of sows (33.8%). One explanation could be the stable gut flora from older animals.
The same effect was observed by Weijtens et al. (2000). They described a sow herd with a
minor Campylobacter spp. status (0-22% during 22 month). This farm started breeding with
SPF-animals (specific pathogen-free), but the hygienic regime was not strict enough to avoid
pathogen contamination. However, the prevalence remained at a low level.
The main infection route is the transmission from animal to animal. Gaull (2002) showed that
an infection from sow to piglet is possible, showing 100% prevalence in piglets within 24
hours after birth. This fact cannot be confirmed however. On the basis of the results from the
present thesis, it becomes obvious that there is no relationship between infected sows and the
infection of their piglets with Campylobacter spp.. This fact clarifies that sampling of sows
alone is useless without taking the piglets into account.
On the basis of the results in the fattening unit, it becomes obvious that a stable gut flora from
older pigs can cause a decrease in prevalence (89.2% vs. 64.7%). Other studies e.g. from
Weijtens et al. (1993; 1999) confirm this effect.
Furthermore, it could be noticed that in every herd in the fattening unit Campylobacter spp.
excretion was intermittent. This path of excretion was described in other studies, too (Gaull,
2002; Kasimir, 2005). The occasionally pathogen-free status and the following re-infection
could be one explanation for these effects. Weijtens et al. (1999) stated that the pigs are not
pathogen-free when there is no detection rate. They suspected that the pathogen further
existed in the intestinal villi.
A total pathogen eradication in pig herds seems to be utopian, however for chicks several
studies and strategies for pathogen reduction have been described (Kasimir, 2005).
Immunisation seemed to be successful (Rice et al., 1997). Another opportunity for chicks is
Competitive Exclusion. There are no studies on Competitive Exclusion in pigs, but this
method may be successful in that species, too (Weijtens, 1996). As an alternative, Weijtens et
al. (2000) demonstrated that it is possible to keep Campylobacter spp. at a low level or to
arrange a pathogen-free pig herd. The principle is based on Campylobacter spp.-free sows
(from specific pathogen-free herds) in solidly cleaned and disinfected cots, which have been,
when possible, vacant for some time. Sows are, as a result of their robust gut flora, less
susceptible for the pathogen compared to piglets. Additionally, frequently practised housing
in crates prevents coprophagy. The negative sows cannot infect their piglets.
Despite the high prevalence in the faeces, low detection rates on carcasses between 2.9% and
36.5% are described in the literature (Nesbakken et al., 2002; Pearce et al., 2003; Kasimir,
74
2005). In the present thesis, the detected Campylobacter spp. prevalence decreased from
55.7% in the lairage to over 19.7% on the carcasses before chilling to 0% after twelve hours
chilling. In most of the literature, Campylobacter spp. is mostly not detectable after chilling,
too (Chang et al., 2003; Pearce et al., 2003). Other studies have shown that after chilling
equally high prevalence are possible. For example, Gebreys et al. (2003) isolated
Campylobacter spp. from 29% of the carcasses after chilling. It is known that Campylobacter
spp. can survive the chilling process on chicken skin because the skin is sulcate, clammy and
the follicles feature the opportunity to survive it (Kasimir, 2005). A high prevalence of
Campylobacter spp. on pig carcasses is implausible because pig skin with its relatively flush
surface wipes off during the chilling process.
For consumer protection purposes it is noteworthy that in the present project C. coli was
isolated from one liver sample only.
Besides C. coli, C. jejuni were laboratory-confirmed in this examination. The isolation of C.
jejuni from pig samples has been described by other studies as well. For example, Stich-Groh
(1982) and Young et al. (2000) identified 23.4% and 76.3% respectively, Campylobacter spp.
as C. jejuni. In these assays, hippurathydrolysis served as a confirmation method. This
technique is based on the ability of C. jejuni to hydrolyse hippurat, a biochemical reaction C.
coli is not capable of. One major problem of this method is the possible loss of this ability
during the life span of C. jejuni, causing false positive results with regard to C. coli. But it can
be possible that in some farms or in some geographical regions C. jejuni is described as
common in pigs (Kasimir, 2005).
