Enterovirus D68 in United States wastewater: a longitudinal surveillance study integrating climatic, demographic, and clinical data.

Abstract

Enterovirus D68 (EV-D68) can cause severe respiratory illness and acute flaccid myelitis (AFM), but limited clinical testing and sparse surveillance data hinder the ability to address epidemiological questions about its circulation. This study aimed to characterize EV-D68 seasonality across the U.S. using wastewater data, evaluate the influence of climatic and sociodemographic factors, and compare trends with symptom-based clinical indicators. We analyzed 43,876 samples collected from 147 wastewater treatment plants across 40 U.S. states between July 2023 and July 2025 to quantify EV-D68 RNA in wastewater solids and estimate the seasonal peak and season duration. We evaluated climatic and sociodemographic drivers of variation and compared wastewater trends with symptom-based clinical diagnoses for AFM, wheezing, and enterovirus retrieved from Epic Cosmos, a nationwide electronic health record-based research network, representing 4.5 billion encounters during the same study period. We observed a biennial EV-D68 pattern with a national peak in September 2024 and an extended 20-month period of detection in California. Seasonal peaks occurred 28-31 days earlier in regions with 5 °C higher temperatures or dew points. Season duration was longer by 7-11 weeks in dense, urban catchments with more childcare facilities, crowded households, hospitals, and nursing homes. Wastewater concentrations correlated positively with enterovirus diagnoses (Spearman ρ = 0.34, p = 0.01) and negatively with wheezing in adults ≥65 years (ρ = -0.49, p < 0.0001). Wastewater surveillance can generate epidemiological metrics for EV-D68 without clinical surveillance data, identify where and when activity increases, and reveal the environmental and demographic factors driving these patterns. Wastewater surveillance offers high-resolution data for pathogens with diagnostic testing constraints and provides information that can strengthen epidemiological modeling and support preparedness for future disease waves. Sergey Brin Family Foundation.