Bayesian estimation of flock-level sensitivity of detection of Salmonella spp., Enteritidis and Typhimurium according to the sampling procedure in French laying-hen houses

Preventive Veterinary Medicine

Volumn 84, Issue 1-2, 2008, Pages 11-26

  Mahe A ^a   Bougeard, S ^a   Huneau Salaun A ^a   Le Bouquin, S ^a   Petetin, I ^a   Rouxel, S ^a   Lalande, F ^a   Beloeil, P A ^b   Rose, N ^a  

^a Healthy Pigs Production and Experimentation Section   (France)

^b Direction Generale de l'Alimentation   (France)

Author keywords

Bayesian estimation; Laying hens; Salmonella; Sampling procedure; Sensitivity

Indexed keywords

ANIMAL; ANIMAL HUSBANDRY; ANIMAL SALMONELLOSIS; ARTICLE; BAYES THEOREM; BIOLOGICAL MODEL; BIRD DISEASE; CHICKEN; DUST; EPIDEMIOLOGY; FECES; FEMALE; FRANCE; ISOLATION AND PURIFICATION; MICROBIOLOGY; PREVALENCE; SALMONELLA; SENSITIVITY AND SPECIFICITY;

ANIMAL HUSBANDRY; ANIMALS; BAYES THEOREM; CHICKENS; DUST; FECES; FEMALE; FRANCE; MODELS, BIOLOGICAL; POULTRY DISEASES; PREVALENCE; SALMONELLA; SALMONELLA INFECTIONS, ANIMAL; SAMPLING STUDIES; SENSITIVITY AND SPECIFICITY;

SALMONELLA; SALMONELLA ENTERITIDIS; SALMONELLA TYPHIMURIUM;

EID: 39149132504     PISSN: 01675877     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.prevetmed.2007.10.003     Document Type: Article

References (26)

1. Best N.G., Cowles M.K., and Vines S.K. CODA Manual version 0. 30 (1995), MRC Biostatistics Unit, Cambridge, UK
2. Branscum A.J., Gardner I.A., and Johnson W.O. Estimation of diagnostic-test sensitivity and specificity through Bayesian modelling. Prev. Vet. Med. 68 (2005) 145-163
3. Brooks S.P., and Gelman A. Alternative methods for monitoring convergence of iterative simulations. J. Comp. Graph. Statist. 7 (1998) 434-455
4. Brooks S.P., and Roberts G.O. Convergence assessment techniques for Markov chain Monte Carlo. Statist. Comput. 8 (1998) 319-335
5. Congdon P. Applied Bayesian Modelling (2003), John Wiley & Sons Ltd p. 457
6. Delmas G., Gallay A., Espié E., Haeghebaert S., Pihier N., Weill F.X., De Valk H., Vaillant V., and Désenclos J.C. Foodborne-diseases outbreaks in France between 1996 and 2005. B.E.H. 51/52 (2006) 418-422
7. Enøe C., Georgiadis M.P., and Johnson W.O. Estimation of sensitivity and specificity of diagnostic tests and disease prevalence when the true disease state is unknown. Prev. Vet. Med. 45 (2000) 61-81
8. Enøe C., Andersen S., Sørensen V., and Willeberg P. Estimation of sensitivity, specificity and predictive values of two serologic tests for the detection of antibodies against actinobacillus pleuropneumoniae serotype 2 in the absence of a reference test (gold standard). Prev. Vet. Med. 51 (2001) 227-243
9. European Commission, 2004. Baseline study on the prevalence of Salmonella in laying flocks of Gallus gallus in the EU. Technical specifications, vol SANCO/34/2004 Rev3. European Commission-Health & Consumer Protection Directorate-General, 16 p.
10. European Food Safety Authority, 2006. The Community Summary Report on Trends and Sources of Zoonoses, Zoonotic Agents, Antimicrobial Resistance and Foodborne Outbreaks in the European Union in 2005, vol 94, 288 p.
11. Fuller W.A. Regression Analysis for Sample Survey. Sankhy 37 (1975) 117-132 Series C
12. Gelman A., Clarin J.B., Stern H.S., and Rubin D.B. Bayesian Data Analysis (1997), Chapman & Hall, London p. 668
13. Gelman A., Sturtz S., Ligges U., Gorjanc G., and Kerman J. The R2WinBUGS Package Manual Version 2.0-4 (2006), Statistic Department Faculty, New York, USA
14. Georgiadis M.P., Johnson W.O., Gardner I.A., and Singh R. Correlation-adjusted estimation of sensitivity and specificity of two diagnostic tests. Appl. Statist. 52 (2003) 63-76
15. Geurden T., Berkvens D., Geldhof P., Vercruysse J., and Claerebout E. A Bayesian approach for the evaluation of six diagnostic assays and the estimation of Cryptosporidium prevalence in dairy calves. Vet. Res. 37 (2006) 671-682
16. Heidelberger P., and Welch P.D. Simulation run length control in the presence of an initial transient. Opns. Res. 31 (1983) 1109-1144
17. Ihaka R., and Gentleman R. R: a language for data analysis and graphics. J. Comp. Graph. Statist. 5 (1996) 299-314
18. Kostoulas P., Leontides L., Billinis C., and Florou M. Application of a semi-dependent latent model in the Bayesian estimation of the sensitivity and specificity of two faecal culture methods for diagnosis of paratuberculosis in sub-clinically infected Greek dairy sheep and goats. Prev. Vet. Med. 76 (2006) 121-134
19. Kostoulas P., Leontides L., Enøe C., Billinis C., Florou M., and Sofia M. Bayesian estimation of sensitivity and specificity of serum ELISA and faecal culture for diagnosis of paratuberculosis in Greek dairy sheep and goats. Prev. Vet. Med. 76 (2006) 56-73
20. Ministère de l'Agriculture de l'Alimentation de la Pêche et des Affaires Rurales, 2004. Note de service DGAL/SDSPA/N2004-8241. Ministère de l'Agriculture de l'Alimentation, de la Pêche et des Affaires rurales-Direction générale de l'Alimentation, 11 p.
21. Raftery A.L., and Lewis S. Comment: one long run with diagnostics: implementation strategies for Markov chain Monte Carlo. Statist. Sci. 7 (1992) 493-497
22. SAS Institute Inc. SAS/STAT User's Guide (2002), SAS Institute, Cary, NC. USA
23. Spiegelhalter D., Thomas A.T., Best N., and Gilks W. BUGS: Bayesian Inference Using Gibbs Sampling Version 0.50 (1996), MRC Biostatistics, Cambridge, UK
24. Toft N., Innocent G.T., Gettinby G., and Reid S.W.J. Assessing the convergence of Markov Chain Monte Carlo methods: an example from evaluation of diagnostic tests in absence of a gold standard. Prev. Vet. Med. 79 (2007) 244-256
25. Voogt N., Raes M., Wannet W.J.B., Henken A.M., and Van de Giessen A.W. Comparison of selective enrichment media for the detection of Salmonella in poultry faeces. Lett. Appl. Microbiol. 32 (2001) 89-92
26. Woodruff R.S. A Simple method for approximating the variance of a complicated estimate. J. Am. Stat. Asso. 66 (1971) 411-414