Mapping the Global Distribution of Babesia Infections.

Area of Science:

• Veterinary Parasitology
• Infectious Diseases
• Ecological Epidemiology

Background:

• Babesiosis poses a significant global health and economic burden.
• Understanding Babesia species' ecological niches and disease prevalence is crucial for control.

Purpose of the Study:

• To systematically review the global distribution of Babesia species.
• To identify key ecological and vector-associated factors influencing Babesia distributions.
• To assess the human disease burden of Babesiosis.

Main Methods:

• Systematic literature review of Babesia species distribution.
• Analysis of host-parasite and vector-parasite associations.
• Machine learning models to predict geographic ranges and identify transmission drivers.
• Quantification of human babesiosis cases.

Main Results:

• Documented 250 Babesia species across 73 vectors, 224 animals, and humans.
• Babesia microti and Babesia duncani account for >90% of 26,848 human cases.
• Babesia caballi infected the most tick species; Babesia microti showed highest wildlife prevalence.
• Machine learning models identified habitat suitability index (HSI) of ticks as the primary driver of Babesia transmission risk.
• Babesia bovis predicted to have the most extensive geographic range.

Conclusions:

• Babesiosis is a widespread zoonotic disease with diverse hosts and vectors.
• Targeted surveillance and enhanced diagnostic capacity are needed in high-risk areas.
• Tick HSI is a critical factor for predicting Babesia transmission risk.