Contribution of meat inspection to animal health surveillance in Sheep ...

Supporting Publications 2012:EN-320

EXTERNAL SCIENTIFIC REPORT The contribution of meat inspection to animal health surveillance1 in Sheep and Goats Prepared by COMISURV2 Represented for the purpose of this report by: Jo Hardstaff, RVC Annette Nigsch, SAFOSO Niko Dadios, RVC Katharina Stärk, SAFOSO Silvia Alonso, RVC Ann Lindberg, SVA

DISCLAIMER The present document has been produced and adopted by the bodies identified above as authors. This task has been carried out exclusively by the authors in the context of a contract between the European Food Safety Authority and the authors, awarded following a tender procedure. The present document is published complying with the transparency principle to which the Authority is subject. It may not be considered as an output adopted by the Authority. The European Food Safety Authority reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors.

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Question No EFSA-Q-2011-01055

Consortium including the National Veterinary Institute (SVA) Sweden, Safe Food Solutions inc.(SAFOSO) Switzerland, French Agency for Food, Environmental and Occupational Health & Safety (ANSES) France, Federal Institute of Risk Assessment (BfR) Germany, Royal Veterinary College (RVC) the United Kingdom

Any enquiries related to this output should be addressed to [email protected] Suggested citation: Hardstaff, J., Nigsch, A., Dadios, N., Stärk, K., Alonso, S., Lindberg, A.; Contribution of meat inspection to animal health surveillance in sheep and goats. Supporting Publications 2012:EN-320. [43 pp.]. Available online: www.efsa.europa.eu/publications

© European Food Safety Authority, 2012

Contribution of meat inspection to animal health surveillance – Sheep and Goats

ABSTRACT The objective of this work was to assist a working group (WG) appointed by the Animal Health and Animal Welfare Panel (AHAW) in the development of generic stochastic and deterministic models of the meat inspection system to investigate the probability of detection of twenty specific diseases and welfare conditions within that system and to compare the effectiveness of abattoir and clinical surveillance. The impact of three post mortem inspection scenarios (current, intermediate and visual only inspection) was investigated. Definitions of mild and typical cases were defined from the literature and clarified through elicitation with three small ruminant experts. The parameter values for models were derived from the literature and from expert elicitation. The probability of detection was assessed for the ante and post mortem components of abattoir inspection for detectable (mild and typical cases) and all (mild, typical and non-detectable) cases and used as inputs to evaluate the effectiveness of slaughterhouse inspections as a surveillance system component. This was established by using two types of scenario tree models: the component sensitivity model (used for exotic diseases) and detection fraction model (used for endemic diseases/welfare conditions). With the visual only inspection of detectable cases, there was a significant drop in detection probability of detectable cases of liver fluke and bovine tuberculosis (bTB) in goats. When all cases were taken into consideration there was no significant reduction in the detection of any diseases or welfare conditions. Surveillance using clinical observations from the field (clinical surveillance) was more effective than surveillance using observations from abattoirs (abattoir surveillance) at detecting FMD and the combined abattoir and clinical surveillance of sheep scab. Abattoir surveillance combined with clinical surveillance was more effective than either surveillance component on its own for detection of liver fluke, lower respiratory infections, and leg and foot disorders. © European Food Safety Authority, 2012

KEY WORDS Meat inspection, small ruminants, ante mortem inspection, post mortem inspection, decision tree model, detection fraction, surveillance sensitivity component


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The present document has been produced and adopted by the bodies identified above as authors. This task has been carried out exclusively by the authors in the context of a contract between the European Food Safety Authority and the authors, awarded following a tender procedure. The present document is published complying with the transparency principle to which the Authority is subject. It may not be considered as an output adopted by the Authority. The European food Safety Authority reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors


SUMMARY The study consists of three stages: ‘stage 1’ covers the identification of diseases and welfare conditions, case definitions and data elicitation. ‘stage 2’ focussed on the detection probability of meat inspection for detectable (typical and mild cases) and non-detectable cases of twenty diseases and welfare conditions selected in stage 1. In ‘stage 3’ the effectiveness of meat inspection was compared with another surveillance component (for the purpose of this report clinical surveillance), taking account of the prevalence of diseases and welfare conditions and risk factors on animal- and herd level. Note that the word surveillance as used in this report does not imply that any action is taken to capture, or act upon, the information. It merely points to the potential of these systems to be used for such purposes. Stage 2 results revealed that ante mortem inspection provides high probability of detection, particularly for welfare conditions, Orf disease and bluetongue (BT). Meat inspection may therefore be important to document the effectiveness of existing control programs. The low probabilities of detection for post mortem inspection of exotic diseases, e.g. foot and mouth disease (FMD), indicated that it may not be suitable for sole detection of these cases. Our results further showed that for the majority of diseases and welfare conditions, the probability of detection would not be critically compromised by a change in post mortem inspection. When both ante- and post-mortem inspection were considered, the probability of detection was high for most diseases and welfare conditions. This is particularly relevant when considering all cases (detectable and non-detectable cases) where the probability of detection levels were generally lower than for detectable only cases and where a change in post mortem protocol made little impact on these values. Stage 3 results showed that clinical surveillance was more effective than abattoir surveillance at detecting at least one case of FMD in populations of ≤1 million sheep. However, for large populations of 10 million animals, abattoir surveillance can be as effective as clinical surveillance. For endemic diseases (liver fluke and lower respiratory diseases) and animal welfare conditions (leg and foot disorders and sheep scab) a combination of the two surveillance components clinical surveillance and meat inspection showed to be more effective in detecting a higher fraction of infected or affected animals than would have been detected with either one of the surveillance component on its own.


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TABLE OF CONTENTS Abstract ............................................................................................................................................... 2 Key words ........................................................................................................................................... 2 Summary ............................................................................................................................................. 3 Table of contents ................................................................................................................................. 4 List of tables ........................................................................................................................................ 6 List of figures ...................................................................................................................................... 7 Background as provided by EFSA ...................................................................................................... 8 Terms of reference as provided by EFSA ........................................................................................... 8 Acknowledgements ............................................................................................................................. 8 Introduction and objectives ................................................................................................................. 9 1. Overall objectives ........................................................................................................................ 9 2. Specific objectives..................................................................................................................... 10 Materials and methods ...................................................................................................................... 11 3. Meat Inspection Scenarios......................................................................................................... 11 4. Stage 1: Diseases and welfare conditions.................................................................................. 12 4.1 Identifying diseases and welfare conditions to be used in the study ...................................... 12 4.2 Case definition development .................................................................................................. 12 4.3 Data collection ........................................................................................................................ 16 4.4 Elicitation of expert opinion ................................................................................................... 16 4.4.1. Questionnaire development .............................................................................................. 17 4.4.2. First elicitation round........................................................................................................ 17 4.4.3. Data collation .................................................................................................................... 17 4.4.4. Second elicitation round ................................................................................................... 17 4.4.5. Final estimates .................................................................................................................. 17 5. Stage 2: The probability of detection at meat inspection .......................................................... 18 5.1 Model implementation ........................................................................................................... 18 5.2 Calculation of probability of detection ................................................................................... 20 6. Stage 3: Modelling the overall surveillance system .................................................................. 21 6.1 Model structure....................................................................................................................... 21 6.2 Model inputs and implementation .......................................................................................... 21 6.3 Detection fraction models....................................................................................................... 23 6.4 Component sensitivity models ............................................................................................... 24 Results ............................................................................................................................................... 26 7. Stage 1: expert elicitation of case types .................................................................................... 26 8. Stage 2 ....................................................................................................................................... 26 9. Stage 3 ....................................................................................................................................... 30 9.1 Detection fraction model ........................................................................................................ 30 9.2 Component sensitivity model ................................................................................................. 30 Discussion ......................................................................................................................................... 31 10. Methodological considerations ............................................................................................... 31 10.1 General considerations ....................................................................................................... 31 10.2 Data availability and quality............................................................................................... 32 10.3 Modelling assumptions....................................................................................................... 32 11. Implications of results ............................................................................................................ 33 11.1 The probability of detection by meat inspection and the effect of changing the post mortem protocol ................................................................................................................................ 33 11.2 The relative contribution of meat inspection to overall disease surveillance ..................... 34 12. Conclusions ............................................................................................................................ 35


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References ......................................................................................................................................... 36 Appendices ........................................................................................................................................ 39 A. Expert elicitation ....................................................................................................................... 39 B. Parameter data from the literature used to parameterise the stage 2 and stage 3 models .......... 40 C Additional output from the stage 2 models - the probabilities of detection for mild and typical cases at ante mortem, post mortem and combined inspection scenarios. .......................................... 41 D. Additional output from the stage 3 models ............................................................................... 42 Glossary and abbreviations ............................................................................................................... 43


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LIST OF TABLES TABLE 1:

inspection requirements for small ruminants according to regulation (ec) no 853/2004 (v: visual inspection, p: palpation and i: incision). .................................. 11

TABLE 2:

list of diseases and welfare conditions in small ruminants identified by the ahaw wg for consideration in the assessment conducted by comisurv. ................................ 12

TABLE 3:

the presentation of mild and typical animal health diseases and welfare conditions at the ante mortem (am) and post mortem (pm) inspection stages. ............................. 13

TABLE 4:

the risk factors selected for stage 3 of the model......................................................... 16

TABLE 5:

nodes considered for inclusion in the stage 3 model for the abattoir surveillance system component. ...................................................................................................... 22

TABLE 6:

nodes considered for inclusion in the stage 3 model for the clinical surveillance system component. ...................................................................................................... 22

TABLE 7:

proportion of detectable (typical or mild) and non-detectable cases by diseases as elicited from the experts. Estimates were provided as ‘minimum’ (min), ‘most likely’ (ml) and ‘maximum’ (max) values................................................................... 26

TABLE 8:

the probability of detection for all detectable cases of diseases and welfare conditions at ante mortem (am), post mortem (pm) (three proposed scenarios) inspection scenarios with the most likely (ml), 5th and 95th percentiles.. .................... 28

TABLE 9:

the probability of detection for all cases of diseases and conditions combined at ante mortem (am), post mortem (pm) (three proposed scenarios) inspection scenarios with the most likely (ml), 5th and 95th percentiles. .................................... 29

TABLE 10: the detection fractions for clinical surveillance and combined abattoir and clinical surveillance for endemic diseases: liver fluke and lower respiratory tract infection and welfare conditions: leg and foot disorders and sheep scab. .................................. 30 TABLE 11: the abattoir and clinical surveillance sensitivities for fmd. ......................................... 30


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LIST OF FIGURES FIGURE 1. Different case types defined for description and analyses of the sensitivity of meat inspection in small ruminants (for further explanation see text) with: non-detectable cases represented by the white area; detectable cases consist of mild cases (pale blue area) and typical cases (dark blue area). .............................................................. 15 FIGURE 2. A flow diagram of the scenario tree model for stage 2, with the arrows indicating the order that each stage of the model occurs i.e. the node of the tree is calculated. With compartment ‘final result 1’ for detectable cases being the results located in table 8 and the probability of detection for all cases being found in table 9 (‘final results 2’). .................................................................................................................... 19 FIGURE 3. Representation of the overlap in surveillance activities across different population strata, for two surveillance system components (ssc) in an animal population divided into four separate strata by two different animal- and herd level risk factors (red and green). ............................................................................................................ 23


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BACKGROUND AS PROVIDED BY EFSA The inspection of animals for slaughter constitutes a potentially important sentinel function for animal diseases. The European Commission has mandated the European Food Safety Authority (EFSA) to prepare scientific opinions related to meat inspection in different species (M-2010-0232). It specifically requires EFSA to evaluate meat inspection (as defined by Regulation (EC) No 854/2004) in order to assess the fitness of the meat for human consumption and to monitor food-borne zoonotic infections (public health) without jeopardizing either the detection of certain animal diseases or the verification of compliance with rules on animal welfare at slaughter. If the current methodology for monitoring major hazards to public health is found to be unsatisfactory, additional methods should be recommended. Implications of these changes on animal health and welfare should be assessed. In order to ensure a risk-based approach, EFSA has been requested to provide scientific opinions on meat inspection in slaughterhouses and, if considered appropriate, at any other stages of the production chain. Several species are to be considered including sheep and goats, which for the purposes of this report will be collectively known as small ruminants.

TERMS OF REFERENCE AS PROVIDED BY EFSA This contract was awarded by EFSA to the COMISURV Consortium, consisting of the National Veterinary Institute (SVA) Sweden, Safe Food Solutions inc. (SAFOSO) Switzerland, French Agency for Food, Environmental and Occupational Health & Safety (ANSES) France, Federal Institute of Risk Assessment (BfR) Germany and the Royal Veterinary College (RVC) United Kingdom. Consortium including the Contract title: ‘Contribution of meat inspection to animal health surveillance’ Contract number: CT/EFSA/AHAW/2010/05

ACKNOWLEDGEMENTS COMISURV would like to thank experts Dr A. Pointon, Dr A. Ridler and Dr W. Steele for their invaluable assistance in the elicitation exercise, thereby contributing with their broad knowledge on meat inspection, welfare and infectious disease of small ruminants.


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INTRODUCTION AND OBJECTIVES Meat inspection was originally introduced to improve public health by removing potentially hazardous carcasses from the food chain. In Europe, meat inspection protocols have evolved from Ostertag’s 1892 handbook to the current Regulation (EC) No 854/2004 (Ostertag, 1892 and Anonymous, 2004). However, changes in animal husbandry and disease in European countries have led to using hazard analysis and critical control points (HACCP) to assess and reduce health hazards at each step of the meat production chain, resulting in a farm to fork approach and to questions being asked about the effectiveness of the current meat inspection process (Berends et al. 1993 and FAO, 1999). During the meat inspection process welfare conditions and diseases that are of concern to public health and both animal health and welfare are recorded. Over several decades there have been many studies which have observed the effectiveness of meat inspection protocols in discovering diseases in slaughter animal populations. These studies have shown that the sensitivity (the ability to detect true positive cases) of the inspection process to detect diseases and welfare conditions increases when their prevalence increases (Mousing et al. 1997 and Abbott and Whittingdon, 2003). The sensitivity of meat inspection procedures is highly variable depending upon both disease and abattoir factors. For example Bond et al. (2010) found that the sensitivity of inspection for parasitic disorders was low at 0.16 (0.12-0.19) but much higher for respiratory diseases 0.92 (0.84-0.99) and Schemann et al. (2010) demonstrated the variability of inspection processes. There have been several studies including those by Moo et al. 1980; Hathaway et al. 1988 and Hathaway et al. 1989, which have observed the effect of changing the inspection protocol upon the detection of different diseases. These studies have used the probability of detection and the detection fraction (the proportion of infected animals in the population that are successfully detected) as a measure of the effectiveness of the inspection protocols in finding diseases and welfare conditions and have calculated the sensitivity of the inspection protocols to determine the proportion of truly infected animals that are detected in animals that are sent to the abattoir (Enoe et al. 2003). This is going to be estimated in stage 3 of the report in relation to endemic diseases and welfare conditions. To increase the accuracy of calculating the detection fraction in studies, it has been recommended that the prevalence of the disease or welfare condition and factors affecting the prevalence, for example season and age, are taken into account (Hathaway et al. 1993 and Berends et al. 1996). Risk factors and prevalence are going to be taken into consideration during the final stage of this report. This study is part of a process to assess whether a change to current methods would alter the effectiveness of the abattoir surveillance system to detect communicable and non-communicable diseases and welfare conditions, with and without additional information concerning disease or welfare condition risk factors. This study uses scenario tree models to assess the sensitivity of different post mortem protocols, to calculate the probability of detection for diseases and welfare conditions selected by the AHAW WG and evaluate the effectiveness of surveillance using observations from abattoirs (abattoir surveillance) compared with surveillance using clinical observations from the field (clinical surveillance).

1. Overall objectives The overall objectives of this work were to assist the AHAW panel and its WG in responding to the Commission’s request to critically assess implications of any changes to the current meat inspection methods, (suggested in the light of public health risks) on animal health and welfare regarding exotic and endemic diseases and animal welfare conditions. This involved the estimation of the effectiveness, with respect to animal health and welfare, of both meat inspection and the overall surveillance system, both prior to and following suggested surveillance system changes.


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2.

Specific objectives

The specific objectives of this work were to assist in the development of a generic stochastic model of the meat inspection system for small ruminants, as well as of other relevant surveillance components, for specific diseases and welfare conditions (as determined by the AHAW WG) that affect small ruminants which for the purpose of this study are sheep (Ovis aries) and goats (Capra aegagrus). This involved the identification and collection of data needed for the model, the identification of data gaps and the implementation of the model to quantify the effectiveness of three different meat inspection scenarios in detecting the diseases in question. Note that the word surveillance as used in this report does not imply that any action is taken to capture, or act upon, the information. It merely points to the potential of these systems to be used for such purposes.


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MATERIALS AND METHODS 3. Meat Inspection Scenarios The scenarios with respect to changes in meat inspection were developed in agreement with the AHAW WG, taking into account changes already proposed by EFSA’s BIOHAZ panel for swine and for poultry. The scenarios involve retaining the ante mortem processes but changing post mortem processes involved at abattoir inspection. Three scenarios were used in the model. The first scenario involved retaining the current post mortem inspection protocol which is outlined in Table 1. The second scenario involved using a post mortem protocol where lymph nodes are systematically incised and a visual inspection is undertaken with no palpation being carried out apart from the sort of palpation necessary to incise lymph nodes. The third scenario was a visual only inspection where no incision or palpation tasks occur.

Table 1: Inspection requirements for small ruminants according to Regulation (EC) No 853/2004 (v: visual inspection, p: palpation and i: incision). Inspected region Heada Tongue Mouth Fauces Throat Lungs Trachea Oesophagus Pericardium Heart Diaphragm Liver GITa and Mesentery Spleen Kidneys Pleura and Peritoneum Genital organs Udder Umbilical region Joints (young) Lymph Retropharyngeal and parotid nodes Bronchial and mediastinal Hepatic and pancreatic GIT and mesenteric Renal Supramammary

Current v vb vb v vb v, p,i b v,i b v,i b v v,i b v v,p,i v v v,i b v vb v v,p,i b v,p,i b v b,p b,i b v,p, i b v,p v ib v

Mode of inspection Intermediate v vb vb v vb v, i b v,i b v,i b v v,i b v v,i v v v,i b v vb v v,i b v,i b v b,i b v, i b v v ib v

Visual only v vb vb v vb v, v v v v v v v v v v vb v v v vb v v v v

(a): inspection excluded if not going for human consumption (b): inspection only in the event of doubt


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4.

Stage 1: Diseases and welfare conditions

4.1 Identifying diseases and welfare conditions to be used in the study Stage 1 involved reaching a consensus on the diseases and welfare conditions to be studied in the report. Twenty diseases and welfare conditions were selected by the AHAW WG as shown in Table 2. All diseases and welfare conditions listed by the AHAW WG were to be evaluated with regards to their probability of being detected at meat inspection (stage 2). In addition, for five diseases and welfare conditions, surveillance by meat inspection was to be compared with clinical surveillance (stage 3), taking into consideration prevalence risk factors of diseases and welfare conditions. Due to limited data availability in scientific literature and lack of delineation by the experts for goats, the input data and results are predominantly applicable to sheep, with the exception of bTB in goats.

Table 2: List of diseases and welfare conditions in small ruminants identified by the AHAW WG for consideration in the assessment conducted by COMISURV. Disease or welfare condition Bluetongue (BT) Exotic Foot and Mouth disease (FMD) Rift valley fever (RVF) Bovine tuberculosis (bTB) in goats Endemic Caseous lymphadenitis Echinococcosis/hydatidosis Liver fluke Lower respiratory tract infection Lungworm Orf disease Pulmonary adenomatosis / Maedi-Visna Diarrhoea/Soiling Welfare Partial vaginal prolapse/hernia Arthritis Bruising Broken bones Leg and foot disorders including. footrot Poor body condition Sheep scab Mastitis

Stage 2 Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

Stage 3 No Yes No No No No Yes Yes No No No No No No No No Yes No Yes No

4.2 Case definition development Following the list of diseases and welfare conditions provided by the AHAW WG, case definitions of ‘typical’ and ‘mild’ cases were developed and used as the basis for further evaluation. The symptoms for diseases and welfare conditions were obtained from the literature (Linklater, 1993; Gracey et al. 1999; Radostitis et al. 2000; Scott, 2007 and Merck, 2011). Typical cases were by definition detectable cases and express more developed clinical signs than mild cases. They fit the typical case definition provided from the literature and approved through elicitation with the experts. Typical cases were defined as the clinical signs and/or lesions that are expected to be observed in more than 60% of affected or infected small ruminants arriving at slaughter.


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The mild case of a disease or welfare condition is the form that could be seen at the early stages of the disease or at some point between the subclinical (and without pathological lesions that are observable through the meat inspection process) and the fully developed (i.e. ‘typical’ form of). A mild case is neither typical nor non-detectable. The animal will probably present more subtle signs than typical case. Mild cases fit the mild case definition validated by experts. The definitions were approved by experts and can be found in Table 3. Table 3: The presentation of mild and typical animal health diseases and welfare conditions at the ante mortem (AM) and post mortem (PM) inspection stages.

Exotic diseases

Disease or welfare condition Bluetongue (BT)

Foot and mouth disease (FMD)

Rift Valley fever (RVF)

Endemic diseases

Bovine tuberculosis (bTB) in goats

Caseous lymphadenitis

Echinococcosis

Liver fluke

Lower respiratory tract infection

Typical case AM inspection - watery nasal discharge, swollen face, swelling/oedema in the submandibular region, ulcers in mouth, lesions in the coronary band (including inflammation of coronary band), lameness and formation of crusts around the nose. PM inspection - haemorrhages at the base of the pulmonary artery, swelling/oedema in the head and neck areas and cyanotic tongue. AM inspection - lameness, stomatitis with vesicles, erosions and ulcers, vesicles and erosions in the interdigital space and vesicles and erosions in the coronary band. PM inspection - erosions and ulcers in the mouth. AM inspection - depression. PM inspection - necrotic foci in the liver and haemorrhages in the lungs. AM inspection - poor body condition and moist cough. PM inspection - abscesses or granulomas in the lymph nodes of the lungs (bronchial and mediastinal) and with abscesses in the lungs. AM inspection - enlarged superficial lymph nodes. PM inspection - laminated abscesses in the head lymph nodes, abscesses in the lung and with abscesses in the bronchial and mediastinal lymph nodes. AM inspection – no signs. PM inspection - hydatid cysts in the liver and in the lungs. AM inspection - poor body condition. PM inspection - cholangitis/thickened bile duct walls and with the presence of mature flukes in the bile ducts. AM inspection - mucopurulent nasal discharge. PM inspection - lesions of pneumonia (red consolidation, hepatisation etc.) in the apical, cardiac and cranial part of the diaphragmatic lobes and with chronic pleurisy.


Mild case AM inspection - mild swelling of the face, ears, lips and tongue and nasal discharge.

PM inspection - without any lesions.

