Systematic review and meta-analysis of human health-related protein markers for realizing real-time wastewater-based epidemiology

Aptamer-based biosensors for wastewater surveillance of influenza virus, SARS-CoV-2, and norovirus: A comprehensive review

Wastewater-based epidemiological (WBE) surveillance has emerged as a crucial tool for monitoring infectious diseases within communities. However, its broader application is frequently constrained by the high costs, labor-intensive processes, and extended timeframes required for sample collection, transportation, and processing. Aptamer-based biosensors offer a promising alternative, leveraging the specific binding properties of aptamers to biomolecules for the on-site and rapid quantification of disease biomarkers in wastewater. This review systematically evaluates recent advancements in the application of aptamer-based biosensors for the detection of key pathogens, including influenza viruses, SARS-CoV-2, and norovirus, within wastewater matrices. The discussion encompasses the technical stability and reliability of signal transmission associated with these biosensors, as well as the current challenges faced in real-world implementation. Noteworthy progress has been made in the development of these biosensors for WBE, achieving detection limits as low as femtomolar (fM) levels in buffer and linear dynamic ranges extending up to five orders of magnitude for viruses such as influenza and SARS-CoV-2. Despite this progress, considerable hurdles remain to be addressed before these technologies can be effectively deployed in practical settings, especially within complex wastewater environments. Key factors affecting detection performance include matrix interference, environmental variability, and the diminished stability of both viral targets and aptamer-target interactions in wastewater. This review not only highlights these challenges but also outlines potential avenues for future research aimed at enhancing the functionality and applicability of aptamer-based biosensors in WBE, ultimately contributing to more effective public health surveillance and disease monitoring strategies.

Advances in Wastewater-Based Epidemiology for Pandemic Surveillance: Methodological Frameworks and Future Perspectives

Wastewater-based epidemiology (WBE) has emerged as a transformative approach for community-level health monitoring, particularly during the COVID-19 pandemic. This review critically examines the methodological framework of WBE systems through the following three core components: (1) sampling strategies that address spatial-temporal variability in wastewater systems, (2) comparative performance of different platforms in pathogen detection, and (3) predictive modeling integrating machine learning approaches. We systematically analyze how these components collectively overcome the limitations of conventional surveillance methods through early outbreak detection, asymptomatic case identification, and population-level trend monitoring. While highlighting technical breakthroughs in viral concentration methods and variant tracking through sequencing, the review also identifies persistent challenges, including data standardization, cost-effectiveness concerns in resource-limited settings, and ethical considerations in public health surveillance. Drawing insights from global implementation cases, we propose recommendations for optimizing each operational phase and discuss emerging applications beyond pandemic response. This review highlights WBE as an indispensable tool for modern public health, whose methodological refinements and cross-disciplinary integration are critical for transforming pandemic surveillance from reactive containment to proactive population health management.

Identification of protein biomarkers in wastewater linked to the incidence of COVID-19

Wastewater-based epidemiological (WBE) surveillance is a viable disease surveillance technique capable of monitoring the spread of infectious disease agents in sewershed communities. In addition to detecting viral genomes in wastewater, WBE surveillance can identify other endogenous biomarkers that are significantly elevated and excreted in the saliva, urine, and/or stool of infected individuals. Human protein biomarkers allow the realization of real-time WBE surveillance using highly sensitive biosensors. In this study, we analyzed endogenous protein biomarkers present in wastewater influent through liquid chromatography-tandem mass spectrophotometry and scaffold data-independent acquisition to identify candidate target protein biomarkers for WBE surveillance of SARS-CoV-2. We found that out of the 1382 proteins observed in the wastewater samples, 44 were human proteins associated with infectious diseases. These included immune response substances such as immunoglobulins, cytokine-chemokines, and complements, as well as proteins belonging to antimicrobial and antiviral groups. A significant correlation was observed between the intensity of human infectious disease-related protein biomarkers in wastewater and COVID-19 case numbers. Real-time WBE surveillance using biosensors targeting immune response proteins, such as antibodies or immunoglobulins, in wastewater holds promise for expediting the implementation of relevant policies for the effective prevention of infectious diseases in the near future.