As a result of the small sample size in the farrowing unit (CHAPTER THREE) it was not
possible to perform a risk analysis which yielded significant conclusions in this production
stage. Thus, further risk factors for the occurrence of Campylobacter spp. in fattening units
should be observed via environmental and feed samples from the checked herds and
questionnaires in the corresponding pig farms. Neither in the feed nor in the environmental
samples was Campylobacter spp. detected. In the fattening stage, the following risk factors
had a significant effect (p≤0.05) on Campylobacter spp. prevalence: sampling time, number
of fattening places per herd, mixed farming, floor space design, feed origin, antibacterial and
anthelmintic treatment. These results show that housing and management have a possible
influence on Campylobacter spp. prevalence and should be investigated further. Weijtens et
al. (2000) found out that feed, water and biotic vectors including humans are permanent risk
factors for piglets. As a result of the low moisture content, feed can be excluded as a risk
factor (Altekruse and Swerdlow, 2002). The risk of introducing the pathogen via water can be
75
reduced by using chlorinated water. The combination of keeping away birds, rodents and
insects with a strict hygiene management routine should prevent or at least limit the risk
factors at the farrowing and fattening units. Furthermore, Kasimir (2005) found that the age of
the cots and the corresponding infection-pressure have no influence on pathogen incidence.
Recapitulating, it can be mentioned that many facts are known about Campylobacter spp.
epidemiology. It seems to be possible to hold the pathogen prevalence at a low herd level.
Other methods to create a pathogen-free herd with SPF-animals (specific pathogen-free) and
with a really strict hygiene regime are associated with high costs for the farmers. Because of
the probably low impact on human health, such arrangements, such as herd decontamination,
make no sense. Against this background, the discussion of general Campylobacter spp.
abatement is essential, especially with regard to effective preventive adoption at a certain
stage of the production chain. One point speaking against such an implementation is the fact
that human campylobacteriosis is caused by C. jejuni in only 90% of cases. Only 5% to 10%
of the cases are caused by C. coli (Tam et al., 2003). The main source for C. jejuni is chicken
meat, while the infection source for human C. coli-infection is unclear. This pathogen is often
isolated from pigs but also from turkey hens (Kramer, 2000). Despite the high isolation rate in
pig tonsils and faeces samples, pork (besides offal) is hardly contaminated with
Campylobacter spp.. One reason for this is the effective chilling of the carcasses in
combination with drying the skin after slaughtering. Campylobacter infections are often
sporadic single-diseases, so the search for the infection source is very difficult.
The advantage of abatement is the reduction of the potential health risk for humans, because
at the moment it cannot be estimated how often the VBNC status (viable-but-not-cultivable)
is present on the carcasses and in the meat. Further studies are urgently needed to gather
further information on the VBNC mechanism of Campylobacter spp..
With regard to Campylobacter spp., consumer education is important. There is a crosscontamination risk from chicken and maybe from pig meat in combination with bad kitchen
hygiene because the infection dose is very low with 500 to 800 pathogens (Black et al., 1988).
Yersinia spp.
Yersinia spp. seems to play a negligible role in farrowing herds because neither in suckling
piglets nor in sows was the pathogen detected. This is in accordance with another study
detecting Yersinia spp. only during the fattening period but not in sows and piglets (Kasimir,
2005). Whereas Korte et al. (2004) in contrast reasoned from their study that sows are an
important infection source for the pig herd.
76
The fact that Y. enterocolitica was not isolated in the farrowing unit but could not be isolated
until the beginning of the fattening period is evidence that the cause of infection has to be
looked for in the fattening unit. In this production stage, the prevalence of Y. enterocolitica
were between 0% and 46.9%. Bush et al. (2003) detected 12.8% Y. enterocolitica in 2,664
faecal samples and Kasimir (2005) described isolation rates between 0% and 65.4%. The
prevalence at farm level arranged variably. Some farms had a prevalence of 0% at the
beginning of fattening period and at the end nearly 100% or vice versa. It is ambiguous as to
why the pathogen diffuses in some herds at a high level and not in other herds in turn,
although some pigs are infected there, too. It is described in the literature that the pathogen
can only be separated in a certain period after infection (Nielsen et al., 1996). Furthermore, a
re-infection of the pigs is impossible, because of the gut-generated immunity (Fukushima,
1983). This is the reason why the prevalence decreased from the first (15.2%) to the second
(13.3%) sample time in the fattening unit.