AM inspection - mild lameness and lesions in the feet (interdigital dermatitis, vesicles etc). PM inspection - without any lesions. AM inspection - depression. PM inspection with haemorrhages in various organs. AM inspection - cough and poor body condition. PM inspection mild lung lesions (abscesses/granulomas) and a poor carcase. AM inspection – no signs. PM inspection - enlarged superficial lymph nodes and abscesses in the body (including the lymph nodes). AM inspection – no signs. PM inspection - a small number of small cysts in liver and lungs. AM inspection - no signs. PM inspection - adult flukes in liver ducts and mild liver lesions. AM inspection - respiratory signs (coughing, hyperpnoea etc.) and dullness. PM inspection - lesions consistent with pneumonia (consolidation etc).

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Contribution of meat inspection to animal health surveillance – Sheep and Goats Disease or welfare condition Lungworm

Mild case

AM inspection – cough. PM inspection - greenish exudate in bronchi, patches of consolidation in lungs, fibrous/calcified nodules in the subpleural lung parenchyma and with (lungworm) parasites in the airways.

AM inspection - mild cough. PM inspection - frothy airways with small numbers of worms and lesions of pneumonia in caudal lobes (vacuoles etc.).

AM inspection - granulomatous type lesions and scabs around the mouth. PM inspection - see AM. AM inspection - poor body condition and dyspnoea . PM inspection - grossly enlarged and heavy lungs, coalescing grey areas in the lungs, frothy fluid in the cut surface of the lung lesions and in the airways and with enlarged, oedematous bronchial and mediastinal lymph nodes.

AM inspection - crusts and ulcers in the lips and nostrils. PM inspection - see AM. AM inspection - slight respiratory distress, nasal discharge and lethargy. PM inspection - minor increase in lung size and grey areas (lesions) in the lungs.

AM inspection - lameness and swollen joints.

AM inspection - mild lameness.

PM inspection - turbid synovial fluid, erosions on the articular cartilage and enlarged local lymph nodes. AM inspection - fracture in one leg, severe lameness, abnormal movements of the damaged leg and with pain on the palpation and manipulation of the leg. PM inspection - a fracture surrounded by fresh haemorrhage.

PM inspection - swollen joint(s) with increased synovial fluid.

AM inspection - abnormal behaviour indicating pain.

AM inspection - without any signs.

PM inspection - recent/fresh bruises on the flanks and on the legs and broken ribs.

PM inspection - mild, localised bruises, especially on back and flanks.

Diarrhoea or Soiling

AM inspection - soiled hind parts. PM inspection - abnormal intestinal contents (watery, bloody etc.).

AM inspection - soiled perineum PM inspection - diarrhoeic contents in the intestines

Leg and feet disorders (inc. footrot)

AM inspection - slight lameness, disability in more than one leg, offensive smell and interdigital dermatitis.

AM inspection - mild lameness and mild interdigital dermatitis or necrosis with foul smell.

PM inspection - atrophy of the affected muscles. AM inspection - swollen udder, enlarged supramammary lymph nodes and with lumps in the mammary tissue. PM inspection - fibrosis in the udder and enlarged supramammary lymph nodes.

PM inspection without any lesions.

Orf disease

Pulmonary Adenomatosis / Maedi-Visna

Arthritis

Broken bones

Bruising

Welfare conditions

Typical case

Mastitis

N/A – there is no mild form of broken bones

AM inspection - without any signs.

PM inspection - enlarged udder.

Partial vaginal prolapsed

AM inspection - the detection of a prolapsed mass in the genital area.

AM inspection - straining and a slight protrusion and swelling of the vagina.

Poor body condition

PM inspection - a prolapsed vagina. AM inspection - the detection of prominent bones on the animal.

PM inspection - without any lesions. AM inspection - prominent bones.


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Contribution of meat inspection to animal health surveillance – Sheep and Goats Disease or welfare condition

Sheep scab (Psoroptes ovis)

Typical case PM inspection - the loss of the subcutaneous fat, the loss or the reduced amount of intracavities fat and with the oedematous and jelly-like appearance of the carcase fat. AM inspection - the loss of wool (including bare patches and alopecia), intense pruritus, the presence of papules, pustules etc. on the body (including the head) and with matted/ragged fleece/wool. PM inspection - pruritus, pustules on the skin and skin lesions.

Mild case PM inspection - little fat cover and prominent bones. AM inspection - pruritus, skin lesions (papules, crusts around mouth, ears, bruising etc.) and ragged/deranged fleece. PM inspection - pruritus and pustules on the skin.

The mild and typical cases were combined to form detectable cases whilst asymptomatic cases (undetectable during ante mortem) and cases with no pathological lesions (undetectable during post mortem) cases were classed as non-detectable cases (Figure 1). Detectable and non-detectable cases were combined to calculate the overall probability of detection for all cases which are presented at the abattoir. An analysis based on the detectable cases provides the effectiveness of abattoir inspection in detecting cases due to the theory that these are 100% detectable; however in practise there are limitations of time, experience, lighting or other conditions. Similarly, an analysis based on all cases provide an approximation of the detection fraction, the proportion of infected animals within the population that are successfully detected.

Figure 1. Graphical representation of the three types of cases which may be present at the abattoir and their different likelihood of detection based on meat inspection tasks. The arrow indicates both the possible progression of the disease and that detection will increase from a non-detectable stage to a typical stage. However, not all exposed animals will become diseased, not all non-detectable cases develop into mild and/or typical cases and not all mild cases progress through typical cases. For the purposes of this report, mild and typical cases have been combined into a ‘detectable case’ category. The proportion of cases in the different case categories will depend on multiple factors including disease biology and environmental factors.


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Mild and typical cases were subsequently taken forward for elicitation of the percentage of infected or affected animals in the population expressing typical, mild or no clinical signs/lesions. During the subsequent elicitation, there was no pre-set assumption regarding the percentage of cases belonging to either category. In other words, the case definitions provided below are merely expressing two levels of severity, and their relative proportions as used in the subsequent analyses were elicited in a separate step as described under section 4. Consequently, for the purpose of this analysis, what is defined below as typical is simply a more severe form of the condition, which does not necessarily correspond to the more common form. Risk factors for diseases and welfare conditions were taken into consideration with regards to the comparison of different methods of surveillance in stage 3 of the model. The risk factors were partly elicited from the literature and from the experts (Table 4). Input values for the models can be found in Appendix B (Tables B1 and B2). With the herd level risk factors, ‘open farm system’ refers to a farming practice where new stock is purchased and introduced into the herd in contrast to closed farm systems, where breeding and production is predominantly based on own stock, i.e. they can purchase rams but not ewes. The term ‘housed flock’ indicates that animals are kept indoors, in pens or yards and require feed. Lambing tends to occur indoors in this system.

Table 4:

The risk factors selected for stage 3 of the model.

Disease or welfare condition

Animal level Age less than one year old

Risk factors References Herd level Experts Open farm system

References Barnett and Cox,1999 Experts

Exotic disease

Foot and mouth disease (FMD)

Endemic diseases

Liver fluke (Fasciola hepatica) Lower respiratory tract infection (inc. pneumonia) Leg and feet disorders inc. footrot

Age more than one year old Age less than six months old

Experts

Breed e.g. Merino

Sheep scab (Ps. ovis)

Poor body condition

Bishop and Morris, 2007 Experts

Welfare conditions

Scott,2011

Open farm system Housed flock

Open farm system

Jones et al, 1979; Sargisson and Scott,2011 Abbott and Lewis, 2005

Open farm system

Rose and Wall, 2011

4.3 Data collection Three values: the most likely, minimum and maximum, were obtained to define the distributions of each input value of the model. Data for the parameters needed for stage 2 were obtained primarily through elicitation of expert opinion via questionnaires (for details, see Appendix A’s attached documents). Data for stage 3 parameters of the model were obtained from both literature and the experts (Appendix B). The elicitation of data from experts was completed by developing and using a protocol based on a modified Delphi technique (Hecht et al. 1977; Hsu et al. 2007 and Knol et al. 2010). This protocol consisted of five steps: (i) questionnaire development; (ii) first elicitation round; (iii) data collation; (iv) second elicitation round and (v) final estimates. 4.4 Elicitation of expert opinion Experts were recruited to provide parameter values that were unobtainable from the literature and appraised the disease definitions and risk factors which were used in stages 2 and 3 of the model. Experts were selected on the basis of their professional expertise in meat inspection or in small ruminant pathology in relation to the small ruminant production chain in Europe. Three experts from Supporting Publications 2012:EN-320

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Australia, New Zealand and Scotland, with extensive knowledge and numerous peer reviewed publications on meat inspection, infectious diseases and/or welfare conditions of small ruminants, were identified and invited to participate in the study. The experts were contacted in writing and briefed on the project aims and objectives and were given clear instructions on the elicitation process. Their agreement to participate in the expert elicitation was obtained.

4.4.1.

Questionnaire development

Two questionnaires were developed with the aim to support the data collection, particularly where data were missing from the literature. The purpose of the first questionnaire was to obtain information on and clarify our own definitions of mild and typical cases (Appendix A1), and the second to provide data for the parameters related to detection probabilities at meat and clinical inspection on the basis of the case definitions provided by the experts and animal- and herd-level risk factors (Appendix A2). 4.4.2.

First elicitation round

Questionnaires were submitted to the selected experts electronically. Instructions for filling in the questionnaire along with a deadline (approximately two weeks from receiving the questionnaire) for submission of responses were clearly stated. 4.4.3.

Data collation

The estimates provided by each expert were collated in one document. An overall estimate for each of the requested parameters was derived by combining the single expert estimates using means of their values. However, if the experts’ answers were too divergent (with values that differ by more than 0.2), they were taken forward to a second elicitation round.

4.4.4.

Second elicitation round

The combined estimates were circulated anonymously among the experts who were given the opportunity to reconsider their inputs in the light of other experts’ estimates, and/or give comments on the reliability of the provided estimates or the overall estimate. An additional communication with experts was organised to obtain feedback on the results.

4.4.5.

Final estimates

A consensus response was finally obtained from the experts. The most likely value and the variability (minimum and maximum) values of the experts’ responses were used as inputs for the stage 2 (case specific probability of detection) and stage 3 decision tree models (component sensitivity models and detection fraction models) at the relevant decision nodes (Tables 4 and 5).


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5. Stage 2: The probability of detection at meat inspection The objective of stage 2 modelling was to estimate case type-specific probabilities of detection at meat inspection, as well as to provide an estimate of an overall measure of surveillance efficiency for both detectable cases (typical and mild cases) and for all cases (detectable and non-detectable cases). Detectable case results will provide the detection effectiveness of the process where in theory all cases in the category should be detected but may not be detected, for example due to time constraints, experience, sub-optimal inspection conditions at the abattoir etc. All cases indicate the value of the abattoir inspection for detecting the proportion of infected/affected animals, with all infected/affected animals as denominator population (i.e. the prevalence was not taken in account at stage 2). All scenarios described in section 3 were evaluated, i.e. the current system, an intermediate system where lymph nodes are systematically incised and a visual inspection is undertaken, and a system where meat inspection is by a visual inspection procedure only.

5.1 Model implementation Consolidated estimates collected during expert elicitation (i.e. ‘most likely’, ‘minimum’ and ‘maximum’ values) for the ante mortem and post mortem inspection steps, were used as input for stage 2 models (Appendix A). Two types of decision nodes were considered for this stage of the model: detection category nodes and detection nodes. Detection category nodes are included to account for the case type (typical, mild or non-detectable case), a factor influencing the probability of detection. Detection nodes refer to events, procedures and choices that lead to the detection of the welfare condition or the disease with the surveillance system considered (i.e. the inspection tasks performed: ante mortem and post mortem) (Cameron et al. 2003). This report focuses on the results for detectable and all cases; intermediate results for mild and typical cases can be found in Appendices C1 and C2. The probability of detection (probability of detecting an infected individual at the abattoir) at each inspection step was estimated by translation of the consolidated estimates into BetaPert distributions, using Monte-Carlo simulations (10,000 iterations) as applied in @Risk 5.7 Professional (Palisade Europe UK Ltd). Each step of the model represents a node of a tree, and is run in the sequence shown in Figure 2. The most likely, as well as 5th and 95th percentiles (the credibility intervals) of the output distributions of ante mortem, post mortem and combined (ante mortem and post mortem inspection) detection probabilities were derived for each of the diseases and welfare conditions in Table 1. The overlap of the credibility intervals was used to assess whether scenarios differed significantly from each other.


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Distribution of clinical signs/lesions

Typical cases

Mild cases

Non‐detectable cases

Step 1‐ Ante‐Mortem inspection



The proportion of cases detected at this step


The proportion of cases not detected at this step

Step 2‐ Post‐Mortem (PM) inspection

Step 2‐ Post‐Mortem (PM) inspection



(Note: PM is referred to as a single inspection step)

(Note: PM is referred to as a single inspection step)

Intermediate result

Intermediate result

Total proportion of typical cases detected by AM & PM inspection steps

Total proportion of early and mild cases detected by AM & PM inspection steps

Step 2‐ Post‐Mortem inspection The proportion of cases not detected at this step

Intermediate result Total proportion of non‐detectable cases that have gone through AM & PM inspection steps and not detected

Final result 1 Total proportion of detectable (typical and mild) cases detected by AM and PM inspection steps

Final result 2 Total proportion of cases detected by AM and PM inspection steps

Figure 2. A flow diagram of the scenario tree model for stage 2, with the arrows indicating the order that each stage of the model occurs i.e. node of the tree is calculated. With compartment ‘Final result 1’ for detectable cases being the results located in Table 8 and the probability of detection for all cases being found in Table 9 (‘Final results 2’).


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5.2 Calculation of probability of detection The probability of detection during the whole meat inspection procedure (ante mortem and post mortem inspection) was calculated, by case type, as described in equation (Eq.) 1. 1

(1)

where SeMI is the overall probability of detection at ante mortem and post mortem inspection for case type i (parameter values were provided by experts through elicitation), SeAM is the probability of detection at ante mortem inspection for case type i and SePM is the probability of detection at post mortem inspection for case type i. This formula takes account of the dependency of post mortem inspection from ante mortem inspection. Only those cases that have not already been detected by the preceding ante-mortem inspection step will be subject to post mortem inspection. Thus, a high sensitivity of post mortem can nevertheless lead to a low probability of detection if ante-mortem also has a high sensitivity. For the twenty selected diseases and welfare conditions the overall probabilities of detection during meat inspection (at ante mortem inspection, at post mortem conditional on the condition not being detected at ante mortem inspection, and at ante mortem and post mortem inspection combined) were calculated considering detectable and all cases, respectively. For detectable cases, case type categories were restricted to typical and mild. For all cases (detectable and non-detectable), all case type categories were considered (typical, mild and non-detectable), see flow diagram, Figure 2. Overall probabilities were calculated as 1

(2) where SeMI is the probability of detection at meat inspection, x is the proportion of the population with case type i and Sei is the probability of detection at the meat inspection step in question (at ante mortem inspection, at post mortem conditional on the condition not being detected at ante mortem inspection, and at ante mortem and post mortem inspection combined) for case type i, respectively. Note that the specificity of the meat inspection procedure, i.e. the parameter influencing the proportion of animals falsely detected as positive, was not considered in this assessment.


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6. Stage 3: Modelling the overall surveillance system The objective of stage 3 modelling was to estimate two different effectiveness outcomes, depending on whether the disease or welfare condition was to be considered endemic (present) or exotic (not present). Five diseases and welfare conditions in small ruminants were selected by the AHAW WG for inclusion in stage 3 models. The objective for exotic diseases (i.e. FMD), was to evaluate the probability of detecting at least one infected case of infected small ruminants by abattoir inspection relative to other surveillance system components (SSC) (component sensitivity), which for the purposes of this report is clinical surveillance. For endemic diseases (liver fluke, lower respiratory tract infection) and welfare conditions (leg and feet disorders inc. footrot, sheep scab) the objective was to calculate the case-finding capacity i.e. the proportion of infected or affected animals detected by the surveillance components (detection fraction): abattoir and clinical surveillance.

6.1 Model structure Two SSCs, abattoir and clinical surveillance, were considered for the purpose of analysis of the overall small ruminant surveillance system. Four types of nodes were considered for this model: risk category nodes, infection nodes, detection category nodes and detection nodes. The category nodes (risk- and detection-) aim to split the population into different strata with an equal probability of having the disease or welfare condition or being detected with the disease or welfare condition. The model allowed us to account for one risk factor at the animal level, and one at the herd level (Table 4). Infection nodes refer to the infection status of the individual (animal) level and farm (herd) level. Finally, detection nodes refer to the inspection tasks performed for the abattoir surveillance, and to the event chain ‘veterinarian is called’ – ‘veterinarian takes samples’ – ‘test outcome is positive’ for clinical surveillance. Nodes relevant to each of the SSCs were identified and included as steps in the scenario tree for each SSC (Table 4 and Table 5 for abattoir and clinical surveillance respectively). The nodes were placed according to their chronological order and by decreasing size of groups of units. Risk category nodes were placed before infection nodes, with infection nodes preceding detection category and detection nodes as defined by Martin et al. (2007).

6.2 Model inputs and implementation The scenario tree model for stage 3 consisted of seven or eight nodes concerned with disease prevalence, risk factor prevalence, detection probabilities and diagnostic test sensitivities. The details of the nodes and the data sources can be found in Tables 5 and 6, which are for abattoir and clinical surveillance respectively, Appendix B lists the input values. Each SSC was outlined in separate Excel spreadsheets (Microsoft Office 2007, Microsoft Corporation), allowing for stochastic modelling using @Risk 5.7 Professional (Palisade Europe UK Ltd) software. The probability of detection during the whole meat inspection procedure (ante mortem and post mortem inspection) was calculated, by stratum, as described in Eq. 1 for stage 2. Note that the specificity of the meat inspection procedure, i.e. the parameter influencing the proportion of animals falsely detected as positive, was not considered in this assessment.


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Table 5: Nodes considered for inclusion in the stage 3 model for the abattoir surveillance system component. Node

Name

Type

Outcome

1

Herd level risk factor (e.g. farm type)

Risk category

2

Herd prevalence

Infection

3

Animal level risk factor (e.g. age group)

Risk category

4

Animal prevalence

Infection

5

Presence of clinical signs (within herd-level and animal-level risk factor categories)

Detection category

6

Detected at ante mortem inspection

Detection

7

Detected at post mortem inspection

Detection

Risk category 0 Risk category 1 Yes No Risk category 0 Risk category 1 Yes No Typical cases Mild cases Non-detectable cases Yes No Yes No

Next node 2 2 3 End 4 4 5 End 6 6 6 7 End End End

Source of data Literature Literature Literature Literature Expert elicitation Expert elicitation Expert elicitation

Table 6: Nodes considered for inclusion in the stage 3 model for the clinical surveillance system component. Node

Name

Type

1

Herd level risk factor (e.g. Farm type)

Risk category

2

Farm infected

Infection

3

Animal level risk factor (e.g. Age group)

Risk category

4

Infected animals

Infection

5

Presence of clinical signs (within herd-level and animallevel risk factor categories)

Detection category

6

Veterinarian contacted

Detection

7

Veterinarian sampled

Detection

8

Test outcome

Detection


Outcome Risk category 0 Risk category 1 Yes No Risk category 0 Risk category 1 Yes No Typical cases Mild cases Subclinical cases Yes No Yes No Yes No

Next node 2 2 3 End 4 4 5 End 6 6 6 7 End 8 End End End

Source of data Literature Literature Literature Literature Expert elicitation Expert elicitation Expert elicitation Expert elicitation / literature

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6.3 Detection fraction models In assessing the case-finding capacity of the overall surveillance system (measured as detection fraction), the overlap in coverage between surveillance components had to be taken into account (Figure 3). This included specifying the coverage by the surveillance component. By definition, all animals are covered under clinical surveillance, i.e. every animal has a chance (although very small for some) to become subject to a veterinary visit. Thus, there are two sections to the two-component surveillance system: 1: the proportion of animals covered only by the clinical surveillance component, 2: the proportion of animals covered by both abattoir and clinical surveillance (the overlap).

High Risk

High Risk

SSC 1

SSC 2

Low Risk

Low Risk

Figure 3. Representation of the overlap in surveillance activities across different population strata, for two surveillance system components (SSC) in an animal population divided into four separate strata by two different animal- and herd level risk factors (red and green). The proportion of infected animals successfully detected by the abattoir inspection surveillance component (the detection fraction) was calculated as

∑

(3)

where x is the proportion of the population in stratum i, p is the animal-level prevalence of the disease/welfare condition in stratum i, SeMI is the overall probability of detection at meat inspection in stratum i, c is the coverage of the surveillance activity for stratum i and P is the global prevalence at animal-level. The global prevalence P was derived as a weighted average of the stratum-specific prevalences, which was calculated as: ∑


(4)

23



where x is the proportion of the population in stratum i, pHL is the herd-level prevalence of the disease or welfare condition in stratum i and pAL is the animal-level prevalence of the disease or welfare condition in stratum i. The proportion of the whole population being detected as a true positive (TP) within each surveillance segment k, was calculated by: ∑

(5)

where x is the proportion of the population in stratum i, p is the animal-level prevalence of the disease/welfare condition in stratum i, Se is the probability of detection by the test system used defined by surveillance segment k in stratum i and c is the coverage of the surveillance segment k for stratum i. For the population covered by the overlap (both systems), the probability of being detected as a TP by system 1 or 2 or both was calculated as:

(6)

The overall detection fraction is then calculated, similar to in Eq. 3:

∑

(7)

The surveillance component-specific detection fraction was estimated by summarising the proportion of animals detected as TPs in all segments covered by the surveillance component.

6.4 Component sensitivity models For the models aimed at estimating and comparing component sensitivity, stratum-specific sensitivities (Se) were calculated as the sum of all probabilities in the scenario tree that were associated with a positive outcome (i.e. detection). Estimates were derived separately for clinical surveillance and for the three abattoir surveillance scenarios: (i) meat inspection by the current system, (ii) for an intermediate meat inspection scenario where lymph nodes are systematically incised and a visual inspection is undertaken, and (iii) for a system based on visual inspection only. The component sensitivity for each surveillance component reflects the probability that at least one animal is detected as positive with the respective surveillance component, i.e. 1 – p (all negative). Component sensitivity was then estimated as: 1


1

(8)

24



where Se is the probability of an animal testing positive in stratum i, and n is the number of animals in stratum i that are processed by the surveillance component (in this case, the number of animals slaughtered during a one month period (for abattoir surveillance), and population size (for clinical surveillance, with the assumption of 100 % coverage).


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RESULTS 7. Stage 1: expert elicitation of case types The proportion of non-detectable, mild and typical cases by disease and welfare condition, as elicited by experts, is provided in Table 7.

Table 7: Proportion of detectable (typical or mild) and non-detectable cases by diseases as elicited from the experts. Estimates were provided as ‘minimum’ (Min), ‘most likely’ (ML) and ‘maximum’ (Max) values.

