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Seroprevalence and molecular detection of Brucella infection in livestock in the United Arab Emirates.

Gobena AmeniAboma ZewudeBerecha BayissaIbrahim Abdallah AlfakiAbdallah A AlbizrehNaeema AlhosaniKhaja MohteshamuddinBerhanu Adenew DegefaMohamed Elfatih HamadMeera Saeed AlkalbaniMohamed Moustafa AbdelhalimAssem Sobhi AbdelazimRafeek Aroul KoliyanKaltham KayafMervat Mari Al NuaimatRobert BarigyeArve Lee WillinghamMarkos TibboBedaso Mammo EdoTeshale SoriYassir Mohammed Eltahir
Published in: International journal of veterinary science and medicine (2024)
Small ruminants and camels are important livestock species in the United Arab Emirates (UAE), although Brucella infection can limit their productivity. This study aimed to investigate the seroprevalence of Brucella infection and its associated risk factors in small ruminants and camels in the Emirate of Abu Dhabi. Additionally, seropositive animals were tested for the DNA of Brucella . Multispecies competitive enzyme-linked immunosorbent assay (c-ELISA) and multispecies indirect (i-ELISA) were used to test 3,086 animals from 2022 to 2023. Brucella cell surface 31 kDa protein (bcsp31) gene-based real-time polymerase chain reaction (q-PCR) was used to detect Brucella DNA. Multivariate logistic regression was used to assess the association between seroprevalence and potential risk factors. The overall seroprevalences of Brucella infection were 1.7% (95% confidence interval [CI], 1.2%-2.2%) and 5.8% (95% CI, 5.0%-6.7%) based on serial and parallel testing, respectively. The DNA of Brucella was detected in 13 of the 51 seropositive animals. The overall seroprevalence of Brucella infection was associated with the region, type of animal holding, species, and age of the animals. In conclusion, this study documented Brucella infection in small ruminants and camels in the Emirate of Abu Dhabi, warranting necessary intervention strategies to eliminate Brucella infections in livestock populations.
Keyphrases
  • risk factors
  • circulating tumor
  • cell surface
  • genome wide
  • high throughput
  • climate change