The prevalence of Yersinia spp. in the slaughterhouse was low (lairage: 5.7% vs. before
chilling: 0.8%). One reason for this effect is that Yersinia spp. persists in the tonsils and will
be shed with the faeces discontinuously. Anderson (1988) described the influence of different
eviscerate techniques in relation to carcass contamination in the slaughterhouse. By the
manual gut cut down, he found on the medial hind leg significantly more (26.3%) Yersinia
enterocolitica O:3 than by the use of the bung cutters (13.4%). The contamination was lowest
when behind the bung cutter the rectum was closed with a plastic bag. Nesbakken et al.
(1994) produced similar results. The faeces has no influence on carcass contamination.
Bornadi et al. (2003) could not isolate Yersinia spp. on 150 carcass samples while the rectum
was not closed with a plastic bag. The detection rate in the faeces was very low with 4.0%.
The tonsils contaminate the carcasses only marginally. Of higher significance is the
contamination of the pluck per tonsils (Fredriksson-Ahomaa et al., 2001). The authors found
that the pluck had a higher prevalence than the kidney.
Neither in the environmental nor in the feed samples were Yersinia spp. isolated. One reason
therefore can be found in the method of detection. Especially for environmental and animal
feed samples, the cultivation method seems to be inferior compared to Polymerase-ChainReaction (PCR), because the low numbers of pathogenic strains in these samples can often be
suppressed by a distinct satellite flora (Fredriksson-Ahomaa and Korkeala, 2003).
Yersinia spp. is only sporadically found in meat samples. One reason is that it is not easy for
the pathogen to flourish against the natural meat micro-flora. But the pathogen is able to
survive in raw pig meat for a long time (Fukushima and Gomyoda, 1986). A higher risk factor
77
is offal. Bucher et al. (2001) were able to isolate Yersinia enterocolitica 4/O:3 from 75% of
tongues, 70% of hearts and 25% of livers. When these contaminated offal are further
processed at home and the knives or the workplace are not cleaned correctly, the carry-over
risk to other food exists.
As a result of the small pathogen detection rate in the farrowing and fattening unit it was not
possible to perform a risk analysis which yielded significant conclusions. But in the literature
there is research about the risk factors. For example, a Norwegian study about risk factors of
Yersinia spp. in pig production shows that herds with only fattening pigs have a higher
prevalence than farrowing-to-finishing herds (Skjerve et al., 1998). The purchase of animals
and the associated animal assortment are the highest risk factor for pathogen diffusion in the
herd. Also cats and straw litter raise the infection risk. A pathogen decrease was realised with
low-pressure aeration, hygienic methods such as a disinfected mat in the entrance area and
feeding per hand. When the pathogen is in the herd it is persistent. It is not really known how
eradication methods have an influence of Yersinia status. The elimination from carrieranimals inside a herd is not effective (Skjerve et al., 1998). During 2001, a Swiss study dealt
with the prevalence of Yersinia spp. in pork herds with different animal husbandries. In this
case, the application of medicine feed as a prophylaxis for pigs at the beginning of the
fattening period was a high risk factor for occurrence of Yersinia spp. in the herd
(Ledergerber et al., 2003). In a Canadian study, 1,944 environmental samples were analysed
(Pilon et al., 2000). From only 17 (0.6%) could Yersinia spp. be isolated. Per farm only one
genotype was isolated. Because of this fact the authors came to the conclusion that external
causes of a pathogen risk factor are only of little importance. Pathogen isolation from
environmental samples is very difficult, because the pathogen concentration is very low and
the concentration of company flora is very high (Fredriksson-Ahomaa and Korkeala, 2003).
In conclusion, knowledge about the epidemiology of Yersinia spp. is currently very limited.
Concrete arrangements do not exist, but the purchase of pigs from different herds, the
application of herd-specific vaccination in problem herds and the forceful compliance of
hygiene methods seem to be steps into the right direction. A monitoring implementation can
help define high-contaminated herds from low-contaminated. The main focus has to be placed
on the slaughterhouse. Herds with a high prevalence should be slaughtered separately at the
end of a slaughter day and their co-products should only be brought to the market heattreated. Furthermore, the slaughter technique discontinuing the had completely with tongue
and tonsils, is a preventive method (Christensen and Lüthje, 1994). Likewise, the
improvement of hygiene standards at the slaughterhouse is very important for a generation of
78
safety food. Regular education is important to improve the hygienic awareness of the
assistants (Bucher, 2001).
In addition, consumers have to be educated about the contact risk of pig meat, mainly offal.