Welfare conditions

Endemic

Exotic

Disease or welfare condition BT FMD RVF bTB in goats Caseous lymphadenitis Echinococcosis Liver fluke Lower respiratory tract infections Lungworm Orf disease Pulmonary Adenomatosis / MaediVisna Arthritis Broken bonesa Bruising Diarrhoeab Leg and foot disorders inc. footrot Mastitis Partial vaginal prolapse or hernia Poor body condition Sheep scab (Ps. ovis)

Proportion of case types within an infected or affected batch Typical cases Mild cases Non-detectable cases Min Max Min Max Min Max ML ML ML 0.001 0.050 0.480 0.005 0.250 0.625 0.830 0.990 0.120 0.001 0.015 0.060 0.005 0.100 0.800 0.920 0.990 0.065 0.200 0.450 0.800 0.150 0.750 0.025 0.150 0.300 0.400 0.100 0.200 0.400 0.200 0.650 0.200 0.350 0.550 0.450 0.000 0.050 0.200 0.003 0.400 0.433 0.817 1.000 0.133 0.034 0.103 0.240 0.070 0.333 0.677 0.713 0.766 0.183 0.037 0.140 0.267 0.140 0.533 0.300 0.493 0.717 0.367 0.050 0.200 0.400 0.100 0.700 0.300 0.500 0.850 0.300 0.034 0.100 0.050

0.100 0.137 0.225

0.233 0.307 0.400

0.157 0.170 0.050

0.267 0.250 0.200

0.533 0.433 0.400

0.500 0.373 0.350

0.633 0.613 0.575

0.800 0.830 0.850

0.075 1.000 0.000 0.203 0.033

0.250 1.000 0.067 0.450 0.100

0.500 1.000 0.303 0.617 0.202

0.250 0.167 0.300 0.167

0.600 0.270 0.550 0.270

0.900 0.407 0.733 0.373

0.050 0.360 0.393

0.150 0.663 0.630

0.400 0.766 0.800

0.033 0.033

0.134 0.133

0.270 0.333

0.100 0.267

0.203 0.500

0.407 0.600

0.500 0.000

0.663 0.367

0.765 0.433

0.050 0.070

0.200 0.217

0.450 0.600

0.550 0.150

0.800 0.367

1.000 0.767

0.000 0.333

0.000 0.417

0.100 0.700

(a): not elicited as all cases are typical. (b): all cases considered to be detectable per definition.

8. Stage 2 The values for the probability of detection at ante mortem and for the three proposed post mortem inspection scenarios for detectable and all cases (detectable and non-detectable cases combined) can be found in Tables 8 and 9 respectively. The probabilities of detection for mild and typical cases can be found in the Appendix C (Tables C1 and C2) but are not being discussed in this report. The results refer to the probability of detection at the individual animal level and the most likely (ML) value. Ante mortem inspection had higher probabilities of detection for detectable welfare conditions with 44% having a detection probability above 50% compared with 0% of detectable exotic diseases and


26



25% of detectable endemic diseases (Table 8). Twenty-five percent of detectable welfare conditions, 50% of detectable endemic diseases and 33% of exotic diseases were detected with detection probabilities of ≤25%. When all cases were considered (Table 9) the probability of detection decreased significantly (comparing the overlap of credibility intervals) for 66% of exotic diseases, 50 % of endemic diseases and 11% of welfare conditions. The probability of detection was significantly higher for ante mortem than post-mortem inspection for broken bones, diarrhoea, leg and foot disorders, partial prolapses/hernias, sheep scab, Orf disease and FMD for both detectable and all cases; BT and pulmonary adenomatosis when only considering detectable cases. Post mortem probability of detection levels can be lower because they are conditional on the cases being removed at the antemortem stage of the inspection process. Current post mortem inspection could detect 75% of detectable endemic disease cases, zero detectable exotic disease cases and 33% of detectable welfare condition cases with detection probabilities of ≤50% (Table 7). With a change of post mortem disease protocol to a visual only inspection, 63% and 25% of detectable endemic diseases and welfare conditions could be detected with a ≥50% probability. For three diseases Orf disease, liver fluke and bTB in goats, the reduction of the probability of detection was significant (i.e. non-overlapping credibility intervals) (Table 8), this occurred when the post mortem inspection was reduced to an intermediate inspection, for Orf disease and a visual only inspection, for liver fluke and bTB. When all cases were taken into account (Table 9) only broken bones had a probability of detection > 50%. Fifty percent, 56% and 66% of endemic, welfare and exotic diseases and welfare conditions respectively, had probabilities of detection of ≤20% with the current post-mortem scenario. A change in post mortem protocol did not significantly reduce the detection of any diseases or welfare conditions. Post mortem inspection had significantly higher probabilities of detection than ante-mortem inspection for bTB in goats, echinococcosis, liver fluke, bruising and mastitis for detectable and all cases; and caseous lymph adenitis and lungworm when taking into account detectable cases. Combined abattoir probabilities of detection were higher at detecting cases for many diseases and welfare conditions than when the abattoir inspection components were considered separately. Where this was not the case, i.e the detection probability of the combined meat inspection process yielded equal values as ante mortem or post mortem on their own. This was due to the fact that our experts had agreed that the respective disease/ welfare condition could not be detected at all with the one of the two meat inspection steps. Therefore the results of the combined meat inspection are solely based on the results of either ante mortem or post mortem inspection. For detectable cases only one disease (FMD) had a probability of detection that was lower than 50%, even when the post mortem protocol had been reduced to a visual only inspection. However, the combined inspection with a visual only post mortem protocol significantly reduced the detection of liver fluke and bTB in goats compared to combined current and intermediate scenarios. For the majority of exotic and endemic diseases and for three welfare conditions (arthritis, broken bones and poor body condition), the combined inspection of detectable cases with the intermediate or visual-only post mortem inspection protocol also reduced the detection probability, although this was not significant (Table 8). When considering all cases (Table 9), the probability of detection for the combined inspection was lower than for detectable cases with only 35% of diseases and welfare conditions being detected with a probability of ≥50%., with 15% of diseases and welfare conditions having a probability of detection of ≤20% The change in post mortem protocols lead for four diseases (bTB in goats, liver fluke, Orf disease and pulmonary adenomatosis/Maedi-Visna) and two welfare conditions (arthritis and poor body condition) to a clear reduction in the detection probability, yet none of these reductions were significant when the overlap of credibility intervals was considered.


27



Table 8: The probability of detection for all detectable cases of diseases and welfare conditions at ante mortem (AM), post mortem (PM) (three proposed scenarios) inspection scenarios with the most likely (ML), 5th and 95th percentiles. The AM inspection detection probability is shaded in blue, the PM inspection scenarios are in yellow and combined AM and PM inspection scenarios are in grey, with the darkest shades being the visual only scenarios and the medium shades being the intermediate scenarios and the pale shades being the current inspection scenario.

Welfare conditions

Endemic

Exotic

Disease or welfare condition BT FMD RVF bTB in goats Caseous lymphadenitis Echinococcosis Liver fluke Lower respiratory tract infection Lungworm Orf disease Pulmonary adenomatosis / Maedi-Visna Arthritis Broken bones Bruising Diarrhoea or Soiling Leg and foot disorders Mastitis Partial vaginal prolapse/Hernia Poor body condition Sheep scab

AM inspection

PM inspection Intermediate 0.05 ML 0.95

Visual 0.05 ML 0.95

Combined AM and PM inspection Current Intermediate Visual 0.05 ML 0.95 0.05 ML 0.95 0.05 ML 0.95

0.05

ML

0.95

Current 0.05 ML 0.95

0.27 0.09 0.36 0.16

0.42 0.15 0.48 0.22

0.63 0.31 0.59 0.31

0.11 0.00 0.23 0.50

0.16 0.02 0.32 0.59

0.25 0.05 0.42 0.69

0.09 0.00 0.23 0.50

0.14 0.02 0.32 0.59

0.22 0.05 0.42 0.69

0.07 0.00 0.23 0.33

0.11 0.00 0.32 0.40

0.16 0.00 0.42 0.50

0.46 0.10 0.71 0.74

0.64 0.19 0.82 0.84

0.77 0.34 0.86 0.90

0.41 0.10 0.71 0.74

0.63 0.19 0.82 0.84

0.76 0.34 0.86 0.90

0.39 0.09 0.71 0.55

0.57 0.15 0.82 0.64

0.72 0.31 0.86 0.72

0.07

0.14

0.23

0.56

0.63

0.77

0.56

0.63

0.77

0.49

0.59

0.68

0.69

0.83

0.89

0.69

0.83

0.89

0.62

0.76

0.81

0.00 0.02

0.00 0.03

0.00 0.07

0.82 0.89

0.89 0.92

0.93 0.95

0.82 0.89

0.89 0.92

0.93 0.95

0.71 0.63

0.79 0.66

0.86 0.69

0.82 0.94

0.89 0.96

0.93 0.98

0.82 0.94

0.89 0.96

0.93 0.98

0.71 0.67

0.79 0.69

0.86 0.74

0.33

0.46

0.55

0.41

0.50

0.61

0.41

0.50

0.61

0.41

0.50

0.61

0.91

0.95

0.98

0.91

0.95

0.98

0.91

0.95

0.98

0.19 0.51

0.25 0.59

0.30 0.72

0.44 0.09

0.50 0.13

0.56 0.17

0.44 0.00

0.51 0.00

0.56 0.00

0.44 0.00

0.51 0.00

0.56 0.00

0.69 0.67

0.75 0.76

0.80 0.82

0.69 0.51

0.73 0.59

0.80 0.72

0.69 0.51

0.73 0.59

0.80 0.72

0.42

0.56

0.67

0.21

0.32

0.39

0.18

0.24

0.35

0.18

0.24

0.35

0.76

0.86

0.92

0.72

0.81

0.87

0.72

0.81

0.87

0.32 0.76 0.04

0.43 0.95 0.09

0.52 0.98 0.16

0.19 0.49 0.80

0.26 0.65 0.87

0.36 0.65 0.92

0.19 0.27 0.80

0.26 0.50 0.87

0.36 0.49 0.92

0.14 0.27 0.80

0.20 0.50 0.87

0.26 0.49 0.92

0.59 0.90 0.92

0.71 0.98 0.96

0.78 0.99 0.99

0.59 0.86 0.92

0.71 0.97 0.96

0.78 0.99 0.99

0.53 0.86 0.92

0.65 0.97 0.96

0.70 0.99 0.99

0.58

0.66

0.72

0.07

0.10

0.14

0.06

0.09

0.13

0.06

0.09

0.13

0.70

0.77

0.81

0.69

0.77

0.80

0.69

0.77

0.80

0.34

0.45

0.54

0.11

0.14

0.17

0.11

0.14

0.17

0.11

0.14

0.17

0.49

0.59

0.66

0.49

0.59

0.66

0.49

0.59

0.66

0.09

0.15

0.25

0.42

0.53

0.63

0.42

0.53

0.63

0.42

0.53

0.63

0.56

0.69

0.79

0.56

0.69

0.79

0.56

0.69

0.79

0.43

0.51

0.62

0.01

0.02

0.06

0.01

0.02

0.06

0.01

0.02

0.06

0.45

0.56

0.65

0.45

0.56

0.65

0.45

0.56

0.65

0.39

0.49

0.57

0.30

0.35

0.42

0.29

0.34

0.40

0.29

0.34

0.40

0.81

0.84

0.87

0.79

0.82

0.85

0.79

0.82

0.85

0.49

0.62

0.71

0.00

0.01

0.01

0.00

0.00

0.01

0.00

0.00

0.01

0.50

0.63

0.71

0.50

0.63

0.71

0.50

0.63

0.71

Supporting Publications 2012:EN-320 The present document has been produced and adopted by the bodies identified above as authors. This task has been carried out exclusively by the authors in the context of a contract between the European Food Safety Authority and the authors, awarded following a tender procedure. The present document is published complying with the transparency principle to which the Authority is subject. It may not be considered as an output adopted by the Authority. The European food Safety Authority reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors

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Table 9: The probability of detection for all cases of diseases and welfare conditions combined at ante mortem (AM), post mortem (PM) (three proposed scenarios) inspection scenarios with the most likely (ML), 5th and 95th percentiles. The AM inspection detection probability is shaded in blue, the PM inspection scenarios are in yellow and combined AM and PM inspection scenarios are in grey, with the darkest shades being the visual only scenarios and the medium shades being the intermediate scenarios and the pale shades being the current inspection scenario.

Welfare conditions

Endemic

Exotic

Disease or welfare condition

AM inspection

PM inspection Intermediate 0.05 ML 0.95 0.01 0.02 0.07 0.00 0.00 0.00

Visual 0.05 ML 0.95 0.01 0.02 0.05 0.00 0.00 0.00

Combined AM and PM inspection Current Intermediate Visual 0.05 ML 0.95 0.05 ML 0.95 0.05 ML 0.06 0.11 0.28 0.05 0.09 0.27 0.05 0.11 0.01 0.02 0.03 0.01 0.02 0.03 0.01 0.01

0.95 0.25 0.03

0.05 0.04 0.01

ML 0.10 0.01

0.95 0.21 0.03

Current 0.05 ML 0.95 0.02 0.03 0.08 0.00 0.00 0.00

RVF bTB in goats Caseous lymphadenitis Echinococcosis Liver fluke Lower respiratory tract infection Lungworm

0.27 0.10

0.40 0.15

0.55 0.22

0.18 0.28

0.27 0.40

0.38 0.52

0.18 0.28

0.27 0.40

0.39 0.52

0.18 0.19

0.27 0.26

0.39 0.36

0.49 0.40

0.76 0.57

0.84 0.69

0.49 0.40

0.76 0.57

0.84 0.69

0.49 0.31

0.76 0.40

0.84 0.54

0.01

0.03

0.06

0.06

0.14

0.25

0.06

0.14

0.25

0.05

0.12

0.22

0.08

0.18

0.29

0.08

0.18

0.29

0.07

0.16

0.26

0.00 0.01

0.00 0.02

0.00 0.04

0.18 0.33

0.24 0.47

0.36 0.59

0.18 0.33

0.24 0.47

0.36 0.59

0.16 0.23

0.24 0.34

0.33 0.42

0.18 0.34

0.25 0.47

0.36 0.62

0.18 0.34

0.25 0.47

0.36 0.62

0.16 0.25

0.24 0.34

0.33 0.45

0.14

0.22

0.35

0.16

0.22

0.41

0.16

0.22

0.41

0.16

0.22

0.41

0.32

0.50

0.72

0.32

0.50

0.72

0.32

0.50

0.72

0.07

0.09

0.14

0.14

0.20

0.28

0.14

0.20

0.27

0.14

0.20

0.27

0.21

0.28

0.41

0.21

0.28

0.40

0.21

0.28

0.40

Orf disease Pulmonary adenomatosis / Maedi-Visna Arthritis Broken bones Bruising Diarrhoea or Soiling Leg and foot disorders Mastitis Partial vaginal prolapse/Hernia Poor body condition Sheep scab

0.19

0.27

0.34

0.04

0.06

0.08

0.00

0.00

0.00

0.00

0.00

0.00

0.25

0.33

0.40

0.19

0.27

0.34

0.19

0.27

0.34

0.14

0.24

0.34

0.07

0.13

0.20

0.06

0.10

0.17

0.06

0.10

0.17

0.23

0.39

0.50

0.22

0.33

0.48

0.22

0.33

0.48

0.23 0.76 0.01

0.34 0.95 0.02

0.48 0.98 0.07

0.14 0.49 0.23

0.21 0.65 0.31

0.32 0.65 0.42

0.14 0.27 0.23

0.21 0.50 0.31

0.32 0.49 0.42

0.11 0.27 0.23

0.15 0.50 0.31

0.23 0.49 0.42

0.41 0.90 0.25

0.58 0.98 0.34

0.74 0.99 0.47

0.41 0.86 0.25

0.58 0.97 0.34

0.74 0.99 0.47

0.37 0.86 0.25

0.53 0.97 0.34

0.66 0.99 0.47

0.49

0.66

0.71

0.07

0.10

0.13

0.06

0.09

0.13

0.06

0.09

0.13

0.58

0.74

0.80

0.57

0.75

0.80

0.57

0.75

0.80

0.11

0.16

0.22

0.04

0.05

0.07

0.04

0.05

0.07

0.04

0.05

0.07

0.16

0.21

0.28

0.16

0.21

0.28

0.16

0.21

0.28

0.03

0.05

0.10

0.12

0.18

0.27

0.12

0.18

0.27

0.12

0.18

0.27

0.16

0.26

0.34

0.16

0.26

0.34

0.16

0.26

0.34

0.23

0.31

0.44

0.01

0.01

0.04

0.01

0.01

0.04

0.01

0.01

0.04

0.24

0.32

0.46

0.24

0.32

0.46

0.24

0.32

0.46

0.35

0.45

0.56

0.28

0.34

0.41

0.27

0.33

0.39

0.27

0.33

0.39

0.68

0.85

0.86

0.67

0.82

0.85

0.67

0.82

0.85

0.24

0.36

0.57

0.00

0.00

0.01

0.00

0.00

0.00

0.00

0.00

0.00

0.24

0.39

0.58

0.24

0.37

0.58

0.24

0.37

0.58

BT FMD


29


9. Stage 3 9.1 Detection fraction model From the two endemic diseases (liver fluke and lower respiratory diseases) and two welfare conditions (leg and foot disorder inc. footrot and sheep scab) included in this stage, sheep scab yielded with 23.7% the highest fraction of affected animals that could be detected with clinical surveillance. With a combination of the two surveillance system components the detection fraction was significantly higher for liver fluke, lower respiratory diseases and leg and foot disorders including footrot but not for sheep scab, with liver fluke having the highest detection fraction out of the four diseases. The change in post mortem inspection protocol did not affect the detection fraction of the diseases and welfare conditions (Table 10). Stratum-specific outputs for mild and typical cases are presented in Appendix D, Tables D1.1 – D1.4.

Table 10: The detection fractions for clinical surveillance and combined abattoir and clinical surveillance for endemic diseases: liver fluke and lower respiratory tract infection and welfare conditions: leg and foot disorders and sheep scab. Disease or welfare condition Endemic

Lower respiratory diseases

Welfare

Liver fluke

Leg and foot disorders Sheep scab

Clinical surveillance only 0.05 ML 0.95 0.072 0.094 0.127

Combined abattoir and clinical surveillance Current Intermediate Visual only 0.05 0.95 0.05 0.95 0.05 0.95 ML ML ML 0.356 0.451 0.510 0.356 0.449 0.510 0.356 0.450 0.510

0.037

0.048

0.065

0.182

0.225

0.253

0.182

0.219

0.253

0.169

0.194

0.236

0.064

0.081

0.101

0.153

0.193

0.223

0.153

0.180

0.223

0.153

0.186

0.223

0.157

0.237

0.300

0.211

0.312

0.377

0.210

0.298

0.376

0.210

0.298

0.376

9.2 Component sensitivity model Clinical surveillance had a greater sensitivity for detecting FMD than abattoir surveillance, with the sensitivity increasing with an increase in population size (Table 11). This indicates that for those countries in Europe with a large sheep population, clinical surveillance is highly effective for detecting at least one case of FMD in an infected sheep. For countries with high slaughter numbers of sheep, for example Spain and UK (Eurostat, 2010), the abattoir surveillance is capable of detecting the disease (estimates based on the monthly number of slaughtered animals with a design prevalence of 0.2%).

Table 11: The abattoir and clinical surveillance sensitivities for FMD. Population size (n) 100,000 1,000,000 10,000,000

Abattoir inspection

Clinical surveillance 0.05 0.320 0.979 1.000

ML 0.613 1.000 1.000

0.95 0.801 1.000 1.000

0.05 0.006 0.059 0.457

Current ML 0.016 0.181 0.961

0.95 0.043 0.358 0.988

Intermediate 0.05 0.95 ML 0.006 0.015 0.044 0.059 0.154 0.358 0.450 0.972 0.988

Visual only 0.05 0.95 ML 0.006 0.016 0.043 0.059 0.157 0.358 0.446 0.983 0.989


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DISCUSSION 10. Methodological considerations 10.1

General considerations

The data obtained for the project was biased towards sheep rather than goats. This occurred for two reasons: a – the availability of data from the literature were biased towards sheep, possibly because of the greater sheep population within Europe (Eurostat, 2010) and b – the experts did not comment on the detection of diseases and welfare conditions being different for goats in the questionnaire. This was probably due to differences in the farming system in the countries of our expert’s expertise. The role of meat inspection in surveillance for animal disease and welfare conditions is poorly covered in the scientific literature. This is likely due to the fact that meat inspection has a focus on the public health aspects rather than animal health. Consequently, considering the scope of this work where a large number of diseases and welfare conditions were to be covered, it was deemed necessary to use expert opinion to capture the information needed for modelling. Data to parameterise the models were also obtained from the literature. Publications originated from many geographical regions of Europe and the world, particularly for exotic diseases. For example RVF which has not been encountered in Europe, and FMD where endemic situations and hence values, can be found outside of Europe. When interpreting the results we therefore need to take into account that the values are inferred even from European data, where areas may vary with respect to environmental conditions and farming techniques that may influence disease states and the resulting data. Inference is also a factor for consideration for data elicited from the experts; one of which had no extensive experience with small ruminant disease in Europe and the other experts had extensive knowledge of diseases and welfare conditions primarily for the UK. The purpose of meat inspection is to remove carcasses that may contaminate the food chain and pose a risk to human health. Additionally, it is used to detect animal health and welfare issues. Some diseases are recognised and recorded by abattoir surveillance; however, commonly clinical signs are often recorded but not attributed to a disease, hence the inspection is not aimed at diagnosing specific welfare conditions and diseases. Therefore the probability of detection for many of the diseases and welfare conditions in the report are for clinical signs and lesions that could potentially be linked to a disease but not the actual disease unless specific diagnostic tests are carried out (unlikely at the abattoir). Some diseases and welfare conditions invoke a pathological response that enables them to be detected on the farm, this means that mostly mild or non-detectable cases reach the abattoirs. On the other hand, a number of diseases, for example liver fluke, are primarily noticed at the abattoir due to their pathology, unless they are detected beforehand and routine prophylaxis occurs. This would bias the commonness of diseases, welfare conditions and stages of case presentation at an abattoir and would mean that more mild and nondetectable cases would enter abattoir surveillance than ‘typical’ cases. Thus, it is crucial to consider that animals sent to slaughter are not fully representative of the whole population. Different body parts of animals will be consumed by humans in different countries, for example heads and feet are less likely to be enter the food chain in the UK, and as a result will get discarded without being inspected as is allowed in Regulation (EC) No 854/2004. This will increase the importance of detection at the ante mortem stage of inspection, reduce the detection of diseases such as FMD at post mortem and add country-level and cultural-level variability regarding the detection of various diseases. The number of diseases and welfare conditions considered in the stage 3 analysis was limited, and they were purposively chosen to represent different aspects of interest (exotic, endemic, welfare). Considering this, the results can be regarded as being valid for the specific diseases and welfare conditions under study, but inference to a larger range of diseases or welfare conditions should be executed with due care. In contrast, the analysis in stage 2 covered a broader range of relevant hazards for the respective species Supporting Publications 2012:EN-320 The present document has been produced and adopted by the bodies identified above as authors. This task has been carried out exclusively by the authors in the context of a contract between the European Food Safety Authority and the authors, awarded following a tender procedure. The present document is published complying with the transparency principle to which the Authority is subject. It may not be considered as an output adopted by the Authority. The European food Safety Authority reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors

31


and is more likely to provide a comprehensive picture of how changes in meat inspection may affect detection effectiveness. Still, although the selection of hazards was subject to a systematic process, its purpose was not to produce a representative selection of diseases and welfare conditions. 10.2

Data availability and quality

Many welfare conditions and diseases in the report are not notifiable and are therefore not officially reported, hence data for these were only available from the literature where farmers diagnosed the conditions, for example data from studies on diseases by Wassink et al. (2003) and Lusat et al. (2004), or from a farm survey, for example an ovine footrot study undertaken by Moore et al. (2005). Studies of farmer diagnoses have found that for some conditions, they are accurate but for others they are under or over reported which affects the accuracy of the parameter values used in the report (Kaler and Green, 2008). Quantitative information on possible risk factors categories was difficult to obtain and often unavailable in a suitable form with which to be used in the study. In this assessment, the parameters for the probability of detection are based on expert opinion. There is therefore uncertainty as to the true range of these values. We used experts with significant experience in meat inspection, small ruminant pathology, infectious diseases and animal welfare. However, each expert was not an expert in all fields (meat inspection, animal health and welfare). Expert opinion can be easily skewed particularly where a decline or inability to provide an answer led to data gaps. Given the diversity of diseases and welfare conditions, there were some which the experts had not encountered professionally. For the twenty diseases: none of the experts had encountered cases of RVF; two experts acknowledged that they had not personally seen bTB in goats and one expert had not seen pulmonary adenomatosis, pneumonia or lower respiratory infections, possibly as a result of coming from a country outside of Europe with strict control measures and animal disease elimination programs hence limiting contact with the selected diseases. One expert declined to answer the questions for which they had no knowledge, whilst the others relied upon the definitions and literature (pers comm. with experts, 2012). None of the experts used in this report had seen RVF and therefore, they had to rely on the definitions provided in Table 2, with the clinical and pathological signs that would be encountered at the abattoir obtained from (Linklater, 1993; Gracey et al. 1999; Radostitis et al. 2000; Scott, 2007 and Merck, 2011). Therefore the detection probabilities elicited from the experts were based on how likely that depression and necrotic foci in liver would be discovered, without prior knowledge of the complete disease profile. However, the definitions provided to the experts were more representative of the disease in very young animals that are less likely to enter an abattoir (pers. comm. M. Domingo-Alvarez, 2012). Hence our results are an over-estimation of the probability of detection of the disease at the abattoir-level.

