Title Epidemiology of Johne's Disease in organised dairy farms of Punjab (India) and analysis of associated risk factors
Author(s) Garg R, Patil P, Singh R, Sharma S, Mahajan V, Verma S, Sandhu KS.
Institution(s) Department of Epidemiolgy and Preventive Veterinary Medicine, College of Veterinary Sciences, Guru Angad Dev Veterinary Animal Sciences Univeristy, Punjab, India.
Source Ninth International Colloquium on Paratuberculosis
Section 5: Epidemiology and control strategies
Presentation Poster
Abstract

The control and eradication of Johne's disease is hindered by the prolonged incubation period, presence of undetected subclinical cases, absence of specific diagnostic tools and lack of knowledge of strain diversity. The present study was conducted to understand the epidemiological distribution of the disease and to analyze associated risk factors in the state of Punjab (India). The organized dairy farms (n=30) distributed under different ecological zones were selected randomly and minimum of ten animals from each farm were sampled. Milk and serum samples were subjected to ELISA for detection of Mycobacterium avium subsp paratuberculosis specific antibodies whereas the milk samples were also subjected to IS 900 based PCR. The apparent prevalence based on serum ELISA (sELISA), milk ELISA (mELISA) and milk PCR was found to be 15.6, 16.3 and 14.0% respectively. The degree of association between different tests revealed low degree of agreement between sEISA and m ELISA (kappa value 0.326) however, high degree of agreement was noticed between mELISA and PCR (kappa value 0.682). The present study employing ELISA and PCR revealed high prevalence of the disease in the region in contrast to low prevalence recorded earlier based on histopatholgy and intradermal johnin testing. The results of the study suggested the usefulness of antibody detection test (ELISA) for screening of affected farms followed confirmation using PCR for identification of animals shedding the organism. The risk factors associated with the disease were identified using binary logistic regression analysis by SPSS (Statistical Package for Social Sciences) program.


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