Small ruminant pasteurellosis in Tigray region, Ethiopia: marked serotype diversity may affect vaccine efficacy

Abstract

The aim of this study was to investigate the prevalent Bibersteinia, Mannheimia and Pasteurella serotypes, risk factors and degree of serotype co-infections in sheep and goats in the Tigray region of Ethiopia. Serum was collected from 384 sheep and goats from the Tanqua-Abergelle district of Tigray region using cross-sectional random sampling. An indirect haemagglutination test was used for serotyping. Risk factors for infections were evaluated by logistic regression. Potential clustering of multiple serotypes within individual animals due to common risk factors was evaluated by redundancy analysis. Eight serotypes were identified: all studied animals were serologically positive for at least one serotype. Overall, 355 (92·45%) of the animals were infected by four or more serotypes. Of the five risk factors studied, peasant association (PA), animal species, age (serotype A1), and bodyweight (serotype T15) were significantly associated with infection, but sex was not significant. Only PA explained a significant proportion of the variation (adjusted R 2 = 0·16) in the serological responses. After the effect of PA was accounted for, T3 and T4; A7 and Pasteurella multocida A; and A7 and T10 were positively correlated for co-infection, while T4 and T10 were less likely to be found within the same animal. Diverse serotypes were circulating in the Tigray region and could be a challenge in selecting serotypes for vaccine.

Keywords: B. trehalosi; M. haemolytica; P. multocida; Co-infection; serotype diversity.

Fig. 1.

Mannheimia, Pasteurella and Bibersteinia serotype co-infections analysed for potential of clustering in sheep and goats in different peasant associations (PAs). Triplots of the three significant redundancy analysis (RDA) axes, showing relationships between explanatory and response variables. Solid lines represent serological responses, dashed lines represent PAs. Angles between variables represent their correlations.