10.3

Modelling assumptions

The model focussed upon the detection probability of the surveillance components i.e. the ability to detect true positives and has not reviewed the impact of specificity on animal health and welfare. Although mild and typical cases were originally determined by the clinical signs or lesions observed in 60% of infected or affected animals present at slaughter (i.e. frequency of signs or lesions), in the model these were utilized as a measure of severity of the presentation of the disease. With the amalgamation of the mild and typical cases into detectable cases these differences may have been eliminated in the report. Another assumption applied was that the specificity of the meat inspection procedure was equal to 1, i.e. that all animals classified as detected with a specific syndrome were correctly classified and that there were no false positives. This is a reasonable assumption given that the classification is at the pathological syndrome level rather than for a specific diagnosis. As an example, it is reasonable to assume that animals without lesions in the respiratory tract would not be classified as having a respiratory condition. Given the Supporting Publications 2012:EN-320 The present document has been produced and adopted by the bodies identified above as authors. This task has been carried out exclusively by the authors in the context of a contract between the European Food Safety Authority and the authors, awarded following a tender procedure. The present document is published complying with the transparency principle to which the Authority is subject. It may not be considered as an output adopted by the Authority. The European food Safety Authority reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors

32


syndromic character of several of the case definitions, many different biological hazards could cause the pathological expression described, and in no case the classification was taken further than a macroscopic detection of the described lesions. In other words, any further diagnostic work-up to confirm or reject a particular diagnosis in the abattoir was not taken into account. An assumption was made for stage 3 of the model that all small ruminants would be seen by a veterinarian, after the owner detected clinical signs. However, visits of veterinarians are likely to be concentrated to certain periods: lambing will be the period of the year when a sheep is most likely to be seen by a vet. In addition, sheep are dipped and shorn which is when a farmer may ask for a clinician’s opinion if there is a health problem with a sheep. Such concentration of veterinary visits can lead to under- or overestimation of the capacity of clinical surveillance to detect cases, depending on the season of the year. Seasonality was not modelled here. The component sensitivity models and detection fraction models (stage 3) were estimated with and without the inclusion of animal level and herd level risk factors in the model (risk category nodes 1 and 3). This was to take into account that no recent information on parameter values for risk factors was available in the literature. Some studies dated back to the mid-70s and 80s and the disease profile may have altered since (Appendix B, Table B1); other studies originated from outside of Europe, leading to potential problems of inference. The results from both estimations were not significantly different with the exception of liver fluke and clinical only surveillance (see Tables 10 and 11 for results without risk categories and Appendix D, Table D2 for results with risk categories). We therefore decided to report unadjusted results only in the report.

11. Implications of results 11.1

The probability of detection by meat inspection and the effect of changing the post mortem

protocol The models showed that ante mortem inspection is important for detecting welfare issues, with significantly higher probabilities of detection than at post mortem inspection for four out of nine welfare conditions and with three more welfare conditions with higher, but non-significant, detection probabilities for ante mortem than post mortem inspection. Bruising and mastitis were exceptions in that sense as for these two welfare conditions post mortem inspection was shown to be significantly better. Welfare conditions are often of an external nature, for example sheep scab, hence the higher detection probabilities and removal of animals before the post mortem inspection which may re-enforce the higher detectability at ante mortem. In contrast diseases such as lungworm infestation and echinococcosis are more likely to be detected during post mortem inspection due to the internal nature of the infection and consequent sequelae. However, there is variability within and between abattoirs with regards to the experience of workers, time in lairage, the size of the areas that animals walk through which allow opportunities to detect welfare conditions (Enoe et al. 2003; pers. comm. experts, 2012). Post mortem inspections had a greater probability at detecting endemic diseases than welfare conditions and exotic diseases. For some diseases and welfare conditions such as FMD, sheep scab and prolapses, the post mortem inspection had a very low probability of detection irrespective of the inspection scenario, when considering detectable cases. For the welfare conditions, this may be due to animals having been removed from the inspection process at ante mortem inspection and on the farm. For exotic diseases, generally a low probability of detection would be expected at the abattoir in non-epidemic years given that the prevalence would be low. A study by Mousey et al. (1997), confirmed that there are low detection rates for diseases that circulate at low levels within populations.


33


The change in post mortem inspection protocol from the current to a visual only inspection did reduce the probability of detection for many detectable cases of diseases and welfare conditions, but not significantly. Yet, for bTB in goats, liver fluke and Orf disease, the differences between the current and the visual protocol, were distinct. The model results therefore suggest for the twenty diseases and welfare conditions selected for this project that the overall detection probability of meat inspection would not significantly be reduced if the incision of lymph nodes and the palpation of viscera were removed from the protocol. However, such a change in inspection could have an impact on liver fluke, bTB in goats and Orf disease, because the sensitivity of the current post mortem inspection protocol for these three diseases was higher compared to the intermediate or visual only inspection protocol. If unpasteurised milk or infected meat from bTB-positive goats entered the food chain this could have public health implications (Crawshaw et al. 2008). If liver fluke was not detected this could lead to misleading control decisions if meat inspection data were used by farmers or vets (Morgan et al. 2011).

11.2

The relative contribution of meat inspection to overall disease surveillance

Our results support the experts’ opinions that for exotic diseases, for example FMD, cases would primarily be detected on the farm and that surveillance at the abattoir would contribute at a very low level to the disease detection, especially for European countries with a small population of small ruminants. On the contrary, both clinical and abattoir surveillance components were highly effective for large populations of a million or more heads, that are found in Bulgaria, France, Germany, Greece, Hungary, Ireland, Italy, Netherlands, Portugal, Romania, Spain and UK (Eurostat, 2010). The influence of sample size and test sensitivity for the detection of at least one infected case is well documented for example in articles by Carpenter and Gardner (1996) and Thurmond (2003). The change in the post mortem protocol made no significant difference to the sensitivity of the surveillance components for FMD. For leg and foot disorders including footrot, liver fluke and lower respiratory diseases the detection fraction incorporating both clinical and abattoir surveillance was significantly greater than for clinical surveillance alone. This may initially be surprising for footrot but may be a result of the pathogen often not being readily diagnosed with clinical surveillance. Severe cases of liver fluke or lower respiratory infection may be detected clinically but mild cases would rather be detected at post mortem. For sheep scab abattoir surveillance added little to the detection fraction of the condition, this would be due to the external nature of the disease which can be spotted by farmers and clinicians prior to animals being sent to the abattoir. Knowledge about zoonotic disease and welfare derived from the abattoir is most useful if feedback is provided in order to improve animal health and welfare. A study by Edwards et al. (1999), led to farmers being aware of the health status of their animals and the risk factors involved with the disease so that they could improve their animal husbandry with regards to pneumonia and liver fluke. Our results show that for several diseases for example liver fluke, the detection probability of abattoir inspection is high; therefore reporting cases of liver fluke back to the farmers would prove useful in order for them to improve their management leading to improved animal health and welfare. Changing the post mortem protocol made no significant difference to the detection fraction for the endemic and welfare diseases. There was no significant difference in the detection fraction and the component sensitivity when the decision tree models were extended to include animal and herd level risk factors. The legal requirements of the abattoir inspection are irrespective of the animal or herd origin; therefore every animal should in practice get the same attention during meat inspection (pers. comm. experts, 2012). This should lead to a comparable detection probability for every infected or affected animal given that typical and mild signs/lesions are present.


34


12. Conclusions The probability of detection has indicated that ante mortem inspection is effective for detecting animal welfare diseases. For endemic diseases, post mortem inspection is effective at detecting mild and typical cases but not as effective at detecting all cases hence cases may be missed and the effectiveness of control measures underestimated. The overall inspection (ante mortem and post mortem combined) was effective for most of the diseases and welfare conditions provided by the AHAW WG, indicated by the high probability of detection of detectable cases. This indicates that the total meat inspection process could be relied upon to monitor diseases and welfare conditions. The change in the post mortem inspection scenario only had a noteworthy impact on the detection of three diseases (bTB in goats, liver fluke and Orf disease) all of which are endemic and are potentially hazardous to public health when detectable cases were considered. When all cases were taken into consideration, the impact of the change of inspection protocol diminished. Abattoir surveillance could detect exotic disease in large populations of sheep (circa 10 million individuals) that occur in few European countries, and may not be suitable as a sole method of surveillance in European countries with smaller populations. Although clinical surveillance appears to be more sensitive than meat inspection for detecting incursions of exotic disease, meat inspection is important as a back-up system, in particular in situations when the awareness of exotic disease as a differential diagnosis is low. For example, this may be the case prior to detection of an index case, in particular where there is a high prevalence of endemic diseases with similar manifestations. This was the case with the FMD epidemic in United Kingdom, which was ultimately detected in the abattoir but not through routine meat inspection tasks (Gibbens et al. 2001). For two endemic diseases and one welfare condition the addition of abattoir inspection to clinical inspection significantly improved the detection of cases demonstrating the validity of abattoir inspection. However, for the welfare condition sheep scab, abattoir surveillance was less effective at enhancing the detection of the condition and would not be an effective method for detecting cases.


35


REFERENCES Abbott KA and Whittington RJ, 2003. Monte-Carlo simulation of flock-level sensitivity of abattoir surveillance for ovine paratuberculosis. Preventive Veterinary Medicine, 61, 309-332. Abbott KA and Lewis CJ, 2005. Current approaches to the management of ovine footrot. The Veterinary Journal, 169(1), 28-41. Anonymous, 2004. Regulation (EC) No 854/2004 of the European Parliament and of the Council of 29 April 2004 laying down specific rules for the organisation of official controls on products of animal origin intended for human consumption. Official Journal of the European Union, L 139, 2 (30.4.2004). Barnett PV and Cox SJ, 1999. The role of small ruminants in the epidemiology of foot and mouth disease. Veterinary Journal, 158, 6-13. Berends BR, Snijders JMA and Van Logtestijn JG, 1993. Efficacy of current EC meat inspection procedures and some proposed revisions with respect to microbiological safety: a critical review. Veterinary record, 133, 411-415. Berends BR, Van Knapen F and Snijders JMA, 1996. Suggestions for the construction, analysis and the use of descriptive epidemiological models for the modernisation of meat inspection. International Journal of Food Microbiology, 30, 27-36. Bishop SC and Morris CA, 2007. Genetics of disease resistance on sheep and goats. Small Ruminant Research, 70(1), 48-59. Bonde M, Toft N, Thomsen PT and Sorensen JT, 2010 Evaluation of sensitivity and specificity or routine meat inspection of Danish slaughter pigs using Latent Class Analysis. Preventive Veterinary Medicine, 94, 165-169. Carpenter TE, and Gardner IA, 1996. Simulation modelling to determine herd-level predictive values and sensitivity based on individual-animal test sensitivity and specificity and sample size, Preventive Veterinary Medicine, 27, 57-66. Crawshaw T, Daniel R, Clifton-Hadley R, Clark J, Evans H, Rolfe S, and de la Rua Domenech R, 2008. TB in goats caused by Mycobacterium bovis. Veterinary Record, 163(4), 127-127. Edwards DS, Christiansen KH, Johnston AM and Mead GC, 1999 Determination of farm-level risk factors for abnormalities observed during post-mortem meat inspection of lambs: a feasibility study. Epidemiology and Infection, 123, 109-119. Enoe C, Christensen G, Andersen S and Willeberg P, 2003. The need for built-in validation of surveillance data so that changes in diagnostic performance of post-mortem meat inspection can be detected. Preventive Veterinary Medicine, 57, 117-125. Eurostat, 2010, http://epp.eurostat.ec.europa.eu/portal/page/portal/agriculture/data/database, March, 2012. Food and agricultural organisation (FAO), 1999. Codex Alimentarius Commission: food hygiene basic texts. 2nd Edition, Rome Italy. Gibbens JC, Sharpe CE, Wilesmith JW, Mansley, LM, Michalopoulou E, Ryan JBM and Hudsom M, 2011. Descriptive epidemiology of the 2001 foot-and-mouth disease epidemic in Great Britain: the first five months. The Veterinary Record, 149, 729-743. Gracey JF, Collins DS and Huey RJ, 1999. Meat Hygiene. 10th Edition. W. B. Saunders, London. Hathaway SC, Pullen MM and Mckenzie AI, 1988. The model for the risk assessment of organoleptic post-mortem inspection procedures for meat and poultry. Journal of the American Veterinary Medicine Association, 192(7), 960-966.


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Hathaway SC and Mckenzie AI, 1989. The impact of ovine meat inspection systems on processing and production costs. Veterinary Record, 124, 189-193. Hecht AR, 1977. A modified Delphi Technique for obtaining consensus on institutional research priorities. Paper presented at the Annual Meeting of the North Central Region AERA Special Interest Group on Community College Research, July 77 Hernandez-Jover M, Cogger N, Martin PAJ, Schembri N, Holyoake PK and Toribio J-ALML, (2011) Evaluation of post farm-gate passive surveillance in swine for the detection of foot and mouth disease in Australia. Preventive Veterinary Medicine, 100, 171-186. Hsu CC and Sandford BA, 2007. The Delphi Technique: Making sense of consensus. Practical Assessment Research and Evaluation, 12(10), 1 – 8 Jackowiak J, Kiermeier A, Kolega V, Missen G, Reiser D and Pointon AM, 2006 Assessment of producer conducted ante mortem inspection of market pigs in Australia. Australian Veterinary Journal, 84, 195201. Jones GE, Road WM and Park A, 1979. Respiratory infections in housed sheep, with particular reference to Mycoplasmas. Veterinary Microbiology, 4, 47-59. Kaler J and Green LE, 2008. Naming and recognition of six foot lesions of sheep using written and pictorial information: A study of 809 English sheep farmers. Preventive Veterinary Medicine, 83, 5264. Knol AB, Slottje P, Van Der Sluijs JP, lebret E., 2010. The use of expert elicitation in environmental health impact assessment: a seven step procedure. Environmental Health, 9, 19. Linklater KA, 1993. Colour Atlas of diseases and disorders of the sheep and goat. Wolfe, London. Lusat J, Morgan ER. and Wall R, 2009. Mange in alpacas, llamas and goats in the UK: incidence and risk. Veterinary parasitology, 163, 179-184. Martin PAJ, Cameron AR and Greiner M, 2007. Demonstrating freedom from disease using multiple complex data sources 1: A new methodology based on Scenario trees. Preventive Veterinary Medicine, 79, 71-79. Merck Veterinary Manual, www.merckvetmanual.com/mvm/index,jsp, December 2011. Moo D, O’Boyle D, Mathers W and Frost AJ, 1980, The isolation of Salmonella from jejuna, caecal lymph nodes of slaughtered animals. Australian Veterinary Journal, 56,181. Moore LJ, Wassink GJ, Green LE. and Grogono-Thomas R, 2005. The detection and characterisation of Dichelobacter nodosus from the cases of ovine footrot in England and Wales. Veterinary Microbiology, 108, 57-67. Morgan ER, Hosking BC, Burston S, Carder KM, Hyslop AC, Pritchard LJ, Whitmarsh AK, and Coles GC, (2011). A survey of helminth control practices on sheep farms in Great Britain and Ireland. Veterinary Journal (In Press). Mousing J, Kyrval J, Jensen TK, Aalbaek B, Buttenschon J, Svensmark B, Willeberg P, 1997. Meat safety consequences of implementing visual post-mortem meat inspection procedures in Danish slaughter pigs. Veterinary record, 140, 472-477. Ostertag R. 1892. Handbuch de Fleisch beschau fur Tierzte, Artze unde Richter. 1st Edition, Stuttgart, F. Enke. Radostitis OM, Gay CC, Blood DC. and Hinchcliff KW, 2000. A textbook of the diseases of cattle, sheep, small ruminants, goats and horses. 9th Edition, Saunders, London. Rose H and Wall R, 2011. Endemic sheep scab: Risk factors and the behaviour of up-land sheep flocks. Preventive Veterinary Medicine, 69, 1-6. Supporting Publications 2012:EN-320 The present document has been produced and adopted by the bodies identified above as authors. This task has been carried out exclusively by the authors in the context of a contract between the European Food Safety Authority and the authors, awarded following a tender procedure. The present document is published complying with the transparency principle to which the Authority is subject. It may not be considered as an output adopted by the Authority. The European food Safety Authority reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors

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Sargisson N. C. and Scott P. D. 2011. Diagnosis and economic consequences of triclabendazole resitance in Fasciola hepatica in a sheep flock in South-East Scotland. Veterinary Record, 168, 159-165. Schemann AK, Hernandez-Jover M, Hall W, Holyoake PK and Toribio JALML, 2010. Assessment of current disease surveillance activities for pigs, post-farm gate in New South Wales. Australian Veterinary Journal, 88(3), 75-83. Scott PR, 2007. Sheep Medicine. 1st Edition. Manson Publishing, London. Thurmond MC, 2003. Conceptual foundations for infectious disease surveillance. Journal of Veterinary Diagnostic Investigation, 15(6), 501-514. Wassink GJ, Grogono-Thomas R, Moore LJ and Green LE, 2003. Risk factors associated with the prevalence of footrot in sheep from 1999 to 2000. Veterinary Record, 152, 351-358.


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APPENDICES A. Expert elicitation The questionnaires used to obtain data from experts with regards to case types (questionnaire 1) and parameter values for the model (questionnaire 2), can be found in Al – questionnaire 1, A2 – questionnaire 2 and A3 – additional information for questionnaire 2.


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EXPERT ELICITATION QUESTIONNAIRE 1– Case definitions of selected diseases and condition of small ruminants

EXPERT ELICITATION EFSA PROJECT “Contribution of meat inspection to animal health and welfare surveillance” The project aims at evaluating the sensitivity of current and alternative meat inspection scenarios to detect major animal health and welfare diseases and conditions, as well as comparing the capacity of different surveillance systems to protect animal health and welfare. You have been invited to participate in a series of expert elicitations as an expert in diseases and/or meat inspection of small ruminants. The aim of this expert elicitation is to collect information and opinions on the diagnosis of animal health and welfare conditions at meat inspection. The diseases and animal welfare issues included in the various questionnaires that you will receive were identified by a working group under EFSA’s Animal health and Welfare Panel (AHAW) and prioritized according to their likelihood of detection at ante- and/or post-mortem inspection and their relevance to animals of slaughter age. Please note that diseases/conditions that are predominantly zoonotic, rather than animal health and welfare related, were excluded. The results will be presented afterwards in aggregated form without identifying the data source or disclosing confidential information. This work is conducted under a contract with EFSA, who will have ownership to the project report. EFSA may, or may not, decide to make the report accessible to the public. However, the main purpose of the report is to support the AHAW working group in its assessment of the contribution of meat inspection to animal health surveillance.

Expert elicitation process - Information Three experts will participate in this elicitation. The outcome from each of them will be combined to come up with answers that agree the most to the experts’ opinions. The elicitation will run in three parts: Questionnaire 1 - Elicitation of clinical disease pictures You will receive a questionnaire listing 20 diseases and conditions of small ruminants, along with a list of potential clinical signs and lesions found during ante- and post mortem meat inspection. You will be asked to indicate which of these signs and lesions are seen in a “typical” and in a “mild” case of the disease or condition. Signs and lesions that have been selected by two or more of the


experts will automatically be included in the case definitions of “typical” or “mild” diseases or conditions Questionnaire 2 - Elicitation of sensitivity of meat inspection to detect each disease. You will receive a questionnaire listing 20 diseases. For each of them you will be required to answer a few questions, including providing estimates for the capacity of various meat inspection tasks to detect the disease. Final teleconference to discuss specific estimates (2 hours) The objective of this teleconference will be to discuss specific estimates where experts disagree in order to come up with the most accurante estimate. In the following pages you will find Questionnaire 1, which is divided in parts 1.A and 1.B. Please complete both and return them to us by Friday, 16/12/11


QUESTIONNAIRE 1 – Clinical pictures of diseases of small ruminants Purpose of the questionnaire The aim of this questionnaire is to collect information on clinical pictures and meat inspection lesions of major health and welfare diseases and conditions of small ruminants of slaughter age. It consists of two main parts, 1.A and 1.B; the first one deals with the “typical” form of the diseases or conditions and the second part with the “mild” forms. You are presented with a list of 20 diseases and conditions of small ruminants. Your answers to this questionnaire will be used by our project team as inputs to prepare questionnaire 2. Questionnaire information Please insert all your answers into this questionnaire and email it back to the email below Please feel free to add comments whenever an answer needs further explanation. Please indicate if a question is not clear to you or if you feel that a question is beyond your expertise – we will then contact you after you return the questionnaire to us to discuss these questions together. If you have any further questions, please do not hesitate to contact me on [email protected] or on (+44) (0) 7780 865545 Thank you for your participation and for your valuable contribution to this project!


