Abstract

Mycobacteria cause major diseases including human tuberculosis, bovine tuberculosis and Johne’s disease. In livestock, the dominant species is M. bovis causing bovine tuberculosis (bTB), a disease of global zoonotic importance. In this study, we estimated the prevalence of Mycobacteria in slaughter cattle in Cameroon. A total of 2,346 cattle were examined in a cross-sectional study at four abattoirs in Cameroon. Up to three lesions per animal were collected for further study and a retropharyngeal lymph node was collected from a random sample of non-lesioned animals. Samples were cultured on Lowenstein Jensen media and the BACTEC MGIT 960 system, and identified using the Hain® Genotype kits. A total of 207/2,346 cattle were identified with bTB-like lesions, representing 4.0% (45/1,129), 11.3% (106/935), 23.8% (38/160) and 14.8% (18/122) of the cattle in the Bamenda, Ngaoundere, Garoua and Maroua abattoirs respectively. The minimum estimated prevalence of M. bovis was 2.8% (1.9–3.9), 7.7% (6.1–9.6), 21.3% (15.2–28.4) and 13.1% (7.7–20.4) in the four abattoirs respectively. One M. tuberculosis and three M. bovis strains were recovered from non-lesioned animals. The high prevalence of M. bovis is of public health concern and limits the potential control options in this setting without a viable vaccine as an alternative.

Highlights

  • IntroductionComparisons between abattoirs of the continuous PCA scores for the first 2 components were examined using ANOVA and pairwise comparisons were made using the pairwise.t.test function with a Bonferroni correction in the R statistical environment

  • We identified a number of mycobacterial species dominated by M. bovis from lesions found at slaughter with the exception of 3 isolates from grossly normal lymph nodes

  • We identified a bovid with M. tuberculosis as has been reported in other studies in Ethiopia, Burkina Faso, Nigeria, Zambia, India and Variables Abattoir Sex Dentition Condition

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Summary

Introduction

Comparisons between abattoirs of the continuous PCA scores for the first 2 components were examined using ANOVA and pairwise comparisons were made using the pairwise.t.test function with a Bonferroni correction in the R statistical environment

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