Wastewater Epidemiology: Predicting COVID-19 Surges Through Sewage

Wastewater surveillance has proven to be a powerful predictive tool for monitoring and forecasting COVID-19 hospitalizations, with wastewater data accurately preceding increases in hospitalizations by 1-4 weeks, allowing public health officials to anticipate and prepare for surges before they become apparent through clinical data.

This segment covers US hospitalization data and wastewater virus monitoring. New York State reports 292 COVID hospitalizations with an upward trend line, 363 positive tests on November 25th. Wastewater surveillance reveals regional patterns: Stamford, Connecticut shows RSV high with upward trend, norovirus high with upward trend, and influenza A low but increasing. San Francisco area shows moderate influenza A with upward trend. North Miami reveals RSV high with upward trend, influenza A high and increasing, and norovirus medium. Ann Arbor, Michigan shows influenza A medium with slight decrease, influenza B with detections and upward trend. These wastewater data points provide early warning of community transmission before clinical cases are reported.

Studies in multiple Japanese cities showed wastewater virus concentration patterns closely match clinical infection patterns, with increases in infection numbers corresponding to proportional increases in wastewater concentrations. Research determined that wastewater surveillance can reliably detect infections when there is approximately one new infection per 100,000 people per day. At this threshold, 95% or more of wastewater samples will test positive. Researchers developed a mathematical model to estimate infection numbers from wastewater virus concentrations, assuming virus amount equals the product of infected individuals, virus shedding rate per person, and shedding duration. Research determined infected individuals shed virus for approximately 25 days, with highest concentration in the first few days. The model was validated by comparing estimated values with actual clinical reports, showing good agreement. By sequencing genetic material from wastewater samples, researchers can identify specific virus variants and track how variants change over time.

Analysis of San Diego County wastewater data showed strong correlation with clinical case reports, with wastewater signals appearing 5-6 days earlier due to continued viral shedding before testing and diagnostic delays. A predictive model combining wastewater data, day-of-week factors, and new case counts accurately predicted case trends at least one week into the future, providing public health with approximately seven days advance warning for intervention planning.

This concluding section explores advanced applications and unresolved challenges in wastewater surveillance. For small populations (hospitals, dorms, correctional facilities), deterministic ODE models fail to capture stochastic effects; Markov chain formulations with analytical solutions for mean trajectories and covariances properly account for probabilistic transmission. Joint analysis of wastewater and hospitalization data improves forecasting by leveraging complementary strengths, though this requires introducing time-varying hospitalization probabilities to correct for infectious compartment biases. A major limitation is identified: current models cannot properly capture complex viral shedding profiles showing increased shedding around day 2-3 followed by decline over subsequent days with RNA persistence for 30+ days. The section concludes by emphasizing that wastewater utility depends critically on modeling frameworks and epidemic contexts—it may improve forecasts in some situations while worsening them in others. Despite limitations, wastewater offers significant cost advantages as extreme pool testing, making it valuable for resource-limited settings.

Critics of wastewater drug testing argue that when police obtain the information, it can be used to punish people rather than help them. Beyond the tension between public health and law enforcement, some private employers are considering testing office buildings for drug use. Legal experts state that wastewater searches are almost certainly legal, based on a 1980s Supreme Court ruling that people abandon privacy claims to trash placed on curbs, by extension, no warrant is needed to check what is flushed down toilets.

Ethical considerations in wastewater surveillance differ from human research because sewage contains fecal material from multiple individuals without individual identification. Dutch researchers obtained official confirmation that wastewater surveillance does not require ethical approval under Dutch law for medical scientific research on people. However, ethical considerations arise when monitoring smaller locations like schools, nursing homes, and hospitals where wastewater signals might indicate specific facility-level issues. Communication strategies must balance transparency with avoiding unnecessary public alarm.

Wastewater surveillance raises important ethical and privacy concerns. While monitoring at treatment plants averages conditions for large populations, sampling from specific locations like apartment complexes, schools, or office buildings could enable identification of particular groups. Potential misuse includes law enforcement deploying resources to neighborhoods showing drug-related indicators, or utility providers selling wastewater data to private companies for research or advertising purposes. These concerns highlight the need for careful consideration of how wastewater data might be used beyond public health monitoring.

