Abstract
Understanding the ecological niches and quantifying the disease burden of Babesia species is essential for efficient surveillance and control strategies. Through a systematic review of global distributions, we document all 250 identified Babesia species across 73 vector species, 224 animals, and humans. Babesia caballi infected the broadest range of tick species, while Babesia microti exhibited the highest prevalence in wildlife. Among 26 848 recorded human cases involving 10 Babesia species, >90% were attributed to Babesia microti and Babesia duncani. Using three machine learning algorithms, we evaluated ecological and vector-associated determinants governing the distributions of six predominant Babesia species. Our models predict B. bovis to have the most extensive geographic range. Critically, habitat suitability index (HSI) of vector ticks emerged as the primary driver of Babesia transmission risk. Enhanced awareness, diagnostic capacity, and surveillance are imperative in identified high-risk regions.