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.

Volatile organic compounds (VOCs) are ubiquitous pollutants, and exposure from in utero through childhood may impair neurodevelopment. However, compound-specific risks remain unclear. This systematic review and meta-analysis examined associations between VOC exposure and child neurodevelopmental outcomes. A systematic search of PubMed, Scopus, and Embase was conducted until August 2025, yielding 1213 records. Quality assessment was performed using the Newcastle–Ottawa Scale and risk of bias using the ROBINS-E tool. Pooled odds ratios (ORs) were calculated using random-effects models, with heterogeneity evaluated via I² statistics. Subgroup analyses explored for study design, exposure timing, and country income level. Twenty-eight studies were included in the final analysis. Of the 18 VOCs analyzed, five compounds, propionaldehyde (pooled OR = 1.84; 95% CI 1.19–2.49), styrene (pooled OR = 1.69; 95% CI 1.30–2.21), vinyl chloride (pooled OR = 1.53; 95% CI 1.24–1.89), acrolein (pooled OR = 1.48; 95% CI 1.08–2.04), and trichloroethylene (OR = 1.21; 95% CI 1.04–1.41), demonstrated statistically significant adverse associations with neurodevelopment. Benzene showed borderline significance. Heterogeneity ranged from 0–47%. Subgroup analyses identified significant effect modification for 1,3-butadiene by study design and exposure timing and higher pooled estimates for ethylbenzene in high-income countries.