Especially the risk from cross-contamination in their own kitchens is often underestimated.
Stochastic transition model for the epidemiology of Salmonella spp. in the pork supply
chain
Besides the importance of Salmonella spp. for public health, another aspect is the cost
generated by human salmonellosis. A working document of the European Commission
estimated that costs linked to food-borne salmonellosis ranged between 560 millions and € 2.8
billion in Europe, where Salmonella spp. was estimated to be responsible for nearly 166,000
cases in 1999 (Anonymous, 2001). However, indirect incentives such as the increased interest
in food safety and the large competition on the (international) market for pork, are of
increasing importance, since 1.25 million tons of pork are exported annually (ZMP, 2007).
Therefore, it is important to obtain more insight into the trade-off between prevalence
reduction and associated costs. Currently, the most common perspective on food safety and
human salmonellosis is the stable-to-table concept, acknowledging that each link in the food
production chain has a share in the responsibility of reducing the risk of food-borne disease.
Hence, for an effective control resulting in a satisfying reduction in the end product, the entire
supply chain must be involved (Lammerding and Fazil, 2000).
The presented thesis (CHAPTER FOUR) includes an approach for possible measures that can be
implemented in the farrowing and fattening unit to control the introduction and reduce the
prevalence of Salmonella spp. in finishing pigs. A stochastic state-transition simulation model
was established to gather further information about the influence of the risk factors in the
different pig production stages on the Salmonella spp. prevalence in fattening pigs.
Furthermore, the influence of preventive arrangements of the immunisation of sows, and
additionally, of pathogen-free purchased gilts on the Salmonella spp. prevalence in the
farrowing and fattening unit were determined. The application of risk analysis methods in the
assessment of microbial contamination of foods is relatively new. It offers a potential
overview of the interrelationship between the different processes which influence the
contamination of food items. This is in contrast to more specific detailed experiments which
only provide information about selected area. However, risk analysis models depend on data
preferably from such studies, in order to provide reliable estimates. All models are reduced
79
explanations of the real world. The more sophisticated the model, the more precisely the real
world may be explained.
The results in the present thesis showed that preventive measures must be affected in the
fattening unit because at this production stage the risk factors have the highest influence on
the prevalence of Salmonella spp.. Van der Gaag et al. (1999) identified the fattening farm as
the most important stage to achieve a reduction in Salmonella spp. prevalence, too.
There are several ways to reduce the Salmonella prevalence in a herd. For example, changes
in feeding practise, installation of adequate rodent control and improvements in hygiene
(Alban and Stärk, 2005). The model simulated the following distribution over management
interventions to reduce the prevalence of Salmonella spp. in fattening pigs: farmer (p-value:
0.0004-0.0443), feed (p-value: 0.03-0.46), dust (p-value: 0.33-0.66) and rodents (0.71-0.92).
Immunisation against Salmonella spp. in sows results in a good effect on the prevalence
reduction in the pig production. The exact quantitative effects of separated interventions on
the introduction and spread of Salmonella spp. and the course of infection are very difficult to
quantify precisely. Still, it is known that a package of multiple interventions leads to a
reduction of Salmonella spp. prevalence (Bagger and Nielsen, 2001).
In conclusion, the (pre-) harvest stages of the pork supply chain cannot ensure a zero
prevalence of contaminated carcasses (van der Gaag, 2004). Thus, the next stages (processing,
storage at retail and storage and preparing the pork by the consumer) are also important. For
instance, the consumer can reduce the risk of food-borne salmonellosis by cool storage and
thorough heating of the pork and avoiding cross-contamination in the kitchen (Gorman et al.,
2002). Nevertheless, by reducing the prevalence of contaminated carcasses, the risk for the
consumer should be decreased since less contaminated pork enters the consumer’s kitchen.
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Luchansky, J.B., 2003. Prevalence of Campylobacter within a swine slaughter and
processing facility. J. Food Prot. 66, 1550-1556.
Pilon, J., Higgins, R., Quessy, S., 2000. Epidemiological study of Yersinia enterocolitica in
swine herds in Quebec. Can. Vet. J. 41, 383-387.
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jejuni in broiler chickens: colonization and humoral immunity fallowing oral
vaccination and experimental infection. Vaccine 15, 1922-1932.
Skjerve, E., Lium, B., Nielson, B., Nesbakken, T., 1998. Control of Yersinia enterocolitica in
pigs at a herd level. Int. J. Food Microbiol. 45, 195-203.
