Sensors and biosensors for leptospirosis diagnostics: a scientific and technological review

Leptospirosis causes more than one million human cases annually, yet effective, accessible, and field-deployable diagnostic tools are still limited. Biosensors have emerged as promising alternatives or complementary tools to conventional methods. This review summarizes the current scientific and technological landscape of sensors and biosensors developed for leptospirosis diagnosis or pathogenic Leptospira detection. The search strategy, conducted in March 2026, included PubMed, Web of Science, Scopus, Espacenet, WIPO, and INPI, and aimed to identify scientific articles and patent documents related to sensors, biosensors, rapid tests, and point-of-care technologies for Leptospira spp. detection. Eligible documents written in English or Portuguese were independently screened by pairs of reviewers, with disagreements resolved by a third reviewer. The 47 selected studies and 7 patent documents described a broad range of technologies, differing in transducer, bioreceptor, analyte, detection format, and validation. Electrochemical and optical biosensors were the most frequently reported approaches, often showing low limits of detection and potential for miniaturization and portability. Paper-based platforms and molecularly integrated devices were also identified, offering advantages for point-of-care use and sensitivity enhancement. However, most technologies remain at an early stage of development, with limited validation using clinical, animal, or environmental samples. Methodological heterogeneity, incomplete reporting of performance parameters, and the lack of harmonized comparisons between direct and indirect detection strategies hamper objective assessment of diagnostic utility. Overall, available sensor-based technologies show substantial promise for leptospirosis diagnostics, but further validation, standardization, usability assessment, and investment are required to advance these platforms toward higher technology readiness and real-world implementation.