CRISPR-enabled point-of-care diagnostics for SARS-CoV-2 variant surveillance: design principles for adapting molecular detection to viral evolution

The continual evolution of pathogens such as SARS-CoV-2 exposes a fundamental limitation of static molecular diagnostics, where fixed primer probe designs are vulnerable to single-nucleotide variation and recombination. This review critically examines CRISPR-enabled point-of-care diagnostics as programmable analytical systems capable of maintaining diagnostic performance under viral evolutionary pressure. Rather than providing a comprehensive survey of platforms, we focus on design principles that govern variant-resilient detection, including guide RNA (gRNA) mismatch engineering, target redundancy, multiplexed architectures, and workflow-constrained assay chemistry. We analyse how amplification-free CRISPR strategies reduce operational complexity while introducing new trade-offs in sensitivity, robustness, and deployability. Emerging and orthogonal CRISPR effectors are evaluated in terms of their practical value for point-of-care testing, distinguishing translationally viable approaches from proof-of-concept demonstrations. By aligning molecular detection strategies with SARS-CoV-2 evolutionary dynamics, this review provides a critical framework for designing adaptable diagnostics that can evolve alongside rapidly changing pathogens.