Sticht-Groh, V., 1982. Campylobacter in healthy slaughter pigs: a possible source of infection
for man. Vet. Rec. 110, 104-106.
Tam, C.C., O’Brien, S.J., Adak, G.K., Meakins, S.M., Frost, J.A., 2003. Campylobacter coli –
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van der Gaag, M.A., Backus, G.B.C., Hurine, R.B.M., 1999. Epidemiological and economic
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WA, USA, 231-236.
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84
GENERAL SUMMARY
This thesis focuses on information about the prevalence and origins and preventive measures
of the important zoonotic pathogens Campylobacter spp. and Yersinia spp. in the different
stages of the pig production chain. Furthermore, the epidemiological effects of different
strategies in the farrowing and finishing units with respect to the prevalence of Salmonella
spp. in finishing pigs were evaluated by simulation.
CHAPTER ONE summarises several studies emphasising the importance of Campylobacter
spp. and Yersinia spp. as widespread pathogens in the pig production chain.
First, the taxonomy and the pathogen character of these internationally important pathogens
are described, and second, prevalence in the pig production is reported. Obviously, pigs are
often carriers of Campylobacter spp. and Yersinia spp. causing infections in humans.
Contamination during the slaughtering process is possible.
However, pathogenic Campylobacter spp. and Yersinia spp. are comparatively infrequently
isolated from meat. A greater health risk is represented by entrails. In conclusion, to increase
pork safety, further epidemiological studies are urgently needed to determine the origin of
pathogens and to take counteractive measures.
The objective of CHAPTER TWO was to determine the prevalence of Campylobacter spp. and
Yersinia spp. in a total of 1,040 faecal samples taken from animals at different ages from four
farrowing and twelve fattening herds. In the farrowing unit, faeces were collected from 68
sows (faecal samples) and 256 suckling piglets (rectal swab samples). Further samples were
collected from 362 growing and 354 finishing pigs (rectal swab samples). Additionally, 56
feed and environmental samples were collected. During the slaughtering process, 122 pigs
and their carcasses respectively were sampled three times. First, rectal samples were taken
with swabs during the lairage. Second, the samples were taken from the carcass before
entering the chilling room. The same method was repeated in the chilling room twelve hours
after starting the chilling. Finally, 86 raw meat samples were taken from 34 retail stores.
Campylobacter spp. were isolated in sows (33.8%), piglets (80.9%), growing (89.2%) and
finishing (64.7%) pigs. Yersinia spp. were detected in growing (15.2%) and finishing (13.3%)
pigs only.
85
During lairage, Campylobacter spp. were identified from pig faeces from all farms whereas
Yersinia spp. were detected in pigs from just two herds. After twelve hours of chilling neither
Campylobacter spp. nor Yersinia spp. were detected.
In raw meat samples, Campylobacter spp. were isolated from one liver sample and Yersinia
enterocolitica from two meat samples (mince and cutlet).
Common slaughter techniques and hygiene procedures may be effective tools to reduce the
risk of contamination and recontamination of meat products since Campylobacter spp. and
Yersinia spp. were found only sporadically in raw meat samples.
The aim of CHAPTER THREE was to gather further information about the sources of infection
with Campylobacter spp. and their qualitative and quantitative importance in pig production.
For statistical analysis, 1,040 results from the bacteriological examination for Campylobacter
spp. were evaluated with questionnaires from four farrowing and twelve fattening units. The
prevalence was determined via faeces and swab samples with regard to certain farm
production parameters.
Thereby, 30.8% of the sows and 80.9% of their piglets were carriers of Campylobacter spp..
In the fattening unit, the prevalence at the beginning of the fattening period was 89.2% and at
the end 64.7%.
As a result of the small sample size in the farrowing unit, it was not possible to perform a risk
analysis which yielded significant conclusions.
In the fattening stage, the following risk factors had a significant effect (p≤0.05) on
Campylobacter spp. prevalence: sampling time, number of fattening places per herd, mixed
farming, floor space design, feed origin, antibacterial and anthelmintic treatment. These
results show that housing and management have a possible influence on the Campylobacter
spp. prevalence and should be investigated further.
In CHAPTER FOUR the objective was to gain insight into the epidemiological effects of
different strategies in the farrowing and finishing units to improve the food safety of pork
with respect to the prevalence of Salmonella spp. in finishing pigs.
