REVIEW ARTICLE: GLOBAL EVIDENCE OF BOVINE BABESIOSIS

Abstract

Babesiosis is frequent global wide spread tick-borne infection which influence different domestic animals in particular cattle causes global enormous economic loss. The global and local endemic of this disease raising several challenges posed by uncontrolled infection and parasite diversity through various risk factors. Due to availability of these challenges concomitant with limited recent prevalence data of various Babesia species, thus this review investigated recent available data regarding life cycle, prevalence, method of transmission, clinical signs, diagnosis, treatment and control schedules of bovine babesiosis. Also, highlighted the local and global incidence alongside whether it is foe or friend. The causative agent of bovine babesiosis includes B. bovis, B. bigemina and B. divergens; with a typical signs characterized by high body temperature, severe depression, hemoglobinuria, anemia and high mortality. Microscopic examination of blood smear stained with Giemsa dye represents routine applicable technique to confirm the acute infection. However, advanced diagnostic assays such as serological and molecular assays were employed with more reliable data for confirmation of acute and chronic cases. The major risk factors that are participated in global and local endemic and prevalence of the bovine babesiosis are related to availability of ticks, prevention measurement, existence of ticks in specific region, age and breed of animal, type of babesicidal drugs, general sanitary conditions, and nutrition. Other factors include inactive control schedules on vectors (ticks), evolution of parasitic resistance. This review identified that the disease is challenging and affect agriculture sector particularly cattle management field. Thus, specific qualitative studies that focus on of host with parasite and tick relations, parasite metabolism, and the possible ways of surviving Babesia are required. Additionally, specific and precise studies that create predictive measurements of spreading the vector and infection using available regional and epidemiological information are of interest.