Wu, F. et al. SARS-CoV-2 RNA concentrations in wastewater foreshadow dynamics and clinical presentation of new COVID−19 cases. Sci. Total Environ. 805, 150121 (2022).
Mattei, M., Pintó, R. M., Guix, S., Bosch, A. & Arenas, A. Analysis of SARS-CoV-2 in wastewater for prevalence estimation and investigating clinical diagnostic test biases. Water Res. 242, 120223 (2023).
Ai, Y. et al. Wastewater SARS-CoV-2 monitoring as a community-level COVID−19 trend tracker and variants in Ohio, United States. Sci. Total Environ. 801, 149757 (2021).
Xiao, A. et al. Metrics to relate COVID−19 wastewater data to clinical testing dynamics. Water Res. 212, 118070 (2022).
Kilaru, P. et al. Wastewater surveillance for infectious disease: a systematic review. Am. J. Epidemiol. 192, 305–322 (2023).
Varkila, M. R. J. et al. Use of wastewater metrics to track COVID-19 in the US. JAMA Netw. Open 6, e2325591 (2023).
Gitter, A. et al. Not a waste: wastewater surveillance to enhance public health. Front. Chem. Eng. 4, 1112876 (2023).
Peccia, J. et al. Measurement of SARS-CoV-2 RNA in wastewater tracks community infection dynamics. Nat. Biotechnol. 38, 1164–1167 (2020).
Chen, C. et al. Wastewater-based epidemiology for COVID-19 surveillance and beyond: a survey. Epidemics 49, 100793 (2024).
Phan, T. et al. Making waves: Integrating wastewater surveillance with dynamic modeling to track and predict viral outbreaks. Water Res. 243, 120372 (2023).
Killingley, B. et al. Safety, tolerability and viral kinetics during SARS-CoV-2 human challenge in young adults. Nat. Med. 28, 1031–1041 (2022).
Gunawardana, M. et al. Early SARS-CoV-2 dynamics and immune responses in unvaccinated participants of an intensely sampled longitudinal surveillance study. Commun. Med. 2, 129 (2022).
Wölfel, R. et al. Virological assessment of hospitalized patients with COVID-2019. Nature 581, 465–469 (2020).
Perelson, A. S. & Ke, R. Mechanistic modeling of SARS‐CoV‐2 and other infectious diseases and the effects of therapeutics. Clin. Pharmacol. Ther. 109, 829–840 (2021).
Ke, R., Zitzmann, C., Ho, D. D., Ribeiro, R. M. & Perelson, A. S. In vivo kinetics of SARS-CoV-2 infection and its relationship with a person’s infectiousness. Proc. Natl. Acad. Sci. USA 118, e2111477118 (2021).
Marc, A. et al. Quantifying the relationship between SARS-CoV-2 viral load and infectiousness. eLife 10, e69302 (2021).
Heitzman-Breen, N. & Ciupe, S. M. Modeling within-host and aerosol dynamics of SARS-CoV-2: the relationship with infectiousness. PLoS Comput. Biol. 18, e1009997 (2022).
Goyal, A., Reeves, D. B., Cardozo-Ojeda, E. F., Schiffer, J. T. & Mayer, B. T. Viral load and contact heterogeneity predict SARS-CoV-2 transmission and super-spreading events. eLife 10, e63537 (2021).
Iyaniwura, S. A. et al. The kinetics of SARS-CoV-2 infection based on a human challenge study. Proc. Natl. Acad. Sci. USA 121, e2406303121 (2024).
Sanche, S. et al. A simple model of COVID-19 explains disease severity and the effect of treatments. Sci. Rep. 12, 14210 (2022).
Gandhi, R. T., Lynch, J. B. & Del Rio, C. Mild or moderate Covid-19. N. Engl. J. Med. 383, 1757–1766 (2020).
Avila, J., Long, B., Holladay, D. & Gottlieb, M. Thrombotic complications of COVID-19. Am. J. Emerg. Med. 39, 213–218 (2021).
Zhang, J., Dong, X., Liu, G. & Gao, Y. Risk and protective factors for COVID-19 morbidity, severity, and mortality. Clin. Rev. Allergy Immunol. 64, 90–107 (2022).
Ke, R. et al. Daily longitudinal sampling of SARS-CoV-2 infection reveals substantial heterogeneity in infectiousness. Nat. Microbiol. 7, 640–652 (2022).
Hay, J. A. et al. Quantifying the impact of immune history and variant on SARS-CoV-2 viral kinetics and infection rebound: a retrospective cohort study. eLife 11, e81849 (2022).
Puhach, O., Meyer, B. & Eckerle, I. SARS-CoV-2 viral load and shedding kinetics. Nat. Rev. Microbiol. https://doi.org/10.1038/s41579-022-00822-w (2022).
Owens, K., Esmaeili, S. & Schiffer, J. T. Heterogeneous SARS-CoV-2 kinetics due to variable timing and intensity of immune responses. JCI Insight 9, e176286 (2024).
