Epidemiology and Diagnostics of Leptospirosis

Leptospirosis is a globally important zoonotic disease caused by spirochaetes of the genus Leptospira. Transmission occurs through contact with the urine of infected animals or contaminated water and soil, placing rural subsistence farmers, urban slum dwellers and those involved in water‐based recreation at greatest risk. Recent trends reveal a rise in reported cases in temperate regions, with substantial heterogeneity in incidence between and within countries. Reservoir hosts include rodents, livestock and companion animals, while environmental factors such as flooding, poor sanitation and urban crowding drive transmission. Clinical diagnosis is challenging because early symptoms are non‐specific and overlap with other febrile illnesses. Conventional laboratory methods include culture, the microscopic agglutination test and polymerase chain reaction, but each has limitations in sensitivity, specificity or timeliness. Emerging approaches span molecular typing, high‐throughput sequencing and machine learning–based imaging to improve detection of infection, discriminate pathogenic species and guide public health interventions. A One Health perspective integrating human, animal and environmental surveillance is vital for accurate burden estimation and targeted control strategies.

Research from Nature Portfolio

A novel machine learning–based image analysis method has been developed to track the motility of individual Leptospira interrogans cells without the need for fluorescent labelling. By analysing label-free microscopic video data, researchers demonstrated that strains associated with severe disease exhibit faster surface motility and reduced adherence to kidney cells compared with less virulent counterparts. The approach enables rapid phenotypic characterisation of field isolates, offering potential as a complementary diagnostic tool to assess virulence phenotypes and inform risk profiling in clinical and environmental samples.

Epidemiology and Diagnostics of Leptospirosis publication trend

The graph below shows the total number of articles in epidemiology and diagnostics of leptospirosis across all publications each year (not limited to Nature Index journals).

Technical terms

Serovar: A distinct variation within a Leptospira species defined by antigenic differences in surface lipopolysaccharides.

Biofilm: A structured community of bacteria enclosed in an extracellular matrix and adherent to surfaces, enhancing environmental survival.

Transcriptome: The complete set of RNA transcripts produced by an organism or a specific cell population under defined conditions.

Phylogeny: The evolutionary history and relationships among Leptospira species, often inferred from genomic sequence data.

Label-free motion tracking: A computational imaging technique to monitor bacterial movement without fluorescent markers, enabling phenotypic assessment.

References

1. Machine learning-based motion tracking reveals an inverse correlation between adhesivity and surface motility of the leptospirosis spirochete. Nature Communications (2023).
2. Leptospira interrogans biofilm transcriptome highlights adaption to starvation and general stress while maintaining virulence. npj Biofilms and Microbiomes (2024).
3. Epidemiology of reported cases of leptospirosis in the EU/EEA, 2010 to 2021. Eurosurveillance (2024).
4. Revisiting the taxonomy and evolution of pathogenicity of the genus Leptospira through the prism of genomics. PLOS Neglected Tropical Diseases (2019).