Therefore a stochastic transition model was designed depending on prevalence in the
population (sows = 0.5% to 65%; rearing pigs = 2% to 95%), infection risks (farmer = 0% to
10%; rodents = 0% to 5%; feed = 0% to 10%; and dust = 0% to 5%), the immunisation
schedule of sows (yes/no) and the purchase of pathogen-free gilts (yes/no).
86
The simulation model generated an integrated pig production chain with linkages between the
stages farrowing, rearing and fattening. Within each herd, dynamic patterns of Salmonella
infections were simulated. The simulation covered a time interval of 24 months.
risk factors had the highest influence on the prevalence of Salmonella spp..
The risk factor ‘farmer’ represented an exception as the influence of this factor was higher in
the rearing unit (22.8% vs. 17.1%). The distribution over management interventions in the
finishing stages was in the following order: farmer (p-value: 0.0004-0.0443), feed (p-value:
0.03-0.46), dust (p-value: 0.33-0.66) and rodents (p-value: 0.71-0.92). Immunisation against
Salmonella spp. in sows represents a good strategy to decrease prevalence of Salmonella spp.
in the fattening unit.
87
88
ZUSAMMENFASSUNG
Die Ziele der vorliegenden Arbeit bestanden zum Einen aus der Erfassung und Bewertung
von Prävalenzen und Eintragsquellen der Zooanthroponosenerreger Campylobacter spp. und
Yersinia spp. in den verschiedenen Produktionsstufen der Schweineerzeugung. Zum Anderen
wurde eine Simulation der Ausbreitung von Salmonella spp. und der Einfluss präventiver
Maßnahmen auf die Prävalenz bei Mastschweinen in Ferkelerzeuger- und Mastbetrieben
vorgenommen.
KAPITEL EINS umfasst eine Literaturübersicht über Campylobacter spp. und Yersinia spp. in
der Schweineproduktionskette. Zunächst wurde die Systematik und die Erregereigenschaften
dieser zwei weltweit bedeutenden Zooanthroponoserreger dargestellt. Im Anschluss wurden
die bisher festgestellten Prävalenzen in der Produktionskette beim Schwein aufgezeigt. Es
wird deutlich, dass Schweine häufig Träger humanpathogener Campylobacter spp. und
Yersinia spp. sind und somit eine Kontamination ihres Fleisches während des
Schlachtprozesses möglich ist. Allerdings sind humanpathogene Campylobacter spp. und
Yersinia spp. relativ selten im Fleisch nachweisbar. Eine größere Gefahr stellen Innereien dar.
Zur Sicherung der hygienischen Unbedenklichkeit von Schweinefleisch sollte in Zukunft
versucht werden, die Epidemiologie der Erreger genauer aufzuklären um die Ursache der
Erregerausbreitung zu erkennen und geeignete Gegenmaßnahmen ergreifen zu können.
KAPITEL ZWEI zeigt die ermittelten Prävalenzen von Campylobacter spp. und Yersinia spp.
aus insgesamt 1.040 Kotproben von Tieren unterschiedlichen Alters auf vier Ferkel- und
zwölf Mastbetrieben. In der Ferkelerzeugung wurden 68 Sauen (Kotproben) und 256 Ferkel
(rektale Abstrichtupferproben) beprobt. Weitere Proben wurden von 362 Schweinen am
Mastanfang und 354 Schweinen am Mastende (rektale Abstrichtupferproben) entnommen.
Zusätzlich wurden 56 Futter- und Umweltproben gesammelt. Während des Schlachtprozesses
wurden 122 Schweine und ihre Schlachtkörper insgesamt dreimalig beprobt. Zuerst wurden
rektale Abstrichtupferproben im Wartebereich entnommen. Die zweite Beprobung erfolgte
am Schlachttierkörper direkt vor der Kühlung und noch einmal nach 12 Stunden Kühlung. In
34 Verkaufsstätten wurden abschließend 86 rohe Fleischwarenproben erworben und beprobt.
Campylobacter spp. wurden in Sauen (33,8%), Saugferkeln (80,9%), Schweinen am
Mastanfang (89,2%) und Mastschweinen am Mastende (64,7%) nachgewiesen. Yersinia spp.
wurden nur bei Schweinen am Anfang (15,2%) bzw. am Ende der Mastperiode (13,3%)
89
analysiert. Im Wartebereich des Schlachthofes wurde Campylobacter spp. in Kotproben von
allen Mastbetrieben nachgewiesen, wohingegen Yersinia spp. nur in Schweinen von zwei
Betrieben entdeckt werden konnten. Nach zwölf Stunden Kühlung wurden weder
Campylobacter spp. noch Yersinia spp. nachgewiesen. In den rohen Fleischwarenproben,
wurden Campylobacter spp. in einer Leberprobe analysiert und Yersinia spp. von zwei
Fleischproben (Hackfleisch und Schnitzel).
