肉類檢驗(yàn)的優(yōu)點(diǎn)和缺點(diǎn)外文文獻(xiàn)英文

Strengths and weaknesses of meat inspection as a contribution to animal health and welfare surveillance K D C St rk a b S Alonsob N Dadiosb C Dupuyc L Ellerbroekd M Georgievb e J Hardstaff b A Huneau Sala nf C Laugierg A Mateusa A Nigscha b A Afonsoe A Lindberg h aSAFOSO Inc Bern Switzerland bRoyal Veterinary College North Mymms Hertfordshire United Kingdom cFrench Agency for Food Environmental and Occupational Health and Safety ANSES Epidemiology Unit Lyon France dFederal Institute for Risk Assessment Berlin Germany eEuropean Food Safety Authority Parma Italy fFrench Agency for Food Environmental and Occupational Health and Safety ANSES UEB Ploufragan France gFrench Agency for Food Environmental and Occupational Health and Safety ANSES Dozul Laboratory for Equine Diseases Goustranville France hNational Veterinary Institute Uppsala Sweden a r t i c l ei n f o Article history Received 1 July 2013 Received in revised form 30 October 2013 Accepted 5 November 2013 Keywords Food safety Animal welfare Disease surveillance Disease control programmes a b s t r a c t Meat inspection MI is one of the most widely implemented and longest running systems of surveil lance It was primarily introduced to identify meat of animals that is not fi t for human consumption Additionally MI was progressively recognised as a suitable source of data collection and for monitoring a broad spectrum of diseases and conditions concerning animal health and welfare For Europe MI tasks are regulated at the European rather than country level and include a set of activities before and after stunning ante and post mortem inspection involving visual inspection palpation and incisions Over the last decade the current MI protocol has been challenged because of its low sensitivity for important public health hazards We aimed to assess the strengths and weaknesses of current MI protocols with primary focus on its utility in the context of animal health e including both notifi able and production diseases e and welfare i e its capacity to detect cases with an aim to quantify the frequency of animal disease and welfare cases The consequences of an alternative inspection protocol using visual only inspection were also explored As a fi rst step a review of grey and published literature was conducted for a selected number of diseases and welfare conditions in seven species or species groups swine poultry bovines small ru minants solipeds and farmed game represented by red deer wild boar rabbits and ostriches This re view highlighted a substantial lack of suitable and accessible published data on the frequency of occurrence of many diseases and conditions affecting food animals in Europe Additionally there were very limited data on the detection performance of MI particularly in relation to specifi c degrees of severity of clinical signs Due to the data gaps a large proportion of input data used in this work was based on expert opinion and general biologic manifestations of the conditions investigated The prob ability of case detection was quantifi ed using a scenario tree modelling approach taking into account the frequency of case presentation and inspection coverage In general the performance of MI was highly correlated with the presence of clinical and or patho logical signs in affected animals Early or subclinical cases were likely to be non detectable at slaughter Regarding detectable cases the impact of moving to visual only inspection was negligible for most notifi able diseases and conditions considered with a few exceptions primarily detectable cases of tuberculosis Current MI activities were found to be effective to detect the majority of animal welfare conditions considered by species predominantly by ante mortem inspection The effectiveness of MI was also considered for endemic diseases that are not currently subject to systematic control efforts These included respiratory diseases and parasite infections It was shown that Corresponding author SAFOSO Inc Bremgartenstrasse 109a CH 3012 Bern Switzerland Tel 41 631 29 29 fax 41 631 29 32 E mail addresses katharina staerk safoso ch kstaerk rvc ac uk K D C St rk Contents lists available at ScienceDirect Food Control journal homepage 0956 7135 e see front matter 2013 Elsevier Ltd All rights reserved http dx doi org 10 1016 j foodcont 2013 11 009 Food Control 39 2014 154e162 MI could provide an effi cient means of identifying producers in need of animal health advice provided that information is collected and fed back to veterinarians and livestock farmers Within an integrated information system MI could substantially contribute to the control of a considerable range of animal health and welfare issues Data already collected need to be made available for on farm decision making It was also noted that if the slaughter population is strongly affected by international trade i e where a large proportion of animals originate from one country and are slaughtered in another the usefulness of MI for endemic disease surveillance will be affected by either reduced coverage or bias or both In conclusion our results indicate that while ante mortem inspection remains essential for the detection of animal welfare conditions a move to visual only post mortem inspection has e for the diseases and conditions considered e negligible negative impact on disease control However in coun tries or regions that are not free of TB special relevance of palpation and cutting of lymph nodes will have to be considered MI information has considerable potential to inform disease control efforts but only few countries use it systematically limiting the actual benefi t that is achieved by these data Finally MI can also provide back up surveillance in a situation where other means of detection fail and may represent the sole means of case detection for certain infections e g liver fl uke or cestodes 