Note: 2 Key points for completing this questionnaire: 1. For the purposes of this questionnaire, “typical” case of a disease or condition is “…the combination of clinical signs and post mortem findings (lesions) that will be present in >60% of slaughter animals infected or affected by the disease or condition” 2. Slaughter animals here are defined as the group of animals normally seen in abattoirs for slaughter. This can differ from country to country and, depending on the condition or disease, may mean sometimes younger or sometimes older animals. For example, if a condition is seen only (or predominantly) in older animals (e.g. mastitis, vaginal prolapse) than ONLY this group of animals should be taken into account for that particular question


Part I: I.a

ANIMAL DISEASES

Epidemic (fast spreading) diseases

A) Foot and Mouth Disease (FMD) Here is a list of possible clinical signs and pathological findings associated with FMD. Please select those that you think will be present in a typical case of FMD (i.e. signs or findings likely to be present in >60% of slaughter animals infected with FMD). NOTE: Tick on a box twice to select it (tick it) – a new window will appear where you can select “checked”. Case definition Ante mortem: FEVER DULLNESS. APATHY LAMENESS SALIVATION STOMATITIS WITH VESICLES, EROSIONS AND ULCERS VESICLES AND EROSIONS IN INTERDIGITAL SPACE SWELLING OF CORONET VESICLES AND EROSIONS IN CORONET UNDERGROWING OF SOLE LOSS OF CLAW VESICLES AND EROSIONS ON TEATS AND UDDER MASTITIS OTHER (please specify)

Post mortem: EROSIONS AND ULCERS IN ALIMENTARY TRACT (OES, FORESTOMACHES, INTESTINE) VESICLES AND EROSIONS IN TRACHEA AND BRONCHI MYOCARDIUM: STRIPED APPEARANCE (I.E. NECROSIS, FIBROSIS) (“TIGER HEART”) SKELETAL MUSCLES: STRIATED APPEARANCE (I.E.DEGENERATION) OTHER (please specify)


B) Bluetongue Here is a list of possible clinical signs and pathological findings associated with Bluetongue. Select those that you think will be present in a typical case of Bluetongue (i.e. signs or findings likely to be present in >60% of slaughter animals infected with Bluetongue). Case definition Ante mortem: FEVER SALIVATION WATERY NASAL DISCHARGE BLOODY NASAL DISCHARGE CONJUNCTIVITIS LACRIMATION FACIAL SWELLING / OEDEMA SWELLING/OEDEMA OF EARS SWELLING/OEDEMA OF LIPS SWELLING/OEDEMA OF TONGUE CYANOTIC TONGUE SWELLING/OEDEMA OF SUBMANDIBULAR REGION DYSPNOEA ULCERS IN MOUTH (LIPS, TONGUE, BUCCAL MUCOSA ETC.) LESIONS IN CORONET. CORONITIS LAMINITIS LAMENESS DIARRHOEA TORTICOLLIS (“WRYNECK”) LOSS OF FLEECE OTHER (please specify)

Post mortem: LESIONS IN OESOPHAGUS AND/OR FORESTOMACHS (HYPERAEMIA, HAEMORRHAGES, EROSIONS, ULCERS) LESIONS IN ABOMASUM (HYPERAEMIA, EROSIONS, ULCERS) LESIONS IN THE INTESTINE (HYPERAEMIA, HAEMORRHAGES) HAEMORRHAGES AT BASE OF PULMONARY ARTERY HAEMORRHAGES IN MYOCARDIUM


PNEUMONIA HYDROTHORAX. HYDROPERICARDIUM PERICARDITIS OEDEMA, HAEMORRHAGES AND/OR NECROSIS IN SKELETAL MUSCLE OTHER (please specify)

C) Rift Valley Fever (RVF) Here is a list of possible clinical signs and pathological findings associated with RVF. Select those that you think will be present in a typical case of RFV (i.e. signs or findings likely to be present in >60% of slaughter animals infected with RVF). Case definition Ante mortem: FEVER INCOORDINATION LISTLESSNESS DEPRESSION ABDOMINAL PAIN FOUL SMELLING DIARRHOEA OTHER (please specify)

Post mortem: ICTERUS NECROTIC FOCI IN LIVER ENLARGED, SOFT, FRIABLE LIVER EXTENSIVE HEPATIC NECROSIS DARK, CHOCOLATE COLOUR, INTESTINAL CONTENTS ENLARGED AND OEDEMATOUS SPLEEN PETECHIAE IN SPLEEN PETECHIAE IN HEART PETECHIAE IN ALIMENTARY TRACT HAEMORRHAGES IN SEROUS MEMBRANES/SURFACES ENLARGED AND HEAMORRHAGIC PERIPHERIC LNN OTHER (please specify)


I.b

Non-epidemic (slow spread or not contagious) diseases D) Pneumonic pasteurellosis (PP) (Enzootic pneumonia)

Here is a list of possible clinical signs and pathological findings associated with PP. Select those that you think will be present in a typical case of PP (i.e. signs or findings likely to be present in >60% of slaughter animals affected by pneumonic pasteurellosis). Case definition Ante mortem: DYSPNOEA FROTHING FROM MOUTH FEVER DEPRESSION MUCOPURULENT NASAL DISCHARGE RESPIRATORY SOUNDS (HISSING, PITCHING) ILLTHRIFT COUGHING LETHARGY OTHER (PLEASE SPECIFY)

Post mortem: LESIONS OF PNEUMONIA (EXTENSIVE DARK RED CONSOLIDATION – “HEPATISATION”) IN APICAL, CARDIAC AND CRANIAL PART OF DIAPHRAGMATIC LOBES GREENISH PLEURAL EXUDATE GREENISH, NECROTIC AREAS IN LUNGS LUNG ABSCESSES CHRONIC PLEURISY (FIBRIN, ADHESIONS) ENLARGED, OEDEMATOUS, HAEMORRHAGIC LUNGS HAEMORRHAGES (PETECHIAE, ECCHYMOSES) THROUGHOUT THE BODY FIBRINOUS EXUDATE IN PERITONEAL CAVITY OTHER (PLEASE SPECIFY)


E) Maedi – Visna (MV) (Pneumonic form) – Ovine Pulmonary Adenomatosis (OPA) Here is a list of possible clinical signs and pathological findings associated with the pneumonic form of MV. Select those that you think will be present in a typical case of MV or OPA (i.e. signs or findings likely to be present in >60% of slaughter animals infected with M-V or POA). Case definition Ante mortem: POOR BODY CONDITION. EMACIATION DYSPNOEA COUGHING NASAL DISCHARGE LARGE AMOUNTS OF NASAL DISCHARGE DEPRESSION MASTITIS (“HARDBAG”) SWOLLEN JOINTS. ARTHRITIS OTHER (please specify) Post mortem: GROSSLY ENLARGED AND HEAVY LUNGS COALESCING GREYISH SPOTS/AREAS ON LUNGS GREY AND SOLID APPEARANCE OF CUT SURFACE OF LESIONS IN LUNGS FROTHY FLUID IN CUT SURFACE OF LUNG PARENCHYMA FROTHY FLUID IN TRACHEA / BRONCHI PLEURISY SECONDARY BRONCHOPNEUMONIA (ABSCESSES ETC.) ENLARGED AND OEDEMATOUS BROCHIAL AND MEDIASTINAL LNN MASTITIS ARTHRITIS OTHER (please specify)

F) Lungworm related conditions Here is a list of possible clinical signs and pathological findings associated with lungworm. Select those that you think will be present in a typical case of lungworm (i.e.


signs or findings likely to be present in >60% of slaughter animals infected with lungworm). Case definition Ante mortem: COUGHING DYSPNOEA LOSS OF CONDITION FROTHY MUCOUS FROM NOSE OTHER (PLEASE SPECIFY) Post mortem: BRONCHITIS PNEUMONIA GREENISH, FROTHY EXUDATE IN BRONCHIAL MUCOSA OEDEMATOUS AND HAEMORRHAGIC BRONCHIAL MUCOSA HYALINE MEMBRANE IN BRONCHIAL MUCOSA (SECONDARY) BRONCHOPNEUMONIA YELLOWISH/BROWN SMALL FOCI IN LUNGS PULMONARY OEDEMA SCATTERED PATCHES OF CONSOLIDATION IN LUNGS FIBROUS OR CALCIFIED NODULES IN SUBPLEURAL LUNG PARENCHYMA INTERSTITIAL EMPHYSEMA PARASITES (WORMS) IN AIRWAYS GOATS: DIFFUSE INTERSTITIAL PNEUMONIA OTHER (PLEASE SPECIFY)

G) Caseous lymphadenitis (CL) Here is a list of possible clinical signs and pathological findings associated with CL. Select those that you think will be present in a typical case of CL (i.e. signs or findings likely to be present in >60% of slaughter animals infected with CL). Case definition Ante mortem: WASTING. EMACIATION ENLARGED, NOT PAINFUL, SUPERFICAL LNN IN HEAD/NECK


ENLARGED, NOT PAINFUL, SUPERFICIAL LNN IN BODY FISTULAE DRAINING PUS IN SKIN (ABOVE SUPERFICIAL LNN) LAMENESS ORCHITIS / MASTITIS RESPIRATORY SIGNS CNS SIGNS (ATAXIA, PARAPLEGIA ETC.) OTHER (please specify)

Post mortem: LAMINATED, ONION LIKE, ABSCESSES IN HEAD LNN LAMINATED, ONION LIKE, ABSCESSES IN BODY LNN LAMINATED, ONION LIKE ABSCESSES IN MEDIASTINAL LNN CASEOUS BRONCHOPNEUMONIA ABSCESSES IN LUNGS ABSCESSES IN LIVER ABSCESSES IN KIDNEYS ABSCESSES IN SPLEEN ABSCESSES IN SPINAL CORD ARTHRITIS PYELONEPHRITIS OTHER (please specify)

H) Tuberculosis (TB) in goats Here is a list of possible clinical signs and pathological findings associated with TB caused by Mycobacterium bovis in goats. Select those that you think will be present in a typical case of TB in this species (i.e. signs or findings likely to be present in >60% of slaughter animals infected with Mycobacterium bovis). Case definition Ante mortem: LOSS OF CONDITION. EMACIATION MOIST COUGH DYSPNOEA DULLNESS. APATHY ENLARGED RETROPHARYNGEAL LNN MASTITIS DIARRHOEA


OTHER (please specify)

Post mortem: ABSCESSES/GRANULOMAS IN HEAD LNN ABSCESSES/GRANULOMAS IN LUNG LNN (MEDIASTINAL AND BRONCHIAL) ENLARGED MESENTERIC LNN CASEOUS BRONCHOPNEUMONIA ABSCESSES IN THE LUNGS TUBERCULOUS LESIONS (NODULES, GRANULOMATA) IN INTESTINES ULCERS IN TONSILS, MOUTH ULCERS IN INTESTINES TUBERCULOUS LESIONS (NODES ETC.) IN PLEURA TUBERCULOUS LESIONS (NODES ETC.) IN PERITONEUM TUBERCULOUS LESIONS (NODULES, GRANULOMATA) IN SPLEEN TUBERCULOUS LESIONS (NODULES, GRANULOMATA) IN LIVER TUBERCULOUS LESIONS (NODULES, GRANULOMATA) IN UDDER TUBERCULOUS LESIONS (NODULES, GRANULOMATA) IN UTERUS TUBERCULOUS LESIONS (NODULES, GRANULOMATA) IN INTESTINES TUBERCULOUS LESIONS IN BONES (VERTEBRAE, RIBS) TUBERCULOUS LESIONS (NODULES, GRANULOMATA) IN KIDNEYS MILIARY TB LESIONS IN VARIOUS ORGANS OTHER (PLEASE SPECIFY)

I) Liver fluke (Fascioliasis) Here is a list of possible clinical signs and pathological findings associated with liver fluke. Select those that you think will be present in a typical case of liver fluke (i.e. signs or findings likely to be present in >60% of slaughter animals infected with Fasciola hepatica). Case definition Ante mortem: DULLNESS. APATHY WEAKNESS SUBMANDIBULAR OEDEMA OEDEMA OF FACE AND LIDS OEDEMA OF BRISKET


PALE AND OEDEMATOUS CONJUNCTIVAE PALE MUCOUS MEMBRANES EPISTAXIS PAINFUL LIVER AREAS (ON PALPATION) LOSS OF BODY CONDITION. EMACIATION LOSS OF WOOL OTHER (PLEASE SPECIFY)

Post mortem: ENLARGED, FRIABLE LIVER CIRRHOTIC/FIBROTIC LIVER THICKENED BILE DUCT WALLS (CHOLANGITIS) MATURE FLUKES IN BILE DUCTS NODULES (ENCAPSULATED IMMATURE FLUKES) IN PARENCHYMA HAEMORRHAGIC LIVER HAEMORRHAGIC MIGRATORY TRACTS IN LIVER PARENCHYMA PERITONITIS ENLARGED, DARK HEPATIC LNN ANAEMIC AND OEDEMATOUS CARCASE PERIHEPATITIS. ADHESIONS TO DIAPHRAGM ENCAPSULATED IMMATURE FLUKES (NODULES) IN OTHER ORGANS (MYOCARDIUM, SPLEEN, KIDNEYS ETC.) OTHER (PLEASE SPECIFY)

J) Echinococcosis/Hydatidosis Here is a list of possible clinical signs and pathological findings associated with Echinococcus spp. Select those that you think will be present in a typical case of hydatidosis (i.e. signs or findings likely to be present in >60% of slaughter animals infected with Echinococcus spp). Case definition Ante mortem: WASTING. EMACIATION OTHER (PLEASE SPECIFY)

Post mortem:


Hydatid cysts in liver Hydatid cysts in lungs Hydatid cysts in organs other than liver and lungs OTHER (please specify)

K) Orf disease (Contagious ecthyma) Here is a list of possible clinical signs and pathological findings associated with Orf disease. Select those that you think will be present in a typical case of lameness (i.e. signs or findings likely to be present in >60% of slaughter animals infected with Orf). Case definition Ante mortem: EROSIONS AND ULCERS IN MOUTH (BUCCAL, TONGUE ETC.) SWOLLEN EYELIDS MUCOPURULENT NASAL DISCHARGE AND CRUSTS IN NOSTRILS PAPULES, PUSTULES AND SCABS ON LIPS AND AROUND MOUTH DERMATITIS, SCABS AND OTHER LESIONS IN EARS POOR BODY CONDITION LESIONS IN CORONETS AND INTERDIGITAL CLEFTS WARTY, CAULIFLOWER GROWTHS IN MOUTH AND LIPS STOMATITIS. GINGIVITIS INFECTION OF TEATS MASTITIS EROSIONS AND SCAB IN EXTERNAL GENITALIA RESPIRATORY DISEASE SIGNS GASTROENTERITIS OTHER (PLEASE SPECIFY) Post mortem: FEVERISH CARCASE ULCERS IN UPPER RESPIRATORY TRACT (TRACHEA ETC.) ULCERS IN DIGESTIVE TRACT (SECONDARY) PNEUMONIA (SECONDARY) GASTROENTERITIS EMACIATED CARCASE ENLARGED HEAD LYMPHNODES ENLARGED BRONCHIAL AND MEDIASTINAL LYMPHNODES ENLARGED MESENTERIC LYMPHNODES




Part II:

ANIMAL WELFARE CONDITIONS

L) Diarrhoea / Soiling in slaughter animals Here is a list of possible clinical signs and pathological findings associated with diarrhoea. Select those that you think will be present in a typical case of diarrhoea (i.e. signs or findings likely to be present in >60% of slaughter animals affected by diarrhoea/soiling). Case definition Ante mortem: Soiled hind parts of animal Weight loss. Dehydration Tenesmus OTHER (please specify) Post mortem: Carcase dehydrated Carcase anaemic Intestines: hyperaemic with yellowish contents Intestines: oedema, hyperaemia, haemorrhages Intestines: Necrosis. Ulceration Foul smelling intestinal content Thickened intestinal wall Enlarged, congested, haemorrhagic Lnn Watery faeces with blood and/or mucous OTHER (please specify)

M) Partial vaginal prolapse / hernia Here is a list of possible clinical signs and pathological findings associated with vaginal prolapse. Select those that you think will be present in a typical case of vaginal prolapse (i.e. signs or findings likely to be present in >60% of slaughter animals with partial vaginal prolapse/hernia). Case definition


Ante mortem: Prolapsed mass Necrosis Bleeding Eventration Signs of toxaemia Prolapse of bladder Prolapse of intestinal loops OTHER (please specify) Post mortem: Lesions related to toxaemia Prolapsed vagina

N) (Poly-) Arthritis Here is a list of possible clinical signs and pathological findings associated with arthritis. Select those that you think will be present in a typical case of arthritis [i.e. signs or findings likely to be present in >60% of slaughter animals affected by (poly-) arthritis)]. Case definition Ante mortem: Lameness Swollen at joint(s) Hot joint(s) Joints painful on palpation and manipulation Injury on joint(s) Recumbency Draining sinuses Ankylosis Deformed joints OTHER (please specify) Post mortem: Increased amount of synovial fluid Turbid synovial fluid Thick, cloudy synovial fluid possibly with fibrin, pus, blood Thickened, inflamed synovial membranes Erosion of articular cartilage


Osteophytes Inflammation of periarticular tissues Granulomatous tissue on articular surface (pannus) OTHER (please specify)

O) Bruising Here is a list of possible clinical signs and pathological findings associated with bruising and skin lesions which are animal welfare related. Select those that you think will be present in a typical case of bruising (i.e. signs or findings likely to be present in >60% of slaughter animals affected by bruising). Case definition Ante mortem: enlarged joints enlarged sensitive udder enlarged/swollen jaw abnormal skin colour on back abnormal skin colour on flanks abnormal skin colour on legs abnormal behaviour (indicating pain) abnormal gait or posture (indicating pain) aggressive behaviour affected skin cold affected skin warm OTHER (please specify)

Post mortem: enlarged peripheral (carcase) lymph nodes, inflammation of viscera inflammation of joints recent/fresh (reddish) bruises on back recent/fresh (reddish) bruises on flanks recent/fresh (reddish) bruises on legs old (brown/green) bruises on back old (brown/green) bruises on flanks old (brown/green) bruises on legs



P) Broken bones Here is a list of possible clinical signs and pathological findings associated with broken bones (fractures). Select those that you think will be present in a typical case of broken bones (i.e. signs or findings likely to be present in >60% of slaughter animals with one or more broken bones). Case definition Ante mortem: Fracture in one leg Fracture in more than one legs Fracture in head Fracture in body Severe lameness Recumbency Deformity of extremities Abnormal movements of leg (if fracture on leg). “Hanging” leg etc. Visible bone (open fracture) Skin red, hyperaemic Area painful on palpation and manipulation Signs of septicaemia OTHER (please specify)

Post mortem: Fracture Fresh haemorrhage around fracture (fresh looking blood) Old haemorrhage around fracture: greenish blood, signs of absorption Hyperaemic tissues surrounding fracture Signs of healing: formation of fibrin, new bone etc. OTHER (please specify)

Q) Leg and feet disorders WITH signs (Foot rot etc.)


Here is a list of possible clinical signs and pathological findings associated with leg and feet disorders accompanied with signs (e.g. foot rot). Select those that you think will be present in a typical case of this condition (i.e. signs or findings likely to be present in >60% of slaughter animals found with leg and feet disorders WITH signs). Case definition Ante mortem: Slight lameness Severe lameness Animal disabled in one leg so that it can not walk properly Animal disabled in more than one legs, so that it can not walk properly Animal disabled in more than one legs, so that it can not stand on its feet (recumbent) Poor body condition. Emaciation Offensive smell Interdigital dermatitis (swollen, moist) Deformed claws Hairless and ulcerated knees and brisket Underrunning of hoof. Hoof detachment Necrosis of horn Fever Swollen, enlarged joint in one leg Swollen, enlarged joints in more than one legs OTHER (please specify)

Post mortem: Poor body condition. Emaciation Enlarged peripheral lymphnodes Lesions of arthritis in one leg Lesions of arthritis in more than one legs Feverish carcase Septicaemic carcase OTHER (please specify)

R) Poor body condition Here is a list of possible clinical signs and pathological findings associated with low body condition. Select those that you think will be present in a typical case of low body


condition (i.e. signs or findings likely to be present in >60% of slaughter animals affected by poor body condition). Case definition Ante mortem: Prominent bones Sunken eyes Loss of skin elasticity. Skin folds not returning to original state (“skin tenting test”) Recumbency OTHER (please specify) Post mortem: Loss of subcutaneous fat Carcase anaemic Carcase fat oedematous with jelly like appearance Carcase wet, not “setting” Reduced amount or loss of intra-cavities fat: peri-renal, mesenteric, omentum Reduced size of organs: Liver, spleen etc. Reduced size of muscles Enlarged and oedematous Lnn OTHER (please specify)

S) Sheep scab (Psoroptes ovis) Here is a list of possible clinical signs and pathological findings associated with sheep scab. Select those that you think will be present in a typical case of sheep scab (i.e. signs or findings likely to be present in >60% of slaughter animals infected with Psoroptes ovis). Case definition Ante mortem: Papules, pustules, scabs in body and head Matted, ragged fleece/wool Loss of wool. Bare patches. Alopecia Intense pruritus Poor body condition/emaciaton Anaemia


Weakness Mite infestation of ears. Exudate. Otitis OTHER (please specify)

Post mortem: Poor body condition. Emaciation OTHER (please specify)

T) Chronic or sub-acute mastitis Here is a list of possible clinical signs and pathological findings associated with chronic or sub-acute mastitis. Select those that you think will be present in a typical case of mastitis (i.e. signs or findings likely to be present in >60% of slaughter animals affected by chronic or sub-acute mastitis). Case definition Ante mortem: Swollen udder Hot, painful udder Watery, clotty milk (secretion) Milk (secretion): thick, yellow, pus, blood Blue/black, cold (i.e. gangrenous) Sloughing of dead tissue Lameness on affected side Abscesses Atrophic udder Enlarged supramammary Lnn General signs of toxaemia OTHER (please specify)

Post mortem: Oedema. Inflammation Fibrosis Abscesses Enlarged supramammary Lnn OTHER (please specify)


Questionnaire 1.B – Elicitation of “Mild” cases Questionnaire 1.B deals with the establishment of a definition of the “mild” form of the diseases and conditions encountered in Questionnaire 1A. In the table below, for each disease or condition please give up to two combinations of signs and lesions that in your opinion would describe the “mild” form of a disease. For the purposes of this questionnaire, the “mild” form of a disease or condition is the form that could be seen at the early stages of the disease or at some point between the subclinical and the fully developed (i.e. “typical” form of) disease.

