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Traditional influenza surveillance informs control strategies but can lag behind outbreak onset and undercount cases. Wastewater surveillance is effective for monitoring near real-time dynamics of outbreaks but has not been attempted for influenza. We quantified influenza A virus (IAV) RNA in wastewater during two active outbreaks on university campuses in different parts of the United States and during different times of year using case data from an outbreak investigation and high-quality surveillance data from student athletes. In both cases, the IAV RNA concentrations were strongly associated with reported IAV incidence rates (Kendall's τ values of 0.58 and 0.67 for the University of Michigan and Stanford University, respectively). Furthermore, the RNA concentrations reflected outbreak patterns and magnitudes. For the University of Michigan outbreak, evidence from sequencing IAV RNA from wastewater indicated the same circulating strain identified in cases during the outbreak. The results demonstrate that wastewater surveillance can effectively detect influenza outbreaks and will therefore be a valuable supplement to traditional forms of influenza surveillance.

Wastewater-based epidemiology (WBE) uses concentrations of infectious agent targets in wastewater to infer infection trends in the contributing community. To date, WBE has been used to gain insight into infection trends of gastrointestinal diseases, but its application to respiratory diseases has been limited. Here, we report that respiratory syncytial virus (RSV) genomic ribonucleic acid can be detected in wastewater settled solids at two publicly owned treatment works. We further show that its concentration in settled solids is strongly associated (Kendalls tau = 0.65–0.77, p < 10–7) with clinical positivity rates for RSV at sentinel laboratories across the state in 2021, a year with anomalous seasonal trends of RSV disease. Given that RSV infections have similar clinical presentations to COVID-19, can be life threatening for some, and immunoprophylaxis distribution for vulnerable people is based on outbreak identification, WBE represents an important tool to augment current RSV surveillance and public health response efforts.

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The effective reproductive number, Re, is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a single infectious person through time. To date, Re estimates are based on clinical data such as observed cases, hospitalizations, and/or deaths. Here we show that the dynamics of SARS-CoV-2 RNA in wastewater can be used to estimate Re in near real-time, independent of clinical data and without associated biases stemming from clinical testing and reporting strategies. The method to estimate Re from wastewater is robust and applicable to data from different countries and wastewater matrices. The resulting estimates are as similar to the Re estimates from case report data as Re estimates based on observed cases, hospitalizations, and deaths are among each other. We further provide details on the effect of sampling frequency and the shedding load distribution on the ability to infer Re. To our knowledge, this is the first time Re has been estimated from wastewater. This method provides a low cost, rapid, and independent way to inform SARS-CoV-2 monitoring during the ongoing pandemic and is applicable to future wastewater-based epidemiology targeting other pathogens.

Background: Respiratory disease is a major cause of morbidity and mortality; however, current surveillance for circulating respiratory viruses is passive and biased. Seasonal circulation of respiratory viruses changed dramatically during the COVID-19 pandemic. More active methods for understanding respiratory disease dynamics are needed to better inform public health response and to guide clinical decision making. Wastewater-based epidemiology has been used to understand COVID-19, influenza A, and RSV infection rates at a community level, but has not been used to investigate other respiratory viruses. Methods: We measured concentrations of influenza A and B, RSV A and B, human parainfluenza (1-4), rhinovirus, seasonal human coronaviruses, and human metapneumovirus RNA in wastewater solids three times per week for 17 months spanning the COVID-19 pandemic at a wastewater treatment plant in California, USA. Novel probe-based assays were developed and validated for non-influenza viral targets. We compared viral concentrations to positivity rates for viral infections from clinical specimens submitted to sentinel laboratories. Findings: We detected RNA from all target viruses in wastewater solids. Human rhinovirus and seasonal coronaviruses were found at highest concentrations. Concentrations of viruses correlated significantly and positively with positivity rates of associated viral diseases from sentinel laboratories. Measurements from wastewater indicated limited circulation of RSV A and influenza B, and human coronavirus OC43 dominated the seasonal human coronavirus infections while human parainfluenza 1 and 4A dominated among parainfluenza infections. Interpretation: Wastewater-based epidemiology can be used to obtain information on circulation of respiratory viruses at a community level without the need to test many individuals because a single sample of wastewater represents the entire contributing community. Results from wastewater can be available within 24 hours of sample collection, allowing real time information to inform public health response, clinical decision making, and individual behavior modifications.

We measured concentrations of SARS-CoV-2, influenza A and B virus, respiratory syncytial virus (RSV), mpox virus, human metapneumovirus, norovirus GII, and pepper mild mottle virus nucleic acids in wastewater solids at twelve wastewater treatment plants in Central California, USA. Measurements were made daily for up to two years, depending on the wastewater treatment plant. Measurements were made using digital droplet (reverse-transcription–) polymerase chain reaction (RT-PCR) following best practices for making environmental molecular biology measurements. These data can be used to better understand disease occurrence in communities contributing to the wastewater.