Defining syndromes using cattle meat inspection data for syndromic surveillance purposes: a statistical approach with the 2005–2010 data from ten French slaughterhouses

BMC Veterinary Research

Emilie Gay⁴  Didier Calavas⁴  Christian Ducrot²  Pascal Hendrikx³  Jean-Luc Vinard⁴  Xavier Maugey¹  Eric Morignat⁴  Céline Dupuy² 

[1] Direction générale de l’alimentation, 251, rue de Vaugirard, Paris, Cedex 15, 75732, France;Unité d’épidémiologie animale, UR346, INRA, St Genès Champanelle, 63122, France;Direction scientifique des laboratoires, Agence nationale de sécurité sanitaire de l’alimentation de l’environnement et du travail (Anses), 37-31 avenue du général, Maisons-Alfort, Cedex, Leclerc F-94701, France;Unité Epidémiologie, Agence nationale de sécurité sanitaire de l’alimentation, de l’environnement et du travail (Anses), 31 avenue Tony Garnier, Lyon, Cedex 07, F69364, France

关键词: Cattle;    Slaughterhouses;    Meat inspection;    Animal health;    Syndromic surveillance;   

Others  :  1119550
DOI  :  10.1186/1746-6148-9-88

 received in 2012-11-22, accepted in 2013-04-25,  发布年份 2013

【 摘 要 】

Background

The slaughterhouse is a central processing point for food animals and thus a source of both demographic data (age, breed, sex) and health-related data (reason for condemnation and condemned portions) that are not available through other sources. Using these data for syndromic surveillance is therefore tempting. However many possible reasons for condemnation and condemned portions exist, making the definition of relevant syndromes challenging.

The objective of this study was to determine a typology of cattle with at least one portion of the carcass condemned in order to define syndromes. Multiple factor analysis (MFA) in combination with clustering methods was performed using both health-related data and demographic data.

Results

Analyses were performed on 381,186 cattle with at least one portion of the carcass condemned among the 1,937,917 cattle slaughtered in ten French abattoirs. Results of the MFA and clustering methods led to 12 clusters considered as stable according to year of slaughter and slaughterhouse. One cluster was specific to a disease of public health importance (cysticercosis). Two clusters were linked to the slaughtering process (fecal contamination of heart or lungs and deterioration lesions). Two clusters respectively characterized by chronic liver lesions and chronic peritonitis could be linked to diseases of economic importance to farmers. Three clusters could be linked respectively to reticulo-pericarditis, fatty liver syndrome and farmer’s lung syndrome, which are related to both diseases of economic importance to farmers and herd management issues. Three clusters respectively characterized by arthritis, myopathy and Dark Firm Dry (DFD) meat could notably be linked to animal welfare issues. Finally, one cluster, characterized by bronchopneumonia, could be linked to both animal health and herd management issues.

Conclusion

The statistical approach of combining multiple factor analysis with cluster analysis showed its relevance for the detection of syndromes using available large and complex slaughterhouse data. The advantages of this statistical approach are to i) define groups of reasons for condemnation based on meat inspection data, ii) help grouping reasons for condemnation among a list of various possible reasons for condemnation for which a consensus among experts could be difficult to reach, iii) assign each animal to a single syndrome which allows the detection of changes in trends of syndromes to detect unusual patterns in known diseases and emergence of new diseases.

