EV-A71 is a common viral pathogen that causes hand, foot and mouth disease. It is a single-stranded RNA virus that has a low fidelity RNA polymerase and, as a result, spontaneous mutations frequently occur in the EV-A71 genome. The mutations within the genome give rise to quasispecies within the viral population that could be further defined by haplotypes. In vitro virulence of EV-A71 was shown by plaque size in Rhabdomyosarcoma (RD) cells, which was substantiated by in vitro characterizations of growth, RNA replication, binding, attachment and host cell internalization. Viruses could exhibit different host cell adaptations in different cell lines during viral passaging. The EV-A71/WT (derived from EV-A71 subgenotype B4) was shown to comprise six haplotypes through next-generation sequencing, where only EV-A71/Hap2 was found to be cultivable in RD cells, while EV-A71/Hap4 was the only cultivable haplotype in Vero cells. The EV-A71/WT produced plaques of four different sizes (small, medium, big, huge) in RD cells, while only two plaque variants (small, medium) were present in Vero cells. The small plaque variant isolated from RD cells displayed lower RNA replication rates, slower in vitro growth kinetics, higher TCID₅₀ and lower attachment, binding and entry ability when compared against EV-A71/WT due to the mutation at 3D-S228P that disrupted the active site of the RNA polymerase, resulting in low replication and growth of the variant.

Background: Wastewater-based surveillance (WBS) has emerged as a valuable tool for population-level monitoring of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) transmission, yet the interplay between sampling strategies and disease prevalence in shaping detection performance remains ambiguous. We investigated how grab and composite sampling influence SARS-CoV-2 ribonucleic acid (RNA) detection dynamics and predictive lag times across high- and low-prevalence communities in Selangor, Malaysia. Methods: A 28-week longitudinal study was conducted in Selangor, Malaysia, comparing grab and composite wastewater sampling in communities with high and low Coronavirus disease 2019 (COVID-19) prevalence. SARS-CoV-2 RNA in 348 samples was quantified using digital Reverse Transcription Polymerase Chain Reaction (RT-dPCR), and viral lineages were characterized by Nanopore sequencing. Detection sensitivity and lead times relative to reported cases were evaluated. Results: In low-prevalence settings, grab sampling showed higher detection sensitivity than composite sampling (92.0% vs. 70.0%), whereas both methods achieved similarly high detection in high-prevalence areas (>97.0%). Lag-time analysis indicated that grab sampling in high-prevalence settings was significantly associated with case trends at potential two-week lead (p = 0.024), while composite sampling in low-prevalence settings showed the strongest association at a potential one-week lead (p = 0.0022). Overall, lag structures varied by both sampling strategy and prevalence context. Both sampling approaches captured the replacement of Omicron sublineages (XBB.1.5, XBB.1.9.1, XBB.1.16) and identified additional circulating variants, including EG.5, that were not captured in the available clinical sequencing dataset during the same period. Conclusions: These findings reveal that local transmission intensity is associated with the utility of different sampling designs. Context-specific optimization of WBS sampling strategies enhances sensitivity, reduces detection lag, and strengthens early warning and genomic-tracking capacity in public health surveillance frameworks.