As wastewater surveillance expands to more granular levels (such as building-level sampling), important ethical and legal issues emerge regarding privacy and potential misuse. Current approaches maintain anonymity since wastewater represents pooled community samples from thousands of individuals. However, if samplers are placed outside individual residences or congregate facilities, questions arise about surveillance capabilities and potential for misuse. These conversations need to accompany the rapid expansion of wastewater monitoring programs.

Sewer surveillance involves monitoring municipal wastewater to catch criminals and identify diseases, with the technology being justified and piloted during the COVID-19 pandemic to make it acceptable to the general public. In Missouri, a December 2025 program allowed local education agencies to participate in voluntary wastewater sampling to identify illicit drugs, with more than 40 LEAs participating. The program detected alarming levels of dangerous drugs including fentanyl, which is 4,300 times stronger than morphine. This represents a significant expansion of surveillance technology into educational settings, raising important questions about privacy, consent, and the balance between public safety and individual rights.

Expanding wastewater surveillance beyond SARS-CoV-2 requires systematic prioritization guided by four key questions: (1) Are there actionable public health interventions at the community level? (2) Does the pathogen shed into wastewater in detectable amounts? (3) Can clinical assays be adapted for wastewater analysis? (4) What is the case distribution and timing of clinical diagnosis? For antimicrobial resistance, wastewater surveillance is particularly valuable because most carriers never receive clinical diagnosis. The NWSS expansion strategy includes normalization controls (pepper mild mottle virus, crAss phage, bovine coronavirus), antimicrobial resistance genes, respiratory panel (influenza A/B, RSV), foodborne panel (adenovirus, norovirus, toxigenic E. coli, Campylobacter), and emerging infections (mpox, Candida auris). Implementation through Centers of Excellence aims for early 2024 rollout, with corresponding dashboard visualizations developed for each target type. This strategic framework ensures resources address the most meaningful public health questions while adapting to evolving scientific understanding.

Wastewater-based epidemiology (WBE) uses urban wastewater as a 'treasure chest' containing human metabolic products reflecting lifestyle, diet, health, and disease patterns. The WHO defines environmental health as addressing external factors affecting human wellbeing. WBE originated in the 1930s with polio surveillance, gained WHO recognition in 2003, and expanded to drug monitoring. The SCORE Network (2010) harmonized protocols, enabling early warning systems during the COVID-19 pandemic. Key applications include: public health surveillance (over 70 countries now use it for disease outbreak detection), drug enforcement (China's 2018 program dismantled dozens of clandestine labs), industrial monitoring (tracking persistent pollutants like PFAS), and AMR surveillance through the One Health approach linking human, animal, and environmental health.

La vigilancia epidemiológica basada en aguas residuales (WBE) es una herramienta complementaria que permite detectar brotes de enfermedades infecciosas semanas antes que los sistemas convencionales, al analizar biomarcadores excretados por toda la población en las aguas residuales, lo que ofrece ventajas como alerta temprana, independencia del sistema médico y mayor sensibilidad para identificar tendencias de enfermedades, resistencia antimicrobiana y emergencias sanitarias.

Wastewater-based epidemiology serves as an effective, cost-efficient method for monitoring antimicrobial resistance patterns in communities, as demonstrated by a study showing that 15.1% of Grenadian municipal wastewater samples and 52.9% of clinical UTI isolates exhibited antibiotic resistance, with ampicillin showing the highest resistance rates and nitrofurantoine the lowest; this approach bridges environmental and clinical data to inform public health decisions and guide treatment strategies in resource-limited settings.

Wastewater-based epidemiology (WBE) uses digital PCR technology to detect pathogens in wastewater, enabling public health surveillance by monitoring what enters treatment plants before contaminants reach the environment; this approach allows for early detection of seasonal pathogens like influenza and norovirus, and was particularly valuable during the COVID-19 pandemic for tracking disease spread at the community level.