The re-emergence of Monkeypox virus (MPXV) underscores the critical imperative for rapid and deployable diagnostic methods to support effective surveillance and outbreak response. In this study, two recombinase polymerase amplification (RPA)-based assays were developed for MPXV detection by integrating RPA with fluorescence monitoring or lateral flow biosensor (LFB) readouts, referred to as the fluorescent RPA-MPXV and LFB-RPA-MPXV assays, respectively. Both assays were performed under isothermal conditions at 39 °C and efficiently executed within 20 min. The fluorescent RPA-MPXV assay enabled detection via real-time fluorescence monitoring or blue-light–assisted end-point visualization, whereas the LFB-RPA-MPXV assay allowed for instrument-free detection using immunochromatographic strips. Analytical evaluation demonstrated exceptional sensitivity, with a limit of detection of 14 copies using plasmid templates, and uncompromising specificity, as no cross-reactivity was observed against 28 non-MPXV pathogens. Diagnostic applicability was further assessed using simulated clinical specimens, including skin swabs, sputum, and plasma spiked with pseudotyped MPXV. Consistent detection was achieved at concentrations as low as 45 copies across all tested matrices, and all negative controls remained negative, indicating negligible matrix interference and highly stable assay performance. Overall, the fluorescent RPA-MPXV and LFB-RPA-MPXV assays provide rapid and versatile diagnostic tools that complement existing molecular detection methods and support point-of-care testing and field-oriented MPXV surveillance, particularly in settings with limited laboratory infrastructure. • Two complementary RPA-based assays were developed for rapid MPXV detection • Isothermal amplification enabled results within 20 min at 39 °C • Dual readout formats support fluorescence monitoring and LFB-based detection • The assays achieved a detection limit of 14 copies with high analytical specificity • Robust performance was validated across simulated clinical specimen matrices
Li et al. (2026) studied this question.