Diagnostics for Hemorrhagic Fever Viruses: Lassa Fever as an Example

Abstract Lassa virus (LASV) causes severe hemorrhagic fever across West Africa where the development of rapid, accurate diagnostics remains hindered by the extensive lineage-level genetic diversity and by the limited availability of high-level containment laboratories. We developed a LASV assay using the CRISPR-based Streamlined Highlighting of Infections to Navigate Epidemics (SHINE) platform to enable safe, field-deployable detection. To enable assay development without handling live virus, we established a plasmid-based system that generates LASV RNA controls spanning major viral lineages. Using these surrogate plasmids, we optimized the assay for 32 genetically distinct LASV isolates, demonstrating detection across major lineage subdivisions with lineage-dependent sensitivity. The assay maintained sensitivity in serum and whole blood, and was further evaluated using clinical samples in Nigeria. To reduce subjectivity in strip interpretation, we developed supervised machine-learning models for automated classification of lateral flow results. Together, this integrated diagnostic framework supports field-oriented detection of genetically diverse LASV and provides a broader approach for diagnostic development for high-consequence RNA viruses.