Abstract

This study evaluated the resistance status of Haemonchus contortus from sheep flocks in the state of São Paulo, Brazil, through comparison between the fecal egg count reduction test (FECRT) and the larval development test (LDT). For the FECRT, 35 sheep were selected in each of five flocks and divided into groups treated with: benzimidazole, levamisole, ivermectin, monepantel and control. Feces were collected for EPG and fecal cultures. The LDT was performed using thiabendazole (TBZ), levamisole (LEV), ivermectin aglycone (IVM-A) and Zolvix (ZLV). Resistance to all drugs was detected using FECRT in 100% of the flocks, except in relation to ZLV (40% resistant and 20% suspected of resistance). LDT indicated resistance to TBZ and IVM-A in all flocks, to LEV in 80% of flocks and to ZLV in 10%. Total agreement was obtained between the two tests for TBZ and IVM (k = 1.0), while for LEV (k = 0.8) and ZLV (k = 0.9), substantial and almost perfect agreement were obtained, respectively. The concordance between the tests was significant, thus showing that it is possible to use the outcome of the LDT to predict the FECRT, and hence validating the former as a fast diagnostic test for use by sheep farmers in Brazil.

Highlights

  • Helminthiasis in small ruminants is aggravated by high levels of parasite resistance

  • The present study indicated that a good association existed between fecal egg count reduction test (FECRT) and larval development test (LDT) with regard to detection of H. contortus resistant to benzimidazoles and TBZ

  • The data from the present study indicated that H. contortus had a multiple-resistance profile in the flocks evaluated

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Summary

Introduction

Helminthiasis in small ruminants is aggravated by high levels of parasite resistance. This is the current scenario in almost all countries in the world in which sheep farming is present (Kaplan & Vidyashankar, 2012). Many advances in investigating resistance have been achieved over the past 50 years, including in relation to diagnostics, important physiological and genetic discoveries and the development of predictive mathematical models and tools to help farmers to manage resistance (Kotze et al, 2014). This challenge has only been partially overcome. One key issue that still needs to be resolved is to develop faster and easier diagnostic techniques for estimating the presence of anthelmintic resistance that can be used by farmers

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