A

DISEASE Foot and Mouth

B

Bluetongue

C

Rift Valley Fever

D

Lower respiratory tract infection or pneumonia (pneumonic pasteurellosis etc.) Maedi-Visna (pulmonary form) and Ovine Pulmonary Adenomatosis Lungworm related conditions

E

F

G

Caseous lymphadenitis

H

TB in goats

I

Liver fluke (Fascioliasis)

J

Echinococcosis/Hydatidosis

Mild form A

Mild form B


K

Orf disease Ecthyma)

L

Diarrhoea / Soiling slaughter animals

M

Vaginal prolapse/hernia

N

(Poly-) Arthritis

O

Bruising

P

Broken bones

Q

Leg and feet disorders WITH signs

R

Poor body condition

S

Sheep ovis)

T

Mastitis

scab

(Contagious

in

(Psoroptes


General questions a) Please state your area of expertise [underscore the correct option(s)]: Animal Health/ Animal Welfare/ Meat Inspection/Other If you answer was “other” please specify area of expertise: ___________________________________________________________ b) Please state number of years of experience: _____________________________

c) If there were any questions/ issues that you would like to raise concerning this questionnaire, please state those below ___________________________________________________________________ ___________________________________________________________________ ___________________________________________________________________ ___________________________________________________________________ ___________________________________________________________________ ___________________________________________________________________ ___________________________________________________________________ ___________________________________________________________________ ___________________________________________________________________ ___________________________________________________________________ ___________________________________________________________________ ___________________________________________________________________ ___________________________________________________________________

NAME: …………………………………………………………………………………… (Note: Name will remain confidential)

Final small ruminants (SR) questionnaire on the detection of disease and welfare concerns at abattoirs Dear Dr X, Thank you for your help with the project. This is the final questionnaire concerning the detection of disease and welfare concerns at the abattoir level. This project is concerned with the efficacy of different surveillance protocols at the abattoir. The objective of this questionnaire is to estimate probability of detection of an infected or affected animal at meat inspection. Your answers will be used to parameterise the model which will calculate the probability of detection for each selected disease and welfare condition at the abattoir. This report is concerned with twenty conditions in farmed small ruminants, listed in the methods section on the next page. Information regarding the meat inspection process is provided in the document ‘Small_Ruminant_Additional_Information’ which is attached to the same e-mail as the questionnaire. Please could you fill in the tables and return the forms back to [email protected], by the 20th February 2012, if possible. If you have any problems completing the questionnaire please do not hesitate to contact me. We appreciate your time and effort in completing the questionnaires and taking part in this project.

BACKGROUND AND INTRODUCTION The model is a scenario tree, where each node represents a stage in the meat production process, for example there is a node in the model which represents the ante-mortem inspection process. There are two models; the first model calculates the detection fraction for all twenty selected small ruminant

(SR)

conditions

for

the

classical

abattoir

meat

inspection

(see

Small_Ruminant_Additional_Information), an intermediate meat inspection and visual only inspection protocols. The second model calculates the detection fraction taking into account risk factors at both farm and animal (individual) levels for five diseases: foot and mouth disease (FMD), pneumonia/lower lung infections, sheep scab, leg and foot disorders (inc. foot rot) and liver fluke (Fasciola hepatica). For the second model we are calculating the impact of farm-level and individual SR level risk factors. The parameters required for the first model are: The proportion of all infected or affected animals that are typical or mild cases, or are asymptomatic for a disease or condition. The definitions for mild and typical cases are provided for each condition and were derived from the original questionnaire. The probability of detection at ante-mortem (am) inspection, given case type, for example the probability of detecting a mild case of mastitis during the ante-mortem inspection. The probability of detection at post-mortem (pm) inspection, given case type, for example the probability of detecting a typical case of tuberculosis during the post-mortem inspection.

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs The probability of detection of a condition using a visual inspection of the carcass and offal, and the incision of the lymph nodes currently incised (this table is in yellow due to being a recent addition to the questionnaire).

The probability of detection of a condition using a visual only meat inspection with no palpation or incisions. (this table is in yellow due to being a recent addition to the questionnaire). The second model uses the same parameters as the first model but these are divided into animal and farm (herd) level risk factor categories. The second model is more detailed than the first model and includes additional questions on the sensitivity of diagnostic tests.

METHODS For each disease there are typical, mild and asymptomatic disease states. For each small ruminant (SR) category and disease state you will be asked to give parameter values. For each parameter you will be asked to provide minimum (Min), most likely (ML) (modal average) and maximum (Max) probability values. These three values are needed to describe the probability distributions (betapert) used in the model. The parameters will be required for both mild and typical cases. The first part of the questionnaire will cover model one for blue tongue (1.1), bovine tuberculosis (caused by M. bovis) in goats (1.2), rift valley fever (1.3), Orf’s disease (1.4), mastitis (1.5), bruising (1.6), arthritis (1.7), Echincoccosis (1.8), lung worm, (1.9) diarrhea (1.10), caseous lymphadenitis (1.11), pulmonary adenomatosis (1.12), prolapse/hernia (1.13), broken limbs (1.14)and poor body condition (1.15). The second part of the model will cover material needed for models one and two on foot and mouth disease (FMD) (2.1), pneumonia/lower lung infections (2.2), sheep scab (2.3), leg and foot disorders (inc. foot rot) (2.4) and liver fluke (Fasciola hepatica) (2.5).

With the exception of bTB and goats (1.2), we would like you to provide parameter values for small ruminants in general. If there is a condition for which the species greatly vary please provide estimates for both by placing values for sheep in the tables and goats in the additional comments area.

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 1. SECTION ONE 1.1 BLUETONGUE VIRUS (BTV) Definitions A typical case of bluetongue is assumed to present itself at AM inspection with watery nasal discharge, swollen face, swelling/oedema in the submandibular region, ulcers in mouth, lesions in the coronary band (including inflammation of coronary band), lameness and formation of crusts around the nose and at PM inspection with haemorrhages at the base of the pulmonary artery, swelling/oedema in the head and neck areas and cyanotic tongue. A mild case of bluetongue is assumed to present itself at AM inspection with mild swelling of the face, ears, lips and tongue and nasal discharge and at PM inspection without any lesions. Q 1.1.1. Within a batch of animals infected with BTV presented at slaughter, what are the proportions of all BTV infected animals that are asymptomatic (subclinical cases) or show typical or mild signs of the disease? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max

Q1.1.2. What are the probabilities of detection at ante-mortem inspection for animals which present typical and mild signs of infection? Case type

Probability of detection at ante-mortem inspection Min ML (Mode) Max

Typical Mild Additional comments: Q1.1.3. What are the probabilities of detection at post-mortem inspection for animals which present typical and mild signs of infection? Case type

Probability of detection at post-mortem inspection Min ML (Mode) Max

Typical Mild Additional comments:

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs Q1.1.4. What are the probabilities of detection of BTV by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q1.1.5. What are the probabilities of detection of BTV using a visual only meat inspection for animals which present typical and mild signs of infection? Case type



1.2 BOVINE TUBERCULOSIS (BTB) (CAUSED BY M. BOVIS) IN GOATS Definitions A typical case of bTB in goats is assumed to present itself at AM inspection with poor body condition and moist cough and at PM inspection with abscesses or granulomas in the lymph nodes of the lungs (bronchial and mediastinal) and with abscesses in the lungs. A mild case of bTB in goats is assumed to present itself at AM inspection with cough and poor body condition and at PM inspection with mild lung lesions (abscesses/granulomas) and a poor carcase. Q 1.2.1. Within a batch of animals infected with M. bovis presented at slaughter, what are the proportions of all M. bovis infected animals that are asymptomatic (subclinical cases) or show typical or mild signs of the disease? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs Q1.2.2. What are the probabilities of detection at ante-mortem inspection for animals which present typical and mild signs of infection? Case type Probability of detection at ante-mortem inspection Min ML (Mode) Max Typical Mild Additional comments: Q1.2.3. What are the probabilities of detection at post-mortem inspection for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q1.2.4. What are the probabilities of detection of bTB by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q1.2.5. What are the probabilities of detection of bTB using a visual only meat inspection for animals which present typical and mild signs of infection? Case type



1.3 RIFT VALLEY FEVER (RVF) Definitions A typical case of RVF is assumed to present itself at AM inspection with depression and at PM inspection with necrotic foci in the liver and haemorrhages in the lungs. A mild case of RVF is assumed to present itself at AM inspection with depression and at PM inspection with haemorrhages in various organs.

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs Q 1.3.1. Within a batch of animals infected with RVF presented at slaughter, what are the proportions of all RVF infected animals that are asymptomatic (subclinical cases) or show typical or mild signs of the disease? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max





Typical Mild Additional comments: Q1.3.4. What are the probabilities of detection of RVF by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q1.3.5. What are the probabilities of detection of RVF using a visual only meat inspection for animals which present typical and mild signs of infection? Case type



Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 1.4. Orf’s disease Definitions A typical case of Orf’s disease is assumed to present itself at AM inspection with granulomatous type lesions and scabs around the mouth and at PM inspection without any lesions. A mild case of Orf’s disease is assumed to present itself at AM inspection with crusts and ulcers in the lips and nostrils and at PM inspection without any lesions. Q 1.4.1. Within a batch of animals infected with Orf’s disease presented at slaughter, what are the proportions of all Orf’s disease infected animals that are asymptomatic (subclinical cases) or show typical or mild signs of the disease? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max





Typical Mild Additional comments: Q1.4.4. What are the probabilities of detection of Orf’s disease by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type



Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs Q1.4.5. What are the probabilities of detection of Orf’s disease using a visual only meat inspection for animals which present typical and mild signs of infection? Case type



1.5 MASTITIS Definitions A typical case of mastitis is assumed to present itself at AM inspection with swollen udder, enlarged supramammary lymph nodes and with lumps in the mammary tissue and at PM inspection with fibrosis in the udder and enlarged supramammary lymph nodes. A mild case of mastitis is assumed to present itself at AM inspection without any signs and at PM inspection with enlarged udder. Q 1.5.1. Within a batch of animals infected with mastitis presented at slaughter, what are the proportions of all mastitis diseased animals that are asymptomatic (subclinical cases) or show typical or mild signs of the disease? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max






Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs Q1.5.4. What are the probabilities of detection of mastitis by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q1.5.5. What are the probabilities of detection of mastitis using a visual only meat inspection for animals which present typical and mild signs of infection? Case type



1.6 BRUISING Definitions A typical case of bruising is assumed to present itself at AM inspection with abnormal behaviour indicating pain and at PM inspection with recent/fresh bruises on the flanks and on the legs and broken ribs. A mild case of bruising is assumed to present itself at AM inspection without any signs and at PM inspection with mild, localised bruises, especially on back and flanks. Q 1.6.1. Within a batch of animals with bruising presented at slaughter, what are the proportions of all bruised animals that are asymptomatic (subclinical cases) or show typical or mild signs of the condition? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max




Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs Q1.6.3. What are the probabilities of detection at post-mortem inspection for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q1.6.4. What are the probabilities of detection of bruising by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q1.6.5. What are the probabilities of detection of bruising using a visual only meat inspection for animals which present typical and mild signs of infection? Case type



1.7 ARTHRITIS Definitions A typical case of (poly-) arthritis is assumed to present itself at AM inspection with lameness and swollen joints and at PM inspection with turbid synovial fluid, erosions on the articular cartilage and enlarged local lymph nodes. A mild case of (poly-) arthritis is assumed to present itself at AM inspection with mild lameness and at PM inspection with swollen joint(s) with increased synovial fluid.

Q 1.7.1. Within a batch of animals with arthritis presented at slaughter, what are the proportions of all arthritic animals that are asymptomatic (subclinical cases) or show typical or mild signs of the disease? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs





Typical Mild Additional comments: Q1.7.4. What are the probabilities of detection of arthritis by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q1.7.5. What are the probabilities of detection of arthritis using a visual only meat inspection for animals which present typical and mild signs of infection? Case type



Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 1.8. Echinococcosis Definitions A typical case of echinococcosis is assumed to present itself at AM inspection without any signs and at PM inspection with hydatid cysts in the liver and in the lungs. A mild case of echinococcosis is assumed to present itself at AM inspection without any signs and at PM inspection with a small number of small cysts in liver and lungs. Q 1.8.1. Within a batch of animals infected with echinococcosis presented at slaughter, what are the proportions of all echinococcosis infected animals that are asymptomatic (subclinical cases) or show typical or mild signs of the disease? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max





Typical Mild Additional comments: Q1.8.4. What are the probabilities of detection of Echinococcus by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type



Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs

Q1.8.5. What are the probabilities of detection of Echinococcus using a visual only meat inspection for animals which present typical and mild signs of infection? Case type



1.9 LUNG WORM Definitions A typical case of lungworm infection is assumed to present itself at AM inspection with cough and at PM inspection with greenish exudate in bronchi, patches of consolidation in lungs, fibrous/calcified nodules in the subpleural lung parenchyma and with (lungworm) parasites in the airways. A mild case of a lungworm infection is assumed to present itself at AM inspection with mild cough and at PM inspection with frothy airways with small numbers of worms and lesions of pneumonia in caudal lobes (vacuoles etc.). Q 1.9.1. Within a batch of animals infected with lung worm presented at slaughter, what are the proportions of all lung worm infected animals that are asymptomatic (subclinical cases) or show typical or mild signs of the disease? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max




Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs Q1.9.3. What are the probabilities of detection at post-mortem inspection for animals which present typical and mild signs of infection? Case type Probability of detection at post-mortem inspection Min ML (Mode) Max Typical Mild Additional comments: Q1.9.4. What are the probabilities of detection of lung worm by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q1.9.5. What are the probabilities of detection of lung worm using a visual only meat inspection for animals which present typical and mild signs of infection? Case type



1.10

DIARRHOEA

Definitions A typical case of diarrhoea/soiling is assumed to present itself at AM inspection with soiled hind parts and at PM inspection with abnormal intestinal contents (watery, bloody etc.). A mild case of diarrhoea/soiling is assumed to present itself at AM inspection with soiled perineum and at PM inspection with diarrhoeic contents in the intestines. Q 1.10.1. Within a batch of animals with diarrhoea presented at slaughter, what are the proportions of all diarrhoea cases that show typical or mild signs of the condition? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Additional comments:

Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs Q1.10.2. What are the probabilities of detection at ante-mortem inspection for animals which present typical and mild signs of infection? Case type Probability of detection at ante-mortem inspection Min ML (Mode) Max Typical Mild Additional comments: Q1.10.3. What are the probabilities of detection at post-mortem inspection for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q1.10.4. What are the probabilities of detection of lung worm by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q1.10.5. What are the probabilities of detection of lung worm using a visual only meat inspection for animals which present typical and mild signs of infection? Case type



1.11

CASEOUS LYMPHADENITIS

Definitions A typical case of caseous lymphadenitis is assumed to present itself at AM inspection without any signs and at PM inspection with laminated abscesses in the head lymph nodes, abscesses in the lung and with abscesses in the bronchial and mediastinal lymph nodes. A mild case of caseous lymphadenitis is assumed to present itself at AM inspection with enlarged superficial lymph nodes and at PM inspection with enlarged superficial lymph nodes and abscesses in the body (including the lymph nodes).

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs Q 1.11.1. Within a batch of animals with caseous lymphadenitis presented at slaughter, what are the proportions of all caseous lymphadenitis cases that are asymptomatic (subclinical cases) or show typical or mild signs of the disease? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max





Typical Mild Additional comments: Q1.11.4. What are the probabilities of detection of caseous lymphadenitis by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q1.11.5. What are the probabilities of detection of caseous lymphadenitis using a visual only meat inspection for animals which present typical and mild signs of infection? Case type



Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 1.12

PULMONARY ADENOMATOSIS (& MAEDI-VISNA (MV))

Definitions A typical case of MV/OPA is assumed to present itself at AM inspection with poor body condition and dyspnoea and at PM inspection with grossly enlarged and heavy lungs, coalescing grey areas in the lungs, frothy fluid in the cut surface of the lung lesions and in the airways and with enlarged, oedematous bronchial and mediastinal lymph nodes. A mild case of MV/OPA is assumed to present itself at AM inspection with slight respiratory distress, nasal discharge and lethargy and at PM inspection with minor increase in lung size and grey areas (lesions) in the lungs. Q 1.12.1. Within a batch of animals with pulmonary adenomatosis/MV presented at slaughter, what are the proportions of all pulmonary adenomatosis/MV cases that are asymptomatic (subclinical cases) or show typical or mild signs of the disease? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max






Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs Q1.12.4. What are the probabilities of detection of pulmonary adenomatosis by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type Probability of detection at post-mortem inspection Min ML (Mode) Max Typical Mild Additional comments: Q1.12.5. What are the probabilities of detection of pulmonary adenomatosis using a visual only meat inspection for animals which present typical and mild signs of infection? Case type



1.13

PROLAPSE/HERNIA

Definitions A typical case of partial vaginal collapse is assumed to present itself at AM inspection with the detection of a prolapsed mass in the genitals’ area and at PM inspection with a prolapsed vagina. A mild case of partial vaginal prolapse is assumed to present itself at AM inspection with straining and a slight protrusion and swelling of the vagina and at PM inspection without any lesions. Q 1.13.1. Within a batch of animals with prolapse/hernia presented at slaughter, what are the proportions of all prolapse/hernia cases that are asymptomatic (subclinical cases) or show typical or mild signs of the condition? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs Q1.13.2. What are the probabilities of detection at ante-mortem inspection for animals which present typical and mild signs of infection? Case type




Typical Mild Additional comments: Q1.13.4. What are the probabilities of detection of a prolapse/hernia by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q1.13.5. What are the probabilities of detection of a prolapse/hernia using a visual only meat inspection for animals which present typical and mild signs of infection? Case type



1.14

BROKEN LIMBS

Definitions A typical case of broken bones is assumed to present itself at AM inspection with fracture in one leg, severe lameness, abnormal movements of the damaged leg and with pain on the palpation and manipulation of the leg and at PM inspection with a fracture surrounded by fresh haemorrhage.

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs Q 1.14.1. Within a batch of animals with broken limbs presented at slaughter, what are the proportions of all cases with broken limbs that show typical signs of the condition? Please note that all three ML (mode) values have to add up to 1. Case type Typical Additional comments:

Min

ML (Mode)

Max



Typical Additional comments: Q1.14.3. What are the probabilities of detection at post-mortem inspection for animals which present typical and mild signs of infection? Case type


Typical Additional comments: Q1.14.4. What are the probabilities of detection of broken limbs by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type


Typical Additional comments: Q1.14.5. What are the probabilities of detection of broken limbs using a visual only meat inspection for animals which present typical and mild signs of infection? Case type


Typical Additional comments:

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 1.15

POOR BODY CONDITION

Definitions A typical case of poor body condition is assumed to present itself at AM inspection with the detection of prominent bones on the animal and at PM inspection with the loss of the subcutaneous fat, the loss or the reduced amount of intracavities fat and with the oedematous and jelly-like appearance of the carcase fat. A mild case of poor body condition is assumed to present itself at AM inspection with prominent bones and at PM inspection with little fat cover and prominent bones. Q 1.15.1. Within a batch of animals with a poor body condition presented at slaughter, what are the proportions of all cases that are asymptomatic (subclinical cases) or show typical or mild signs of the disease? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max






Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs Q1.15.4. What are the probabilities of detection of poor body condition by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type Probability of detection at post-mortem inspection Min ML (Mode) Max Typical Mild Additional comments: Q1.15.5. What are the probabilities of detection of poor body condition using a visual only meat inspection for animals which present typical and mild signs of infection? Case type



2. SECTION TWO Objective: to estimate detection fractions/probabilities or component sensitivities for the surveillance components for the disease or condition of interest. This is looking at the abattoir surveillance processes in greater detail and taking into account more information about the animals and conditions. The exact specification of the data needed is dependent on the farm- and animal-level risk factors defined for a disease or condition in small ruminants. An example of a FLRF (farm-level risk factor) to consider is whether the small ruminants (SR) have come from an open farm system. An example of an ALRF (animal-level risk factor) is the age of the animal, for example, animals under one year of age may be at higher risk of infection than juveniles and adults. Useful Risk factor terminology Open farm system - a farm which imports small ruminants Closed farm system - breeds and rears its own small ruminants, it can buy in rams but not ewes. Extensive farm system - animals graze outdoors during the year, with the exception the winter months when they may be temporarily housed. Lambing tends to occur outdoors in these systems. Housed farm system - animals are kept indoors, in pens or yards and require feed. Lambing tends to occur indoors in this system.

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.1.

FOOT AND MOUTH DISEASE (FMD)

Definitions A typical case of FMD is assumed to present itself at AM inspection with lameness, stomatitis with vesicles, erosions and ulcers, vesicles and erosions in the interdigital space and vesicles and erosions in the coronary band and at PM inspection with erosions and ulcers in the mouth. A mild case of FMD is assumed to present itself at AM inspection with mild lameness and lesions in the feet (interdigital dermatitis, vesicles etc.) and at PM inspection without any lesions.

Q2.1.1. Within a batch of animals infected with FMD presented at slaughter, what are the proportions of all FMD infected animals that are asymptomatic (subclinical cases) or show typical or mild signs of the disease? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max






Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs Q2.1.4. What are the probabilities of detection of FMD by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q2.1.5. What are the probabilities of detection of FMD using a visual only meat inspection for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Probabilities of detection The probability of detection is going to take into account whether the animal is above or below one year of age, the animal-level risk factor (ALRF) and whether the animals come from an open or closed farming system, the farm- (herd) level risk factor (RLRF) for FMD. 2.1.6. What is the probability that animals over or under one year of age with the disease, will present typical or mild signs of FMD? ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Animals 1 yr Additional comments: 2.1.7. What is the probability of detection of FMD at ante -mortem inspection for open and closed farms and animals of under and over one year of age? FLRF Open farm system

ALRF

Animals 1 yr Closed Animals farm 1 yr Additional comments:

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.1.8.1. What is the probability of detection of FMD at post -mortem inspection for open and closed farms and animals of under and over one year of age? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open Animals farm 1 yr Closed Animals farm 1 yr Additional comments: 2.1.8.2. What is the probability of detection of FMD by visually inspecting the carcass and offal, and by incising lymph nodes, for open and closed farms and animals of under and over one year of age? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open Animals farm 1 yr Closed Animals farm 1 yr Additional comments: 2.1.8.3. What is the probability of detection of FMD by visual only inspection, for open and closed farms and animals of under and over one year of age? FLRF

ALRF

Open Animals farm 1 yr Closed Animals farm 1 yr Additional comments:

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.1.9.1. What is the probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for FMD, given the farm system and age of the animal? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open farm system

Animals 1 yr Closed Animals farm 1 yr Additional comments: 2.1.9.2. What is the probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for FMD after visual inspection of the carcass and offal and incision of Lymph nodes, given the farm system and age of the animal? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open Animals farm 1 yr Closed Animals farm 1 yr Additional comments: 2.1.9.3. What is the probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for FMD after a visual only inspection, given the farm system and age of the animal? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

Open Animals farm 1 yr Closed Animals farm 1 yr Additional comments: 2.1.10. Which diagnostic tests could be undertaken in the abattoir for FMD?

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.1.11. For the methods you have indicated in the previous question, What is the sensitivity of the testing method, given the animal’s age and whether the signs were typical or mild? ALRF

Typical Min

ML (Mode)

Mild Min

Max

ML (Mode)

Max

Animals 1 yr Additional comments: The probabilities of detection for the clinical surveillance component of the model 2.1.12. What is the probability that veterinarian is called by the farmer for a clinical case of FMD? Please take account the case type, the farm system and age. FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open Animals farm 1 yr Closed Animals farm 1 yr Additional comments: 2.1.13. What is the probability that a veterinarian will take an additional step to diagnose FMD, for example take samples for laboratory diagnosis of the disease? Please take account the case type, the farm system and age. FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open farm system

Animals 1 yr Closed Animals farm 1 yr Additional comments: 2.1.14. Which additional examination methods (test, autopsy) would be undertaken by the veterinarian for FMD?

