Computational paper-based vertical flow assay for Lyme disease diagnosis (Conference Presentation)

Abstract

We demonstrate a computational paper-based vertical flow assay (VFA) for point-of-care serodiagnosis of Lyme Disease (LD). We leveraged the multiplexed nature of the VFA and functionalized it using different antigen panels specific to LD. The paper-based VFA operation takes <20min, after which a hand-held reader captures an image of the sensing membrane. A deep learning-based algorithm processes the signals from multiple immunoreactions to output a diagnostic decision (i.e., positive/negative). This cost-effective computational VFA platform achieved a sensitivity and a specificity of 90.5% and 87%, respectively, demonstrating its promising potential for point-of-care diagnosis of LD even in resource-limited settings.