2013 Elsevier Ltd All rights reserved 1 Introduction Meat inspection MI is one of the most widely implemented and longestrunning systems of surveillance Its primaryobjective is to identify animals that are not fi t for human consumption and to remove their carcasses and offal from the food chain Additional objectives are to support animal disease control and to identify and prosecute animal welfare issues As such MI will contribute infor mation on notifi able diseases and zoonoses endemic production diseases and animal welfare MI tasks are regulated at European Union EU level and include a set of activities before and after stunning death ante and post mortem inspection AMI PMI involving visual inspection palpation and incision of particular organs and lymph nodes Regulation EC No 854 2004 Over the last decade the current MI protocol has been chal lenged because of its low sensitivity for important public health hazards such as Salmonella and Campylobacter and because of possible contamination risks Berends Snijders Pacheco Brinch Kruse Petersen Hathaway Hill Brouwer et al 2013 Hill Horrigan et al 2013 94 pp Moo O Boyle Mathers Berends Van Knapen Dadios Hardstaff Alonso St rk Dupuy Hendrikx Hardstaff EFSA 2012 Ellerbroek Mateus St rk Alonso Huneau et al 2011 Hardstaff et al 2012 Laugier ii fi rst elicitation round iii data collation iv second elicitation round and v validation of fi nal estimates Hsu Knol Slottje Van Der Sluijs the second round was conducted as a group discussion using the combined values median from the fi rst round The questionnaires were piloted with a few individuals before use 2 5 Scenario tree modelling A quantitative stochastic model was developed for each of the diseases conditions considered in each species in order to esti mate the detection probability of ante and post mortem in spection procedures Fig 2 A different set of parameters was used for the alternative inspection scenarios In addition for endemic diseases and conditions the DF was the measure of interest It was estimated with regard to the slaughtered popu lation and for a subset of diseases and conditions also for the overall population For notifi able diseases absent in a region the measure of interest was the component sensitivity which is the probability of detecting one or more animals with the disease in question if it is present at or above a certain design prevalence Martin Cameron Greiner 2007 Details of all models are provided in the respective reports published by EFSA www efsa europa eu Briefl y consolidatedestimatescollectedduring expert elicitation the most likely minimum and maximum values for ante and post mortem inspection were used as input together with estimates of proportions of case types likely to be presented at the abattoir for slaughter For the comparison with alternative surveillance systems proportions of the population within certain risk strata coverage of the surveillance compo nents and the probability of detection by the alternative systems were also used as input The output was estimated by translation of the consolidated estimates into BetaPert distributions and by using Monte Carlo simulation 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 Fig 2 The most likely as well as 5th and 95th percentiles the credi bility 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 Any overlap of the credibility intervals was used to assess whether scenarios differed signifi cantly from each other 3 Results The review of grey and published literature highlighted a sub stantial lack of data on the frequency of occurrence of many of the selected diseases and conditions both at individual animal herd fl ock and abattoir level Additionally there were very limited data on the detection performance of MI This had been anticipated and a large proportion of input data used in this work was therefore based on expert opinion and biologic features of listed diseases conditions The experts initially had to provide quantitative estimates for case detection through individual MI tasks This was found to be very challenging Also the lack of independence between tasks was confi rmed byexperts Determination of the animal health status or the batch health status is the result of an integrated approach of the different tasks of AMI including food chain information FCI and PMI The approach was therefore modifi ed aftercompleting the pig and poultry reports such that AMI and PMI tasks were com bined in one estimate A further challenge was the defi nition of typical and mild case The methods used in calculating over all detection probabilities for each species are therefore not identical across species The majority of examples provided below are therefore taken from species other than pigs and poultry Detection probabilities for individual diseases and conditions varied greatly within species almost ranging from 0 to 1 For example for solipeds low probabilities of detection at PMI were obtained for typical and mild cases of West Nile fever and grass sickness with most likely values of 0 00 and 0 06 respectively At the other end of the spectrum again for solipeds the PMI detection probability for echinococcosis hydatidosis was 0 73 and AMI detection probability for grass sickness was 0 80 Combined AMI and PMI for solipeds ranged from0 33 to0 95 values for fascioliasis and strangles A similar degree of variability was observed for other species data not shown Differences were also marked be tween AMI and PMI depending on the clinical manifestation of a disease or condition Welfare conditions were generally more likely to be observed during AMI with a few exceptions such as bruising or dark fi rm dry meat in pigs When considering all cases i e including non detectable stages of disease and condition the DF decreased according to the pro portion of non detectable cases It also varied greatly between diseasesandconditionswithinspeciesdepending