Prevalence and Associated Risk Factors of Bovine Tuberculosis in Dairy Cattle Determined by Comparative Intradermal...

Bovine tuberculosis (bTB) caused by Mycobacterium bovis is a major zoonotic disease in West Africa. In Africa, bTB is endemic in cattle with a prevalence ranging from 2% up to 18%. The disease causes significant public health risks due to unpasteurized milk and milk product consumption. In the context of the EU-PRISMA project, which promotes research and innovation for productive, resilient, and healthy agropastoral systems in West Africa, a cross-sectional survey was conducted in dairy herds from Mali and Niger to assess animal, herd, and within-herd bTB prevalence, as well as to identify animal risk factors and predictors of bTB herd status. Method and principal findings: A random cross-sectional survey on dairy cattle farms using comparative intradermal tuberculin test and epidemiological inquiry was performed in four regions of Mali (Bamako, Koulikoro, Mopti, and Sikasso) and three regions of Niger (Tahoua, Dosso, and Tillabéry). Herd and animal prevalence of bTB and within-herd prevalence were significantly higher in Mali (especially in Bamako and Koulikoro) than in Niger. Several risk factors were significantly associated with animals positive to bTB, i.e., the region where animals live, the age range from 3 to 7 years old, and female animals. In addition, in regions with higher bTB prevalence, the herd with slaughtering of animals in the farm and the herd with the presence of an animal assembly area were associated with the most unfavorable status of a herd with regards to bTB. Moreover, the average and the median annual economic losses of bTB at animal level were estimated at €262 and €137 respectively, with large variability depending on the farm (between €46 and €838).

This survey provides useful data on bTB epidemiology and economical losses in Mali and Niger and urges for improvement of surveillance systems and prevention and control strategies. Cost-benefit, return of investment, or similar analyses are strongly recommended to help with decision making.