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.1.15. What is the sensitivity of the additional examination method (test, autopsy) for FMD given the animal’s age and case type?* ALRF Typical Mild Min ML Max Min ML Max (Mode) (Mode) Animals 1 yr *Note that this sensitivity can be different from what is defined for the test under the Meat inspection component above, e.g. if the type of samples taken are likely to be different. Additional comments:

2.2 PNEUMONIA/LOWER RESPIRATORY INFECTION Definitions A typical case of lower respiratory tract infection is assumed to present itself at AM inspection with mucopurulent nasal discharge and at PM inspection with lesions of pneumonia (red consolidation, hepatisation etc.) in the apical, cardiac and cranial part of the diaphragmatic lobes and with chronic pleurisy. A mild case of a lower respiratory tract infection is assumed to present itself at AM inspection with respiratory signs (coughing, hyperpnoea etc.) and dullness and at PM inspection with lesions consistent with pneumonia (consolidation etc.). 2.2.1. Within a batch of animals with pneumonia/lower respiratory tract infections presented at slaughter, what are the proportions of all infected animals that are asymptomatic (subclinical cases) or show typical or mild signs of the disease? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max






Typical Mild Additional comments: Q2.2.4. What are the probabilities of detection of pneumonia/lower respiratory tract infection by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q2.2.5. What are the probabilities of detection of pneumonia/lower respiratory tract infection using a visual only meat inspection for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Probabilities of detection The probability of detection is going to take into account whether the animal is below or above six months in age (the animal-level risk factor (ALRF)) and whether the animal has come from an extensive or housed farm system (the farm- (herd) level risk factor (RLRF)) for pneumonia/power respiratory tract infection. 2.2.6. What is the probability that animals over or under one year of age with the disease, will present typical or mild signs of pneumonia/lower respiratory tract infection? ALRF

Typical Min

Animals 6 months old Additional comments:

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.2.7. What is the probability of detection of pneumonia/lower respiratory tract infection at ante mortem inspection for open and closed farms and animals of under and over one year of age? FLRF ALRF Typical Mild Min ML Max Min ML Max (Mode) (Mode) Extensive Animals 6 months old Housed Animals 6 months old Additional comments: 2.2.8.1. What is the probability of detection of pneumonia/lower respiratory tract infection at post mortem inspection for open and closed farms and animals of under and over one year of age? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Extensive Animals 6 months old Housed Animals 6 months old Additional comments: 2.2.8.2. What is the probability of detection of pneumonia/lower respiratory tract infection by visually inspecting the carcass and offal, and by incising lymph nodes, for open and closed farms and animals of under and over one year of age? FLRF

ALRF

Extensive Animals 6 months old Housed Animals 6 months old Additional comments:

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.2.8.3. What is the probability of detection of pneumonia/lower respiratory tract infection by visual only inspection for open and closed farms and animals of under and over one year of age? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Extensive Animals 6 months old Housed Animals 6 months old Additional comments: 2.2.9.1. What is the probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for pneumonia/lower respiratory tract infection, given the farm system and age of the animal? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Extensive Animals 6 months old Housed Animals 6 months old Additional comments: 2.2.9.2. What is the probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for pneumonia/lower respiratory tract infection after visual inspection of the carcass and offal and incision of Lymph nodes, given the farm system and age of the animal? FLRF

ALRF


Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.2.9.3. What is the probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for pneumonia/lower respiratory tract infection after a visual only inspection, given the farm system and age of the animal? FLRF

ALRF

Typical Min

ML (Mode)

Mild Min

Max

ML (Mode)

Max

Extensive Animals 6 months old Housed Animals 6 months old Additional comments: 2.2.10. Which diagnostic tests could be undertaken in the abattoir for pneumonia/power respiratory tract infections?

2.2.11. What is the sensitivity of the testing methods for pneumonia/lower respiratory tract infections, given the animal’s age and whether the signs were typical or mild? ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Animals 6 months old Additional comments: The probabilities of detection for the clinical surveillance component of the model 2.2.12. What is the probability that veterinarian is called by the farmer for a clinical case of pneumonia/power respiratory tract infection? Please take account the case type, the farm system and age. FLRF

ALRF


Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.2.13. What is the probability that a veterinarian will take an additional step to diagnose pneumonia/lower respiratory tract infection, for example take samples for laboratory diagnosis of the disease? Please take account the case type, the farm system and age. FLRF ALRF Typical Mild Min ML Max Min ML Max (Mode) (Mode) Extensive Animals 6 months old Housed Animals 6 months old Additional comments: 2.2.14. Which additional examination methods (test, autopsy) would be undertaken by the veterinarian for pneumonia/lower respiratory tract infections? 2.2.15. What is the sensitivity of the additional examination method (test, autopsy) for pneumonia/lower respiratory tract infection given the animal’s age and case type?* ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Animals 6 months old *Note that this sensitivity can be different from what is defined for the test under the Meat inspection component above, e.g. if the type of samples taken are likely to be different.

Additional comments:

2.3 SHEEP SCAB

Definitions A typical case of sheep scab is assumed to present itself at AM inspection with the loss of wool (including bare patches and alopecia), intense pruritus, the presence of papules, pustules etc. on the body (including the head) and with matted/ragged fleece/wool and at PM inspection without any lesions. A mild case of sheep scab is assumed to present itself at AM inspection with pruritus, skin lesions (papules, crusts around mouth, ears, bruising etc.) and ragged/deranged fleece and at PM inspection without any lesions.

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.3.1 Within a batch of animals with sheep scab presented at slaughter, what are the proportions of all infected animals that are asymptomatic (subclinical cases) or show typical or mild signs of the disease? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max






Q2.3.4. What are the probabilities of detection of sheep scab by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q2.3.5. What are the probabilities of detection of sheep scab using a visual only meat inspection for animals which present typical and mild signs of infection? Case type



Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs Probabilities of detection The probability of detection is going to take into account the body condition of an individual (animallevel risk factor (ALRF)) and whether the farm operates on a closed or open system (farm- (herd) level risk factor (RLRF)) for sheep scab. 2.3.6. What is the probability that animals with a poor or good body condition will present typical or mild signs of sheep scab? ALRF

Typical Min

ML (Mode)

Mild Min

Max

ML (Mode)

Max

Poor body condition Good body condition Additional comments: 2.3.7. What is the probability of detection for typical or mild cases of sheep scab at ante -mortem inspection for animals with a poor or good body condition from an open or closed farm? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open farm system

Poor body condition Good body condition Closed Poor body farm condition system Good body condition Additional comments: 2.3.8.1. What is the probability of detection for typical or mild cases of sheep scab at post -mortem inspection for animals with a poor or good body condition from an open or closed farm? FLRF

ALRF

Open Poor body farm condition system Good body condition Closed Poor body farm condition system Good body condition Additional comments:

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.3.8.2. What is the probability of detection of sheep scab by visually inspecting the carcass and offal, and by incising lymph nodes, for open and closed farms and animals of under and over one year of age? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open farm system

Poor body condition Good body condition Closed Poor body farm condition system Good body condition Additional comments: 2.3.8.3. What is the probability of detection of sheep scab by visual only inspection for open and closed farms and animals of under and over one year of age? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open farm system

Poor body condition Good body condition Closed Poor body farm condition system Good body condition Additional comments: 2.3.9.1 What is the probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for sheep scab, given the farm system and body condition of the animal? FLRF Open farm system

ALRF

Poor body condition Good body condition Closed Poor body farm condition system Good body condition Additional comments:

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.3.9.2. What is the probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for sheep scab after visual inspection of the carcass and offal and incision of Lymph nodes, given the farm system and age of the animal? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open Poor body farm condition system Good body condition Closed Poor body farm condition system Good body condition Additional comments: 2.3.9.3. What is the probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for sheep scabafter a visual only inspection, given the farm system and age of the animal? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open Poor body farm condition system Good body condition Closed Poor body farm condition system Good body condition Additional comments: 2.3.10. Which diagnostic tests could be undertaken in the abattoir for sheep scab? 2.3.11. What is the sensitivity of the testing method for sheep scab, given the animal’s age and whether the signs were typical or mild? ALRF Poor body condition Good body condition Additional comments:

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs The probabilities of detection for the clinical surveillance component of the model 2.3.12. What is the probability that veterinarian is called by the farmer for a clinical case of sheep scab? Please take account the case type, farm system and body condition. FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open Poor body farm condition system Good body condition Closed Poor body farm condition system Good body condition Additional comments: 2.3.13. What is the probability that a veterinarian will take an additional step to diagnose sheep scab, for example take samples for laboratory diagnosis of the disease? Please take account the case type, farm system and body condition FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open farm system

Poor body condition Good body condition Closed Poor body farm condition system Good body condition Additional comments: 2.3.14. Which additional examination methods (test, autopsy) would be undertaken by the veterinarian for sheep scab? 2.3.15. What is the sensitivity of the additional examination method (test, autopsy) for sheep scab given the animal’s age and case type?* ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Poor body condition Good body condition *Note that this sensitivity can be different from what is defined for the test under the Meat inspection component above, e.g. if the type of samples taken are likely to be different.


Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.4 LEG AND FOOT DISORDERS (INC. FOOT ROT) Definitions A typical case of leg and foot disorders is assumed to present itself at AM inspection with slight lameness, disability in more than one leg, offensive smell and interdigital dermatitis and at PM inspection with atrophy of the affected muscles. A mild case of leg and foot disorders is assumed to present itself at AM inspection with mild lameness and mild interdigital dermatitis or necrosis with foul smell and at PM inspection without any lesions. 2.4.1. Within a batch of animals with leg and foot disorders presented at slaughter, what are the proportions of all affected animals that are asymptomatic (subclinical cases) or show typical or mild signs of the infliction? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max






Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs Q2.4.4. What are the probabilities of detection of leg and foot disorders by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q2.4.5. What are the probabilities of detection of leg and foot disorders by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Probabilities of detection The probability of detection is going to take into account whether or not the animal is a high risk breed (Merino) as an animal-level risk factor (ALRF) and whether the animal is from an open or closed farm as a farm- (herd) level risk factor (RLRF) for leg and foot disorders. 2.4.6. What is the probability that animals over or under one year of age with the disease, will present typical or mild signs of leg and foot disorders? ALRF

Typical Min ML (Mode)

Mild Min

Max

ML (Mode)

Max

High risk breed (Merino) Low risk breed Additional comments: 2.4.7. What is the probability of detection of leg and foot disorders at ante -mortem inspection for animals under and over one year of age from open and closed farms? FLRF

ALRF

Open High risk breed farm (Merino) system Low risk breed Closed High risk breed farm (Merino) system Low risk breed Additional comments:

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.4.8.1. What is the probability of detection of leg and foot disorders at post -mortem inspection for animals under and over one year of age from open and closed farms? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open High risk breed farm (Merino) system Low risk breed Closed High risk breed farm (Merino) system Low risk breed Additional comments: 2.4.8.2. What is the probability of detection of leg and foot disorders by visually inspecting the carcass and offal, and by incising lymph nodes, for open and closed farms and animals of under and over one year of age? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open High risk breed farm (Merino) system Low risk breed Closed High risk breed farm (Merino) system Low risk breed Additional comments: 2.4.8.3. What is the probability of detection of leg and foot disorders by using a visual only inspection for open and closed farms and animals of under and over one year of age? FLRF

ALRF

Open High risk breed farm (Merino) system Low risk breed Closed High risk breed farm (Merino) system Low risk breed Additional comments:

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.4.9. 1. What is the probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for leg and foot disorders, given the farm system and age of the animal? FLRF ALRF Typical Mild Min ML Max Min ML Max (Mode) (Mode) Open High risk breed farm (Merino) system Low risk breed Closed High risk breed farm (Merino) system Low risk breed Additional comments: 2.4.9.2. What is the probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for leg and foot disorders, after visual inspection of the carcass and offal and incision of Lymph nodes, given the farm system and age of the animal? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open High risk breed farm (Merino) system Low risk breed Closed High risk breed farm (Merino) system Low risk breed Additional comments: 2.5.9.3. What is the probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for leg and foot disorders after a visual only inspection, given the farm system and age of the animal? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Open High risk breed farm (Merino) system Low risk breed Closed High risk breed farm (Merino) system Low risk breed Additional comments: 2.4.10. Which diagnostic tests could be undertaken in the abattoir for leg and foot disorders?

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.4.11. What is the sensitivity of the testing method, given the animal’s age and whether the signs were typical or mild? ALRF Typical Mild Min ML Max Min ML Max (Mode) (Mode) High risk breed (Merino) Low risk breed Additional comments: The probabilities of detection for the clinical surveillance component of the model 2.4.12. What is the probability that veterinarian is called by the farmer for a clinical case of leg and foot disorders? Please take account the case type, farm system and animal age. FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open High risk breed farm (Merino) system Low risk breed Closed High risk breed farm (Merino) system Low risk breed Additional comments: 2.4.13. What is the probability that a veterinarian will take an additional step to diagnose leg and foot disorders, for example take samples for laboratory diagnosis of the disease? Please take account the case type, farm system and animal age. FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open farm system

High risk breed (Merino) Low risk breed Closed High farm risk system breed (Merino) Low risk breed Additional comments: 2.4.14. Which additional examination methods (test, autopsy) would be undertaken by the veterinarian for leg and foot disorders?

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.4.15. What is the sensitivity of the additional examination method (test, autopsy) for leg and foot disorders given the animals age and case type?* ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Animals 1 yr *Note that this sensitivity can be different from what is defined for the test under the meat inspection component above, e.g. if the type of samples taken are likely to be different.


2.5 LIVER FLUKE (FASCIOLA HEPATICA) Definitions A typical case of liver fluke is assumed to present itself at AM inspection with poor body condition and at PM inspection with cholangitis/thickened bile duct walls and with the presence of mature flukes in the bile ducts. A mild case of liver fluke is assumed to present itself at AM inspection without any signs and at PM inspection with adult flukes in liver ducts and mild liver lesions. 2.5.1. Within a batch of animals infected with liver fluke presented at slaughter, what are the proportions of all infected animals that are asymptomatic (subclinical cases) or show typical or mild signs of the disease? Please note that all three ML (mode) values have to add up to 1. Case type Typical Mild Asymptomatic Additional comments:

Min

ML (Mode)

Max






Typical Mild Additional comments: Q2.5.4. What are the probabilities of detection of liver fluke by visually inspecting the carcass and offal, and by incising the lymph nodes for animals which present typical and mild signs of infection? Case type


Typical Mild Additional comments: Q2.5.5. What are the probabilities of detection of liver fluke disorders using a visual only meat inspection for animals which present typical and mild signs of infection? Case type



Probabilities of detection The probability of detection is going to take into account whether an animal is above or below one year of age, an animal-level risk factor (ALRF) and whether a farm- (herd) level risk factor (RLRF) for liver fluke infection. 2.5.6. What is the probability that animals over or under one year of age with the disease, will present typical or mild signs of liver fluke infection? ALRF

Typical Min

Animals 1 yr Additional comments:

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.5.7. What is the probability of detection of liver fluke infection at ante -mortem inspection for open and closed farms and animals of under and over one year of age? FLRF ALRF Typical Mild Min ML Max Min ML Max (Mode) (Mode) Open Animals farm 1 yr Closed Animals farm 1 yr Additional comments:

2.5.8. What is the probability of detection of liver fluke infection at post -mortem inspection for open and closed farms and animals of under and over one year of age? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open Animals farm 1 yr Closed Animals farm 1 yr Additional comments: 2.5.8.2. What is the probability of detection of liver fluke by visually inspecting the carcass and offal, and by incising lymph nodes, for open and closed farms and animals of under and over one year of age? FLRF

ALRF


Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.5.8.3. What is the probability of detection of liver fluke by using a visual only inspection for open and closed farms and animals of under and over one year of age? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open Animals farm 1 yr Closed Animals farm 1 yr Additional comments: 2.5.9.1. What is the probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for liver fluke infection, given the farm system and age of the animal? FLRF

ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Open farm system

Animals 1 yr Closed Animals farm 1 yr Additional comments: 2.5.9.2. What is the probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for liver fluke after visual inspection of the carcass and offal and incision of Lymph nodes, given the farm system and age of the animal? FLRF

ALRF


Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.5.9.3. What is the probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for liver fluke after a visual only inspection, given the farm system and age of the animal? FLRF

ALRF

Typical Min

ML (Mode)

Mild Min

Max

ML (Mode)

Max

Open Animals farm 1 yr Closed Animals farm 1 yr Additional comments: 2.5.10. Which diagnostic tests could be undertaken in the abattoir for liver fluke infections? 2.5.11. What is the sensitivity of the testing method, given the animal’s age and whether the signs were typical or mild? ALRF

Typical Min

ML (Mode)

Mild Min

Max

ML (Mode)

Max

Animals 1 yr Additional comments:

The probabilities of detection for the clinical surveillance component of the model 2.5.12. What is the probability that veterinarian is called by the farmer for a clinical case of liver fluke infection? Please take account the case type, farm system and animal age. FLRF

ALRF


Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 2.5.13. What is the probability that a veterinarian will take an additional step to diagnose liver fluke infection, for example take samples for laboratory diagnosis of the disease? Please take account the case type, farm system and animal age. FLRF

ALRF

Typical Min

ML (Mode)

Mild Min

Max

ML (Mode)

Max

Open farm system

Animals 1 yr Closed Animals farm 1 yr Additional comments: 2.5.14. Which additional examination methods (test, autopsy) would be undertaken by the veterinarian for liver fluke? 2.5.15. What is the sensitivity of the additional examination method (test, autopsy) for liver fluke infection given the animal’s age and case type?* ALRF

Typical Min

ML (Mode)

Max

Mild Min

ML (Mode)

Max

Animals 1 yr *Note that this sensitivity can be different from what is defined for the test under the Meat inspection component above, e.g. if the type of samples taken are likely to be different. Additional comments:

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs 3. SECTION THREE We are now interested in the percentage of animals for each animal- and farm-level risk factor category that are subjected to surveillance only at meat inspection and or are subjected to surveillance pre-abattoir inspection, for example testing regimes for particular disease in the manner of bTB testing of cattle herds. What are the percentages of the animals covered by meat inspection (surveillance component A) and/or clinical surveillance (surveillance component B) within one year, for each combination of risk factors below? Each column should add up to 100%. Presence in Open farm system surveillance Animals 1 yr component Meat inspection Clinical surveillance Meat inspection and Clinical surveillance Neither Additional comments:

Closed farm system Animals 1 yr

Presence in Open farm system surveillance Poor body Good body component condition condition Meat inspection Clinical surveillance Meat inspection and B Neither Additional comments:

Closed farm system Poor body Good body condition condition

Presence in Extensive farm system surveillance Animals 6 component months months Meat inspection Clinical surveillance Meat inspection and Clinical surveillance Neither Additional comments:

Housed farm system Animals 6 months months

Final small ruminants (SR)questionnaire on the detection of disease and welfare concerns at abattoirs Presence in Open farm system surveillance High risk breed low risk breed component (Merino) Meat inspection Clinical surveillance Meat inspection and Clinical surveillance Neither Additional comments:

Thank you for completing the final questionnaire.

Closed farm system High risk breed low risk breed (Merino)

Final sheep questionnaire on the detection of disease and welfare concerns at abattoirs GLOSSARY < - less than > - greater than ALRF – Animal level risk factor AM – Ante mortem bTB – bovine tuberculosis BTV – bluetongue virus FCI – Food chain information FLRF – Farm (herd) level risk factor FMD-Foot and mouth disease M. bovis – Mycobacterium bovis Max- maximum Min-minimum ML – Most likely PM – Post mortem Reg. – Regulation RVF- rift valley virus Post-Mortem inspection requirements for ruminants v-visual, p-palpate, i-incise and * when necessary Inspected region Head Tongue Mouth Fauces Throat Lungs Trachea Oesophagus Pericardium Heart Diaphragm Liver GIT§ and Mesentery Spleen Kidneys Pleura and Peritoneum Genital organs Udder Umbilical region Joints (young) Lymph Retropharyngeal and nodes parotid Bronchial and mediastinal Hepatic and pancreatic GIT and mesenteric Renal § Gastro

Supramammary intestinal tract (GIT)

Mode of inspection v v v* v v v* v v v v,i* v v,p,i v v,p* v,i* v v* v v,p,i* v,p,i* v,p,i* v v,p v i* v

Final sheep questionnaire on the detection of disease and welfare concerns at abattoirs EC 854/2004 regulation highlights for ante- and post- mortem inspections of small ruminants

Final sheep questionnaire on the detection of disease and welfare concerns at abattoirs






B. Parameter data from the literature used to parameterise the stage 2 and stage 3 models B1: Data for Stage 2 – Case type proportions B2: Data for Stage 3 - Tables B1 (prevalences, risk factors) and B2 (population proportions) B3: Data for Stage 3 – Detection probabilities B4: Data for Stage 3 - Coverage


40

Stage 2_data Exotic diseases Bluetongue

FMD Proportion of animals in each case type Proportion animals asymptomatic Proportion animals mild Proportion animals typical Ante-mortem inspection:mild Post mortem inspection: current inspection:mild Post mortem inspection: Intermediate inspection:mild Post mortem inspection: visual only inspection: mild Ante-mortem inspection:typical Post mortem inspection: current inspection: typical Post mortem inspection: Intermediate inspection: typical Post mortem inspection: visual only inspection: typical

Proportion of animals in each case type Proportion animals asymptomatic Proportion animals mild Proportion animals typical Ante-mortem inspection:mild Post mortem inspection: current inspection:mild Post mortem inspection: Intermediate inspection:mild Post mortem inspection: visual only inspection: mild Ante-mortem inspection:typical Post mortem inspection: current inspection: typical Post mortem inspection: Intermediate inspection: typical Post mortem inspection: visual only inspection: typical

min 0,800 0,005 0,001 0,005 0,000 0,000 0,000 0,050 0,010 0,010 0,000

mode 0,920 0,065 0,015 0,075 0,000 0,000 0,000 0,600 0,150 0,150 0,000

max 0,990 0,100 0,060 0,175 0,000 0,000 0,000 0,733 0,350 0,350 0,000

min 0,625 0,005 0,001 0,010 0,140 0,073 0,067 0,383 0,383 0,350 0,183

mode 0,830 0,120 0,05 0,317 0,217 0,150 0,133 0,567 0,517 0,500 0,350

max 0,990 0,250 0,48 0,700 0,333 0,267 0,200 1,000 0,733 0,733 0,533

Rift Valley Fever min 0,025 0,150 0,200 0,150 0,250 0,250 0,250 0,350 0,500 0,500 0,500

mode 0,150 0,400 0,450 0,350 0,500 0,500 0,500 0,550 0,750 0,750 0,750

max 0,300 0,750 0,800 0,600 0,700 0,700 0,700 0,850 1,000 1,000 1,000

Endemic diseases Lower respiratory Maedi-Visna Lungworm related tract infection (e.g. (pulmonary form) conditions or min and Ovinemax min minPasteurellosis) mode max mode mode max 0,300 0,100 0,050 0,150 0,750 0,750 0,750 0,300 0,800 0,800 0,800