ontheir respective clinical and pathological manifestations For example in wild boar the most likely combined AMI and PMI detection prob abilities for classical and African swine fever foot and mouth dis ease and tuberculosis decreased from 0 85 0 82 and 0 79 to 0 78 0 81 and 0 66 respectively The DF is a summary measure for the case fi nding capacity of MI and is an estimate of the proportion of all cases in the popu lation that are detected by the system in question The approach to estimate DF was developed as part of this project and used for all species except swine and poultry The results confi rmed that the role of MI as a tool for case detection varies at the general popu lation level mainly depending on the proportion of the population covered in combination with the detectability at MI For example the DF of MI for cases of bovine tuberculosis TB was 0 05 indi cating that out of a 100 TB infected animal in the cattle population only 5 would be detected at slaughter Extremely low DFs for MI were observed for solipeds This is because a signifi cant proportion of horses are not killed at an abattoir and therefore lost to the chance of detection by MI i e the coverage of the system is in practice very low We also compared MI with alternative surveillance designs such as clinical surveillance on farm or targeted testing as part of a control programme Because only a limited number of diseases and 1 Questionnaires are available from the authors on request K D C St rk et al Food Control 39 2014 154e162158 conditions were considered results should be interpreted with caution The fi ndings indicate that there is no general trend as to the relative advantage of abattoir surveillance in comparison to alternative surveillance components However it was shown that the combination of MI with other surveillance components was more effective than MI alone Also for species that are unlikely to be seen by a vet such as farmed deer or wild boar or conditions that are unlikely to generate a veterinary visit such as fascioliasis MI may in practice be the only means of detection Regarding detectable cases of most welfare conditions the impact of moving to visual only inspection was negligible This was true across all species For example for bovines the DF for bruising cleanliness foot and leg disorders fractured limbs integument alterations and body condition score were all unaffected by a change to visual only inspection Regarding disease detection the DF using visual only MI tended to be lower than with the current MI protocol but the reductions were generally 600 000 cattle are moved to be slaughtered in another EU country every year Anonymous 2012 This effect is much larger for pigs where some countries export a substantial proportion of their pigs to be reared and or slaughtered abroad Ultimately MI is also a resource consuming activity and some body has to pay for it Currently costs are incurred by MI services who claim part of it back from primary producers in the form of inspection fees However the latter are rarelycovering all costs The recording of animal health related MI inspection fi ndings would require additional resources although automated recording sys tems can make the task more effi cient In conclusion our results indicate that while ante mortem in spection remains essential for the detection of animal welfare conditions a move to visual only post mortem inspection has e for the diseases and conditions considered e negligible negative impacton general case detection in countries that are free of TB and for all countries where MI information is not systematically used to inform disease control efforts However MI also plays an important role in that it can function as back up surveillance in a situation where other means of detection fail or where there is basically no other means of detection e g as for fascioliasis in cattle Also MI information could be used to assess the effectiveness of other dis ease control measures such as vaccination In general additional information from the farm of origin the so called information on the food chain could be used much more systematically to provide a basis for a more risk based MI Acknowledgements Work leading to this publication was funded by a contract awardedbytheEuropeanFoodSafetyAgency EFSA We acknowledge the contributions of numerous individuals who participated in the expert elicitation exercises We are also grateful to members of the working group appointed by EFSA to integrate this work into several scientifi c opinions particularly to the chair Prof Simon More References Alban L Vilstrup C Steenberg B Elvang Jensen H Alb k B Thune Stephensen F et al 2008 Assessment of the risk for humans associated with supply chain meat inspection e The Danish way Copenhagen Danish Agriculture and Food Council Available online at http www lf dk w media lf Aktuelt Publikationer Svinekod Modernisation 20of 20Meat 20Inspection DK ashx Accessed 08 10 13 Allain V Le Bouquin S Donguy M P Magras C 2013 Inspection sanitaire en abattoirs de volailles de chair quelles missions quelle organisation In 10th Journ es de la Recherche Avicole et Palmip des Foie Gras 26e28 March 2013 La Rochelle France Anonymous 2010 Process manual for expert elicitation tool Australian Centre for Risk Analysis Available online www acera unimelb edu au materials endorsed 0611 process manual pdf Accessed 23 04 13 Anonymous 2012 Animal health DG Sanco Unit G2 health and consumers activity report2011 Availableathttp ec europa eu food animal resources ahsc report 2011 en pdf Berends B R Snijders J M A Van Logtestijn J G 1993 Effi cacy of current EC meat inspection procedures and some proposed revisions with respect to microbiological safety a critical review Veterinary Record 133 411e415 Berends B R Van Knapen F Snijders J M A 1996 Suggestions for the con struction analysis and the use of descriptive epi