Anscheinend sind die gebräuchlichen Schlachttechniken und Hygieneprozeduren effektiv
genug um das Risiko einer Kontamination bzw. Rekontamination von Fleischprodukten zu
reduzieren, da die Erreger nur sporadisch in den Fleischproben nachgewiesen werden
konnten.
KAPITEL DREI sollte zur Aufdeckung produktionsspezifischer Risikofaktoren und ihrer
qualitativen und quantitativen Bedeutung beitragen. Für die statistische Analyse wurden 1.040
Ergebnisse der bakteriologischen Untersuchung auf Campylobacter spp. im Zusammenhang
mit den Informationen aus einem Fragebogen aus vier Ferkelerzeuger- und zwölf
Mastbetrieben ausgewertet. Die Prävalenzen des Erregers wurden mit Hilfe von Kot- und
Abstrichtupferproben vor dem Hintergrund verschiedener Betriebsbedingungen ermittelt.
Dabei wurden bei 33,8% der Sauen und bei 80,9% der Ferkel Campylobacter spp.
nachgewiesen. In der Produktionsstufe Mast betrug die Prävalenz am Mastanfang 89,2% und
am Mastende 64,7%. Aufgrund des geringen Datenmaterials konnte auf der Produktionsstufe
Ferkelerzeugung keine Risikoanalyse durchgeführt werden.
Folgende Faktoren hatten auf den Mastbetrieben einen signifikanten Einfluss (p≤0,05) auf die
Campylobacter spp. Prävalenz: Zeitpunkt der Probeentnahme, Anzahl Mastplätze,
Mischbetrieb, Bodengestaltung, Futterherkunft, Einstallbehandlung und anthelminthische
Behandlung. Die Ergebnisse veranschaulichen, dass eine Reduzierung der Campylobacter
spp. Prävalenz durch betriebliche Haltungs- und Managementfaktoren möglich ist. Aus diesen
Ergebnissen resultiert weiterer Forschungsbedarf.
Ziel des KAPITEL VIER war es, einen Einblick in die epidemiologischen Effekte
verschiedener Strategien zur Qualitätssicherung in Ferkel- und Mastbetrieben und deren
Einfluss auf die Salmonellenprävalenz bei Mastschweinen zu gewinnen.
Dafür wurde ein stochastisches Simulationsmodell in Abhängigkeit der Populationsprävalenz
(Sauen: 0,5% bis 65%; Läufer: 2% bis 95%), des Infektionsrisikos (Betreuungspersonal = 0%
bis 10%; Schadnager = 0% bis 5%; Futter = 0% bis 10% und Staub = 0% bis 5%), der
90
Impfung der Sauen (ja/nein) und dem Zukauf pathogen-freier Jungsauen (ja/nein) konstruiert.
Das Simulationsmodell generiert ein integriertes Produktionssystem beim Schwein mit den
Stufen Ferkelerzeugung, Aufzucht und Mast über einen Zeitintervall von 24 Monaten.
Die vorliegende Studie zeigt, dass präventive Maßnahmen zuerst in der Mast erfolgen
müssen, da dort die größten Effekte auf die Salmonellenprävalenz erzielt wurden. Der
Risikofaktor Betreuungspersonal bildete dabei eine Ausnahme, da er im Flatdeckbereich eine
höhere Prävalenz bei den Mastschweinen verursachte (22.8% vs. 17.1%).
Die Aufteilung der Managementmaßnahmen in der Mastschweineproduktion wurde in
folgender Reihenfolge vorgenommen: Betreuungspersonal (p-Wert: 0.0004-0.0443), Futter
(p-Wert: 0.03-0.46), Staub (p-Wert: 0.33-0.66) und Schadnager (p-Wert: 0.71-0.92). Die
Immunisierung
der
Sauen
gegen
Salmonella
prävalenzreduzierend.