0,500 0,300 0,200 0,350 0,900 0,900 0,900 0,600 0,950 0,950 0,950

0,850 0,700 0,400 0,550 1,000 1,000 1,000 0,800 1,000 1,000 1,000

0,350 0,050 0,050 0,100 0,300 0,300 0,300 0,600 0,875 0,400 0,400

0,575 0,200 0,225 0,300 0,550 0,550 0,550 0,750 1,000 0,650 0,650

0,850 0,400 0,400 0,600 0,750 0,750 0,750 0,950 1,000 0,750 0,750

0,500 0,157 0,034 0,134 0,500 0,500 0,500 0,137 0,733 0,700 0,700

0,633 0,267 0,100 0,237 0,600 0,600 0,600 0,283 0,833 0,800 0,800

0,800 0,533 0,233 0,340 0,750 0,750 0,750 0,390 0,917 0,900 0,900

Stage 2_data Endemic diseases TB in goats

Caseous Proportion of animals in each case type Proportion animals asymptomatic Proportion animals mild Proportion animals typical Ante-mortem inspection:mild Post mortem inspection: current inspection:mild Post mortem inspection: Intermediate inspection:mild Post mortem inspection: visual only inspection: mild Ante-mortem inspection:typical Post mortem inspection: current inspection: typical Post mortem inspection: Intermediate inspection: typical Post mortem inspection: visual only inspection: typical


min 0,433 0,003 0,000 0,000 0,500 0,500 0,450 0,070 0,75 0,750 0,700

mode 0,817 0,133 0,050 0,067 0,750 0,750 0,650 0,283 0,85 0,850 0,750

max 1,000 0,400 0,200 0,201 0,950 0,950 0,850 0,467 0,95 0,950 0,850

min 0,200 0,200 0,100 0,050 0,550 0,550 0,300 0,250 0,750 0,750 0,500

mode 0,350 0,450 0,200 0,100 0,750 0,750 0,500 0,450 0,850 0,850 0,650

max 0,550 0,650 0,400 0,212 0,950 0,950 0,700 0,750 0,950 0,950 0,750

Endemic diseases Orf disease Echinococcosis/ (Contagious Hydatidosis min mode max min Ecthyma) mode max 0,677 0,070 0,034 0,000 0,700 0,700 0,600 0,000 0,850 0,850 0,600

0,713 0,183 0,103 0,000 0,850 0,850 0,800 0,000 0,950 0,950 0,800

0,766 0,333 0,240 0,000 0,950 0,950 0,900 0,000 1,000 1,000 1,000

0,373 0,170 0,100 0,317 0,183 0,000 0,000 0,533 0,350 0,000 0,000

0,613 0,250 0,137 0,533 0,317 0,000 0,000 0,767 0,467 0,000 0,000

0,830 0,433 0,307 0,767 0,417 0,000 0,000 0,917 0,500 0,000 0,000

Liver fluke min 0,300 0,140 0,037 0,000 0,900 0,900 0,603 0,034 0,950 0,950 0,7

mode 0,493 0,367 0,140 0,000 0,950 0,950 0,64 0,137 1,000 1,000 0,8333

max 0,717 0,533 0,267 0,000 1,000 1,000 0,6833 0,273 1,000 1,000 0,9

Welfare conditions Diarrhoea/Soiling in slaughter sheep min n/a 0,300 0,203 0,370 0,100 0,050 0,050 0,700 0,267 0,100 0,100

mode n/a 0,550 0,450 0,500 0,267 0,250 0,250 0,833 0,467 0,450 0,450

max n/a 0,733 0,617 0,633 0,367 0,350 0,350 0,933 0,700 0,700 0,700

Stage 2_data Partial vaginal Proportion of animals in each case type Proportion animals asymptomatic Proportion animals mild Proportion animals typical Ante-mortem inspection:mild Post mortem inspection: current inspection:mild Post mortem inspection: Intermediate inspection:mild Post mortem inspection: visual only inspection: mild Ante-mortem inspection:typical Post mortem inspection: current inspection: typical Post mortem inspection: Intermediate inspection: typical Post mortem inspection: visual only inspection: typical


min 0,000 0,267 0,033 0,267 0,000 0,000 0,000 0,633 0,500 0,500 0,500

mode 0,367 0,500 0,133 0,433 0,000 0,000 0,000 0,833 0,750 0,750 0,750

max 0,433 0,600 0,333 0,600 0,000 0,000 0,000 0,983 0,900 0,900 0,900

Welfare conditions (Poly-) Arthritis Bruising min 0,050 0,250 0,075 0,137 0,200 0,200 0,150 0,467 0,500 0,500 0,400

Leg and feet disorders WITH signs,mode inc. footrot min max min 0,393 0,167 0,033 0,170 0,150 0,150 0,150 0,400 0,400 0,400 0,400

0,630 0,270 0,100 0,367 0,200 0,200 0,200 0,633 0,450 0,450 0,450

0,800 0,373 0,202 0,567 0,250 0,250 0,250 0,833 0,600 0,600 0,600

mode 0,150 0,600 0,250 0,300 0,400 0,400 0,300 0,700 0,750 0,750 0,550

max 0,400 0,900 0,500 0,467 0,650 0,650 0,450 0,867 1,000 1,000 0,750

min 0,360 0,167 0,000 0,000 0,850 0,850 0,850 0,133 0,950 0,950 0,950

mode 0,663 0,270 0,067 0,017 0,950 0,950 0,950 0,300 1,000 1,000 1,000

Broken bones max 0,766 0,407 0,303 0,100 1,000 1,000 1,000 0,433 1,000 1,000 1,000

min n/a n/a 0,000 n/a n/a n/a n/a 0,567 0,300 0,000 0,000

Welfare conditions Poor body Sheep scab (Ps. condition ovis )

0,000 0,550 0,050 0,273 0,637 0,633 0,633 0,450 0,650 0,633 0,633

mode 0,000 0,800 0,200 0,433 0,683 0,667 0,667 0,633 0,733 0,667 0,667

max 0,100 1,000 0,450 0,617 0,700 0,667 0,667 0,767 0,767 0,667 0,667

min 0,333 0,150 0,070 0,250 0,000 0,000 0,000 0,733 0,000 0,000 0,000

mode 0,417 0,367 0,217 0,467 0,017 0,005 0,005 0,833 0,033 0,025 0,025

max 0,700 0,767 0,600 0,650 0,033 0,010 0,010 0,933 0,083 0,080 0,080

mode n/a n/a 1,000 n/a n/a n/a n/a 0,950 0,650 0,500 0,500

max n/a n/a 1,000 n/a n/a n/a n/a 0,993 0,660 0,500 0,500

Mastitis min 0,500 0,100 0,033 0,003 0,300 0,300 0,300 0,183 0,750 0,750 0,750

mode 0,663 0,203 0,134 0,007 0,500 0,500 0,500 0,400 0,900 0,900 0,900

max 0,765 0,407 0,270 0,050 0,800 0,800 0,800 0,583 1,000 1,000 1,000


APPENDIX B2.Data from the literature used to parameterise stage 3 models Table B2.1: Disease or welfare condition FMD

Liver fluke

The data for the prevalence and risk factor nodes for stage 3 of the model. Risk factor /odds ratio or node

Parameter values

Farm prevalence

min 0.013

mode 0.050

max 0.290

Animal prevalence

0.030

0.337

0.480

Odds ratio common grazing (open farm) Ewes Lambs Farm prevalence

1.500

2.300

5.100

0.041

0.124

0.240 1 yr old animals < 1 yr old animals > 1 yr old

Probability that animals will present mild or typical disease when taking into account animal level risk factors. min mode max 0,005 0,065 0,150 0,005 0,065 0,150 0,000 0,015 0,060 0,000 0,015 0,060

Mild

Open farm Closed farm

Typical


Typical

animals < 6 months old animals > 6 months old animals < 6 months old animals >6 months old

0,300 0,150 0,100 0,150

0,500 0,250 0,250 0,325

0,800 0,450 0,450 0,400

Mild

Housed farm Extensive farm

Typical

Housed farm

Sheep Scab

Extensive farm

Mild Typical

Poor body condition Good body condition Poor body condition Good body condition

0,200 0,150 0,450 0,103

0,333 0,533 0,567 0,217

0,467 0,700 0,650 0,367

Mild


Typical

Open farm

Liver Fluke

Leg and feet disorders inc. footrot

Closed farm

Mild Typical

High Risk Breed Low Risk Breed High Risk Breed Low Risk Breed

0,134 0,170 0,133 0,034

0,268 0,271 0,267 0,134

0,437 0,367 0,400 0,235

Mild


Typical


0,140 Mild Typical

animals < 1 yr old animals > 1 yr old animals < 1 yr old animals > 1 yr old

0,467 0,533 0,207 0,307

0,633 0,300 0,433


Typical


Mild

Typical

animals < 6 months old animals > 6 months old animals < 6 monthsold animals > 6 months old animals < 6 months old animals > 6 months ol animals < 6 months ol animals > 6 months r o

0,150 0,200 0,100 0,100 0,250 0,250 0,200 0,200

0,350 0,400 0,250 0,300 0,550 0,600 0,450 0,550

0,500 0,600 0,350 0,400 0,700 0,800 0,650 0,700

Mild

Poor body condition Good body condition Poor body condition Good body condition Poor body condition Good body condition Poor body condition Good body condition

0,383 0,237 0,383 0,237 0,700 0,433 0,700 0,433

0,567 0,350 0,567 0,350 0,833 0,633 0,833 0,633

0,717 0,467 0,717 0,467 0,917 0,733 0,917 0,733

Mild

High Risk Breed Low Risk Breed High Risk Breed Low Risk Breed High Risk Breed Low Risk Breed High Risk Breed Low Risk Breed

0,400 0,050 0,400 0,050 0,600 0,400 0,417 0,367

0,550 0,323 0,550 0,323 0,700 0,700 0,617 0,583

0,800 0,650 0,800 0,650 0,867 0,867 0,750 0,733

Mild

0,000

0,000

0,000

0,600 Mild

0,340 0,170 0,203

animals < 1 yr old animals > 1 yr old animals < 1 yr old animals > 1 yr old animals < 1 yr old animals > 1 yr old animals < 1 yr old animals > 1 yr old

The probability of detection of disease/condition at ante mortem inspection for different animal- and farm level risk factors. min mode max 0,005 0,100 0,175 0,005 0,100 0,175 0,005 0,100 0,175 0,005 0,100 0,175 0,050 0,400 0,750 0,050 0,400 0,750 0,050 0,400 0,750 0,050 0,400 0,750


Typical

Typical

Typical

Mild 0,000 0,000 0,000 0,034 0,067 0,034 0,067

0,000 0,000 0,000 0,103 0,170 0,103 0,170

0,000 0,000 0,000 0,217 0,317 0,217 0,317

Typical

The probability of detection of disease/condition at post mortem inspection(current) for different animal- and farm level risk factors. min mode max 0,150 0,500 Open farm animals < 1 0,100 0,150 0,500 animals > 1 0,100 0,150 0,500 Closed farmanimals < 1 0,100 0,150 0,500 animals > 1 0,100 0,550 0,750 Open farm animals < 1 0,400 0,550 0,750 animals > 1 0,400 0,550 0,750 Closed farmanimals < 1 0,400 0,550 0,750 animals > 1 0,400

Mild

Typical

Housed far animals < 6 animals > 6 Extensive f animals < 6 animals > 6 Housed far animals < 6 animals > 6 Extensive f animals < 6 animals > 6

0,400 0,400 0,400 0,400 0,500 0,500 0,500 0,500

0,550 0,550 0,550 0,550 0,750 0,750 0,750 0,750

0,700 0,700 0,700 0,700 0,900 0,900 0,900 0,900

Mild

Open farm Poor body Good body Closed farmPoor body Good body Open farm Poor body Good body Closed farmPoor body Good body

0,033 0,000 0,017 0,000 0,067 0,000 0,033 0,000

0,073 0,007 0,040 0,020 0,183 0,020 0,100 0,010

0,093 0,037 0,060 0,020 0,267 0,090 0,233 0,060

Mild

Open farm High Risk B Low Risk Br Closed farmHigh Risk B Low Risk Br Open farm High Risk B Low Risk Br Closed farmHigh Risk B Low Risk Br

0,150 0,150 0,150 0,150 0,400 0,400 0,400 0,400

0,200 0,200 0,200 0,200 0,450 0,450 0,450 0,450

0,250 0,250 0,250 0,250 0,600 0,600 0,600 0,600

Mild

0,900

0,950

1,000

Open farm animals < 1 animals > 1 Closed farmanimals < 1 animals > 1 Open farm animals < 1 animals > 1 Closed farmanimals < 1 animals > 1

Typical

Typical

Typical

Mild 0,900 0,900 0,900 0,950 0,950 0,950 0,950

0,950 0,950 0,950 1,000 1,000 1,000 1,000

1,000 1,000 1,000 1,000 1,000 1,000 1,000

Typical

The probability of detection of disease/condition at post mortem inspection (intermediate) for different animal- and farm level risk factors. min mode max 0,150 0,500 Open farm animals < 1 0,100 0,150 0,500 animals > 1 0,100 0,150 0,500 Closed farmanimals < 1 0,100 0,150 0,500 animals > 1 0,100 0,550 0,750 Open farm animals < 1 0,400 0,550 0,750 animals > 1 0,400 0,550 0,750 Closed farmanimals < 1 0,400 0,550 0,750 animals > 1 0,400


0,400 0,400 0,400 0,400 0,500 0,500 0,500 0,500

0,550 0,550 0,550 0,550 0,750 0,750 0,750 0,750

0,700 0,700 0,700 0,700 0,900 0,900 0,900 0,900


0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000

0,010 0,005 0,010 0,005 0,025 0,005 0,025 0,005

0,015 0,005 0,015 0,005 0,100 0,060 0,100 0,060


0,150 0,150 0,150 0,150 0,400 0,400 0,400 0,400

0,200 0,200 0,200 0,200 0,450 0,450 0,450 0,450

0,250 0,250 0,250 0,250 0,600 0,600 0,600 0,600

0,900

0,950

1,000

0,900 0,900 0,900 0,950 0,950 0,950 0,950

0,950 0,950 0,950 1,000 1,000 1,000 1,000

1,000 1,000 1,000 1,000 1,000 1,000 1,000


Foot and mouth disease

Mild


Mild

Sheep Scab

Stage3_data

Mild

Typical

Typical

Liver Fluke


Typical

Mild

Typical

Mild

Typical

The probability of detection of disease/condition at post mortem inspection (visual only) for different animal- and farm level risk factors. min mode max 0,150 0,500 Open farm animals < 1 0,100 0,150 0,500 animals > 1 0,100 0,150 0,500 Closed farmanimals < 1 0,100 0,150 0,500 animals > 1 0,100 0,550 0,750 Open farm animals < 1 0,400 0,550 0,750 animals > 1 0,400 0,550 0,750 Closed farmanimals < 1 0,400 0,550 0,750 animals > 1 0,400


0,500 0,500 0,500 0,500 0,500 0,500 0,500 0,500

0,500 0,500 0,500 0,500 0,500 0,500 0,500 0,500

0,500 0,500 0,500 0,500 0,500 0,500 0,500 0,500


0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000

0,010 0,005 0,010 0,005 0,025 0,005 0,025 0,005

0,015 0,005 0,015 0,005 0,100 0,060 0,100 0,060


0,150 0,150 0,150 0,150 0,400 0,400 0,400 0,400

0,200 0,200 0,200 0,200 0,450 0,450 0,450 0,450

0,250 0,250 0,250 0,250 0,600 0,600 0,600 0,600

0,900

0,950

1,000

0,900 0,900 0,900 0,950 0,950 0,950 0,950

0,950 0,950 0,950 1,000 1,000 1,000 1,000

1,000 1,000 1,000 1,000 1,000 1,000 1,000


The probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for a disease or condition, given the N/A,Notifiable if in an outbreak Don't know

0,000

The probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for a disease or condition after visual N/A,Notifiable if in an outbreak Don't know

0,000

The probability that samples for further diagnosis (laboratory testing) are taken in the slaughterhouse for a disease or conditoin after a N/A,Notifiable if in an outbreak Don't know

0,000

Diagnostic test

min

Don't know

n/a

0,000

n/a

Skin scraping

0,000

0,000

0,000

No samples taken

No samples taken

No samples taken

0,000 Don't know

Sensitivity of the diagnostic test

None Bacteriology

Parasitology Not relevant

mode

max

0,600 0,600

0,700 0,700

0,800 0,800

0,700 0,700

0..8 0..8

0,900 0,900

N/a

Very specific and sensitive Not relevant

Foot and mouth disease

Mild


Stage3_data

Mild


Typical


Housed farm Extensive farm

Typical

Housed farm

Sheep Scab

Extensive farm

Mild


Typical

Open farm

Liver Fluke


Closed farm

Mild

Open farm

Typical

Open farm

Closed farm

Closed farm


The probability that veterinarian is called by the farmer for a clinical case of a disease/condition. min mode max 0,717 0,850 0,967 0,550 0,650 0,767 0,717 0,850 0,967 0,550 0,650 0,767 0,650 0,850 0,983 0,633 0,817 0,983 0,650 0,850 0,983 0,633 0,817 0,983


Typical


Mild

Typical

animals < 6 months old animals > 6 months old animals < 6 monthsold animals > 6 months old animals < 6 months old animals > 6 months old animals < 6 months old animals > 6 months r old

0,050 0,025 0,025 0,025 0,275 0,250 0,150 0,150

0,175 0,150 0,150 0,100 0,475 0,450 0,400 0,350

0,350 0,300 0,350 0,250 0,725 0,725 0,600 0,600

Mild

Poor body condition Good body condition Poor body condition Good body condition Poor body condition Good body condition Poor body condition Good body condition

0,250 0,200 0,250 0,200 0,500 0,267 0,600 0,500

0,500 0,450 0,500 0,450 0,750 0,433 0,800 0,700

0,700 0,650 0,700 0,650 0,900 0,533 0,900 0,800

Mild

High Risk Breed Low Risk Breed High Risk Breed Low Risk Breed High Risk Breed Low Risk Breed High Risk Breed Low Risk Breed

0,1 0,17 0,2 0,1 0,2 0,35 0,1 0,17 0,3 0,1 0,2 0,35 0,2 0,35 0,55 0,133333 0,266667 0,4 0,133333 0,233333 0,366667 0,133333 0,266667 0,4

0,033 Mild

The probability that a veterinarian will take an additional step to diagnose disease/condition, for example take samples for laboratory diagnosis of the disease?


0,100

Typical

Typical

Mild

Typical

0,167 0,100 0,167 0,500 0,400 0,567 0,467

0,300 0,233 0,300 0,600 0,567 0,700 0,667

min 0,500 0,500 0,500 0,500 0,700 0,600 0,700 0,600

max 0,800 0,800 0,800 0,800 0,950 0,920 0,950 0,920

1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000

0,350 0,350 0,350 0,350 0,600 0,600 0,600 0,600

0,000 0,000 0,000 0,000 0,350 0,350 0,350 0,350

0,125 0,125 0,125 0,125 0,375 0,375 0,375 0,375

Open farm Poor body condition Good body condition Closed farmPoor body condition Good body condition Open farm Poor body condition Good body condition Closed farmPoor body condition Good body condition

0,500 0,550 0,500 0,550 0,400 0,400 0,400 0,400

0,700 0,750 0,700 0,750 0,550 0,550 0,550 0,550

Open farm animals < 1 yr old animals > 1 yr old Closed farmanimals < 1 yr old animals > 1 yr old Open farm animals < 1 yr old animals > 1 yr old Closed farmanimals < 1 yr old animals > 1 yr old

0,950 1,000 0,950 1,000 0,750 0,750 0,750 0,750

The sensitivity of the additional examination method (test, autopsy) for Disease/Condition given the animal’s age and case type? min mode max Extraction of vescicle fluid for virus testing . Tissues sections from les Elisa - ~100 0,990 0,990 1,000 PCR-91% 0,910 0,910 0,910

histopathology following Autopsy

Skin scraping Lesion scraping for microscopy Skin scrape and look for mites

0,900

Open farm High Risk Breed Low Risk Breed Closed farmHigh Risk Breed Low Risk Breed Open farm High Risk Breed Low Risk Breed Closed farmHigh Risk Breed Low Risk Breed

Bacteriology and antibiotic sensitivMild

Typical

0,450

Typical

mode

Housed far animals < 6 months old animals > 6 months old Extensive f animals < 6 monthsold animals > 6 months old Housed far animals < 6 months old animals > 6 months old Extensive f animals < 6 months old animals > 6 months r old

0,233 Mild

0,033 0,033 0,033 0,233 0,200 0,300 0,267

Open farm animals < 1 yr old animals > 1 yr old Closed farmanimals < 1 yr old animals > 1 yr old Open farm animals < 1 yr old animals > 1 yr old Closed farmanimals < 1 yr old animals > 1 yr old

The additional examination methods (test, autopsy) would be undertaken by the veterinarian for Disease/Condition?

0,550

0,650

Mild Typical

Housed far animals < 6 Housed far animals < 6

0,700 0,800

0,900 0,900

1,000 1,000

Mild

Open farm Poor body Good body Closed farmPoor body Good body

0,300 0,200 0,700 0,600

0,600 0,500 0,900 0,900

1,000 0,800 1,000 1,000

Skin scrape Elisa

0,863 0,720

0,915 93,700

0,968 98,500

Open farm High Risk B Elisa Low Risk Breed Closed farmHigh Risk Breed Low Risk Breed Open farm High Risk Breed Low Risk Breed Closed farmHigh Risk Breed Low Risk Breed

None - but parasitology is very specific and sensitive Mild

0,450 0,450 0,450 0,450 0,450 0,450 0,450

0,550 0,550 0,550 0,550 0,550 0,550 0,550

0,650 0,650 0,650 0,650 0,650 0,650 0,650

Post-mortem on farm and Autopsy and faecal egg count Typical

0,706

0,824

0,983

1,000

1,000

1,000


1,000 1,000 1,000 1,000 1,000 1,000 1,000

1,000 1,000 1,000 1,000 1,000 1,000 1,000

1,000 1,000 1,000 1,000 1,000 1,000 1,000

Elisa test Faecal test

0,770 0,600

0,860 0,800

0,996 1,000

Stage3_data

Representation of the overlap in surveillance activities across different population strata, for the two surveillance system components (SSC) abattoir inspection and clinical surveillance in a small ruminant population divided into four separate strata by two different animal- and herd level risk factors (see Figure 3 in the main report). The numbers stand for the proportion of the population that will be covered with one or the other SSC. By definition all animals are covered by clinical surveillance, with one part of the animals also being inspected at slaughter (overlap). Thus, the

Farm-level risk factor

Animal level risk factor Abattoir inspection only

Clinical surveillance

Open farm system

Animals >1 yr Animals 1 yr Animals 1 year / Typical Open farm / >1 year / Mild Open farm / 1 year / Mild Closed farm /

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