Abstract:
The Rose Bengal Plate Test (RBPT) and serum agglutination test (SAT) were
conducted to determine the serologic prevalence of brucellosis in horses in the
Khartoum State Sudan. A total of 150 horses that were on stable management system
was sampled. During the period from December 2016 to February 2017. Using cross
sectional study localities State this included Khartoum, Bahri and Omdurman. The
objectives of the study were to determine the prevalence of Brucella antibodies in
horses as well as the distribution of the infection according to the certain risk factors.
The samples collected comprised of 109 males and 41 females from three localities
in Khartoum State Sudan. Sera was screened by Rose Bengal Plate Test (RBPT) and
the positive or week positive such as further processed by serum agglutination test
(SAT) for confirmation. The overall Sero-prevalence of brucellosis in horses was
16.7% by RBPT and 4% by SAT. Source wise Sero-prevalence of brucellosis was
44.7%, 30.7%, and 24.7%, in horses of Khartoum, Bahri and Omdurman
respectively. Gender wise Sero-prevalence in horses was 72.7% males and 27.3%
females. In relation to age, Sero-prevalence was 93.3% adults and 6.7%, young
horses. Prevalence of brucellosis in different breeds of horses was 88% and 12%, in
cross and local breed of horses, respectively. Depending upon the body condition,
the Sero-prevalence was 88.7%, and 11.3% in normal and emaciated body
conditioned horses, respectively. And Sero-prevalence was conducted in horses
according to absent and present the wool sorter this was 78.0% and 22.0%,
respectively. The statistical analysis using are Chi-square Test and Logistic
Regression. Chi-square showed high significant association between disease and
risk factors such as location and gender, and significant association in breed, wool
sorter and body condition. But no significant association between disease and risk
factors in age and contact. The Logistic Regression Test was conducted the all results
significant from Chi square was no significant in the Logistic Regression.