91
spp.
wirkten
im
Mastbereich
DANKSAGUNG
An dieser Stelle möchte ich mich bei den Menschen bedanken, die zum Gelingen dieser
Arbeit beigetragen haben.
Ich danke Herrn Prof. Dr. Joachim Krieter für die Überlassung des Themas, die Unterstützung
bei der Abfassung der Dissertation sowie für die Möglichkeit, meine Ergebnisse auf
unterschiedlichen Tagungen im In- und Ausland vorzustellen.
Herrn Prof. Dr. Edgar Schallenberger danke ich für die Übernahme des Koreferats.
Frau Priv. Doz. Dr. Elisabeth grosse Beilage von der Außenstelle für Epidemiologie der
Tierärztlichen Hochschule Hannover möchte ich für die hilfreiche Beratung und für die
Bereitschaft zum Korrekturlesen danken.
Ein besonders großes Dankeschön geht an Frau Dr. Nicole Kemper für ihre Hilfsbereitschaft
und Unterstützung, der ständigen Bereitschaft zum Korrekturlesen und ihrer wertvollen
Anregungen bei der Anfertigung dieser Arbeit.
Der Vermarktungsgemeinschaft für Zucht- und Nutzvieh (ZNVG, Neumünster) danke ich für
die Unterstützung bei der Auswahl der Betriebe.
Allen Landwirten und dem Schlachthof Jensen (Oldenburg i.H.) möchte ich herzlich für die
Teilnahme an der Untersuchung danken. Die unkomplizierte Art und Hilfsbereitschaft lassen
mich die Besuche auf den Höfen in guter Erinnerung behalten.
Das Projekt wurde ermöglicht durch die finanzielle Förderung der H. Wilhelm Schaumann
Stiftung, dem Ministerium für Soziales, Gesundheit, Familie, Jugend und Senioren des
Landes Schleswig-Holstein und der Arbeitsgruppe Lebensmittelqualität und -sicherheit
(QUASI) der Agrar- und Ernährungswissenschaftlichen Fakultät der Christian-AlbrechtsUniversität zu Kiel, denen ich herzlich danke.
Für die schöne Zeit am Institut, dem guten und freundschaftlichen Arbeitsklima danke ich
allen Kollegen. Besonders möchte ich meinen „Containerkollegen“ danken, allen voran Lotti,
Imke und Diane. Danke, dass ich mit meinen Sorgen und Nöten bei euch immer auf offene
Ohren gestoßen bin und Danke für das freundschaftliche Verhältnis und die moralische
Unterstützung.
Der größte Dank gilt meiner Familie, die es mir durch ihren Rückhalt und ihrem
entgegengebrachten Verständnis ermöglicht hat, meine Promotion erfolgreich zu beenden.
LEBENSLAUF
Name:
Tanja Wehebrink
Geburtsdatum:
01.05.1978
Geburtsort:
Rahden
Staatsangehörigkeit:
deutsch
Familienstand:
ledig
Eltern:
Heinz Wehebrink, Inge Wehebrink (geb. Timm)
Schulbildung:
1984 – 1988
1988 – 1994
1994 – 1997
Grundschule Varl
Freiherr-vom-Stein-Realschule, Rahden
Söderblom Gymnasium, Espelkamp
Abschluss: Allgemeine Hochschulreife
Berufsausbildung:
1997 – 1999
Landwirtin
1997 – 1998
Betrieb Ernst Flömer in Gestringen
(Milchvieh)
Betrieb Friedhelm Lange in Hille
(Ferkelerzeugung u. Mast)
1998 – 1999
Studium:
1999 – 2002
2002 – 2004
Berufliche Tätigkeit:
seit Juni 2004
Studium Agrarwissenschaften
mit der Fachrichtung Tierproduktion an
der Christian-Albrechts-Universität zu
Kiel
Abschluss: Bachelor of Science
Studium Agrarwissenschaften
mit der Fachrichtung Tierproduktion an
der Christian-Albrechts-Universität zu
Kiel
Abschluss: Master of Science
Wissenschaftliche Mitarbeiterin am
Institut für Tierzucht und Tierhaltung der
Christian-Albrechts-Universität zu Kiel
bei Herrn Prof. Dr. Joachim Krieter

campylobacter spp., yersinia spp. and salmonella spp. as zoonotic

Transcription

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