【 授权许可】

   
2013 Dupuy et al.; licensee BioMed Central Ltd.

【 图 表 】

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【 参考文献 】

• [1]European parliament: Council regulation laying down specific rules for the organisation of official controls on products of animal origin intended for human consumption. Brussel, Belgium: 854/2004 Official Journal of the European Union; 2004:83-127.
• [2]Dupuy C, Morignat E, Gay E, Calavas D: Risk factors for condemnation in cattle slaughtered in a French abattoir from 2006 to 2009. Lisbon, Portugal: XXVII World Buiatrics Congress: 4th June 2012 2012; 2012:17.
• [3]Triple S Project: Assessment of syndromic surveillance in Europe. Lancet 2011, 378(9806):1833-1834.
• [4]Katz R, May L, Baker J, Test E: Redefining syndromic surveillance. J Epidemiol Global Health 2011, 1(1):21-31.
• [5]Alton G, Pearl D, Bateman K, McNab W, Berke O: Factors associated with whole carcass condemnation rates in provincially-inspected abattoirs in Ontario 2001–2007: implications for food animal syndromic surveillance. BMC Vet Res 2010, 6:42. BioMed Central Full Text
• [6]Alton GD, Pearl DL, Bateman KG, McNab WB, Berke O: Suitability of bovine portion condemnations at provincially-inspected abattoirs in Ontario Canada for food animal syndromic surveillance. BMC Vet Res 2012, 8(1):88. BioMed Central Full Text
• [7]Liste, codes et types des races bovines de France. http://www.franceagrimer.fr/ webcite
• [8]European parliament: European parliament: Council regulation establishing a common organisation of agricultural markets and on specific provisions for certain agricultural products. Brussel, Belgium: 1234/2007 Official Journal of the European Union; 2007.
• [9]Perrin J-B, Ducrot C, Vinard J-L, Gauffier A, Calavas D, Hendrikx P: Using the national cattle register to estimate the excess mortality during an epidemic: application to an outbreak of bluetongue serotype 8. Epidemics 2010, 2:207-214.
• [10]French Ministry of Agriculture: Modalités d'utilisation d'une liste harmonisée caractérisant les lésions et autres non-conformités rencontrées en abattoir d'animaux de boucherie et à l'origine de saisies vétérinaires. Paris, France: DGAL/SDSSA/N2006-8139; 2006.
• [11]R Development Core Team: R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistial Computing; 2010.
• [12]Bécue-Bertaut M, Pagès J: Multiple factor analysis and clustering of a mixture of quantitative, categorical and frequency data. Comput. Stat. Data Anal. 2008, 52(6):3255-3268.
• [13]Escofier B, Pagès J: Analyses factorielles simples et multiples. Objectifs, méthodes et interprétation, DUNOD edn. Paris: Dunod; 2008.
• [14]Costard S, Porphyre V, Messad S, Rakotondrahanta S, Vidon H, Roger F, Pfeiffer DU: Multivariate analysis of management and biosecurity practices in smallholder pig farms in Madagascar. Prev Vet Med 2009, 92(3):199-209.
• [15]Lebart L, Morineau A, Piron M: Statistique exploratoire multidimensionnelle, visualisation et inférence en fouilles de données. 2006 edition. Paris: Dunod; 2006.
• [16]Lê S, Josse J, Husson F: FactoMineR: An R Package for multivariate analysis. J Stat Softw 2008, 25(1):1-18.
• [17]Warns-Petit E, Morignat E, Artois M, Calavas D: Unsupervised clustering of wildlife necropsy data for syndromic surveillance. BMC Vet Res 2010, 16:6-56.
• [18]Murty MN, Krishna G: A hybrid clustering procedure for concentric and chain-like clusters. Int J Comput Inf Sci 1981, 10(6):397-412.
• [19]Wong MA: A hybrid clustering method for identifying high-density clusters. J Am Statist Assoc 1982, 77(380):841-847.
• [20]Ward J: Hierarchical grouping to optimize an objective function. J Am Statist Assoc 1963, 58(301):236-244.
• [21]Gröhn YT, Bruss ML: Effect of diseases, production, and season on traumatic reticuloperitonitis and ruminal acidosis in dairy cattle. J Dairy Sci 1990, 73(9):2355-2363.
• [22]Rajala-Schultz PJ, Gröhn YT: Culling of dairy cows. Part I. Effects of diseases on culling in Finnish Ayrshire cows. Prev Vet Med 1999, 41(2–3):195-208.
• [23]Akkoç A: Traumatic reticulopericarditis in a Saanen Goat. Turk J Vet Anim Sci 2007, 31(4):283-285.
• [24]Waldner C, Kennedy R, Rosengren L, Clark E: A field study of culling and mortality in beef cows from western Canada. Can Vet J 2009, 50(5):491-499.
• [25]Grummer RR: Nutritional and management strategies for the prevention of fatty liver in dairy cattle. Vet J 2008, 176(1):10-20.
• [26]Bobe G, Young JW, Beitz DC: Invited review: pathology, etiology, prevention, and treatment of fatty liver in dairy cows. J Dairy Sci 2004, 87(10):3105-3124.
• [27]Andrew AH, Blowey RW, Boyd H, Eddy RG: Bovine medicine diseases and husbandry of cattle. 2nd edition. Ames,USA: Blackwell Publishing; 2004.
• [28]Bradford PS: Large animal internal medicine. St Louis, USA: Mosby edn; 1990.
• [29]Cherel Y, Couillandeau P, Lecomte O, Spindler C, Larcher T: Autopsie des bovins, Collection Atlas edn. Rueil-Malmaison, France: Le Point Vétérinaire; 2006.
• [30]Roberts JL: The prevalence and economic significance of liver disorders and contamination in grain-fed and grass-fed cattle. Aust Vet J 1982, 59(5):129-132.
• [31]Kaplan RM: Fasciola hepatica: a review of the economic impact in cattle and considerations for control. Vet Ther 2001, 2(1):40-50.
• [32]Brown TR, Lawrence TE: Association of liver abnormalities with carcass grading performance and value. J Anim Sci 2010, 88(12):4037-4043.
• [33]Sloss V: A clinical study of dystocia in cattle. Aust Vet J 1974, 50(7):294-297.
• [34]Roth L, King JM: Traumatic reticulitis in cattle: a review of 60 fatal cases. J Vet Diagn Invest 1991, 3(1):52-54.
• [35]Morlot C: Etude épidémiologique et statistique de la cysticercose musculaire bovine en France en,2010. Propositions de mesures de controle. Lyon: Université Claude Bernard; 2011.
• [36]Kyvsgaard NC, Ilsoe B, Henriksen S, Nansen P: Distribution of taenia saginata cysts in carcases of experimentally infected calves and its significance for routine meat inspection. Res Vet Sci 1990, 49(1):29-33.
• [37]Lopes WDZ, Santos TR, Soares VE, Nunes JLN, Mendonça RP, de Lima RCA, Sakamoto CAM, Costa GHN, Thomaz-Soccol V, Oliveira GP: Preferential infection sites of Cysticercus bovis in cattle experimentally infected with Taenia saginata eggs. Res Vet Sci 2011, 90(1):84-88.
• [38]Scandrett B, Parker S, Forbes L, Gajadhar A, Dekumyoy P, Waikagul J, Haines D: Distribution of Taenia saginata cysticerci in tissues of experimentally infected cattle. Vet Parasitol 2009, 164(2–4):223-231.
• [39]Shupe JL: Arthritis in cattle. Can Vet J 1961, 2(10):369-376.
• [40]Warriss PD: The handling of cattle pre-slaughter and its effects on carcass and meat quality. Appl Anim Behav Sci 1990, 28(1–2):171-186.
• [41]Knowles G: A review of the road transport of cattle. Vet Rec 1999, 144(8):197-201.
• [42]Kleinman KP, Abrams AM, Kulldorff M, Platt R: A model-adjusted space-time scan statistic with an application to syndromic surveillance. Epidemiol Infect 2005, 133:409-419.