Natarajan, A. et al. Gastrointestinal symptoms and fecal shedding of SARS-CoV-2 RNA suggest prolonged gastrointestinal infection. Med 3, 371–387.e9 (2022).
Gupta, S., Parker, J., Smits, S., Underwood, J. & Dolwani, S. Persistent viral shedding of SARS‐CoV‐2 in faeces – a rapid review. Colorectal Dis. 22, 611–620 (2020).
Cevik, M. et al. SARS-CoV-2, SARS-CoV, and MERS-CoV viral load dynamics, duration of viral shedding, and infectiousness: a systematic review and meta-analysis. Lancet Microbe 2, e13–e22 (2021).
Zhang, Y. et al. Prevalence and persistent shedding of fecal SARS-CoV-2 RNA in patients with COVID-19 infection: a systematic review and meta-analysis. Clin. Transl. Gastroenterol. 12, e00343 (2021).
Du, W. et al. Persistence of SARS-CoV-2 virus RNA in feces: a case series of children. J. Infect. Public Health 13, 926–931 (2020).
Arts, P. J. et al. Longitudinal and quantitative fecal shedding dynamics of SARS-CoV-2, pepper mild mottle virus, and crAssphage. mSphere 8, e00132–23 (2023).
Phan, T. et al. A simple SEIR-V model to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission using wastewater-based surveillance data. Sci. Total Environ. 857, 159326 (2023).
Pell, B., Brozak, S., Phan, T., Wu, F. & Kuang, Y. The emergence of a virus variant: dynamics of a competition model with cross-immunity time-delay validated by wastewater surveillance data for COVID-19. J. Math. Biol. 86, 63 (2023).
Brouwer, A. F. et al. The role of time-varying viral shedding in modelling environmental surveillance for public health: revisiting the 2013 poliovirus outbreak in Israel. J. R. Soc. Interface 19, 20220006 (2022).
Ahmadini, A., Msmali, A., Mutum, Z. & Raghav, Y. S. The mathematical modeling approach for the wastewater treatment process in Saudi Arabia during COVID-19 pandemic. Discrete Dyn. Nat. Soc. 2022, 1–15 (2022).
Nourbakhsh, S. et al. A wastewater-based epidemic model for SARS-CoV-2 with application to three Canadian cities. Epidemics 39, 100560 (2022).
McMahan, C. S. et al. COVID-19 wastewater epidemiology: a model to estimate infected populations. Lancet Planet. Health 5, e874–e881 (2021).
Polcz, P. et al. Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants. Water Res. 241, 120098 (2023).
Proverbio, D. et al. Model-based assessment of COVID-19 epidemic dynamics by wastewater analysis. Sci. Total Environ. 827, 154235 (2022).
Pájaro, M., Fajar, N. M., Alonso, A. A. & Otero-Muras, I. Stochastic SIR model predicts the evolution of COVID-19 epidemics from public health and wastewater data in small and medium-sized municipalities: a one year study. Chaos Solitons Fractals 164, 112671 (2022).
Meadows, T. et al. Epidemiological model can forecast COVID-19 outbreaks from wastewater-based surveillance in rural communities. Water Res. 268, 122671 (2025).
Pant, B., Safdar, S., Ngonghala, C. N. & Gumel, A. B. Mathematical assessment of wastewater-based epidemiology to predict SARS-CoV-2 cases and hospitalizations in Miami-Dade County. Acta Biotheor. 73, 2 (2025).
Joung, M. J. et al. Coupling wastewater-based epidemiological surveillance and modelling of SARS-COV-2/COVID-19: practical applications at the Public Health Agency of Canada. Can. Commun. Dis. Rep. 49, 166–174 (2023).
Hunter, E. & Kelleher, J. D. Understanding the assumptions of an SEIR compartmental model using agentization and a complexity hierarchy. J. Comput. Math. Data Sci. 4, 100056 (2022).
Brauer, F. Some simple epidemic models. Math. Biosci. Eng. 3, 1–15 (2006).
Eikenberry, S. E. et al. To mask or not to mask: modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic. Infect. Dis. Model. 5, 293–308 (2020).
Brauer, F. & Castillo-Chavez, C. Mathematical Models in Population Biology and Epidemiology, Vol. 40 (Springer New York, 2012).
Saikia, D., Bora, K. & Bora, M. P. COVID-19 outbreak in India: an SEIR model-based analysis. Nonlinear Dyn. 104, 4727–4751 (2021).
Saad-Roy, C. M. et al. Immune life history, vaccination, and the dynamics of SARS-CoV-2 over the next 5 years. Science 370, 811–818 (2020).
Bivins, A. et al. Persistence of SARS-CoV-2 in water and wastewater. Environ. Sci. Technol. Lett. 7, 937–942 (2020).
Hart, O. E. & Halden, R. U. Computational analysis of SARS-CoV-2/COVID-19 surveillance by wastewater-based epidemiology locally and globally: feasibility, economy, opportunities and challenges. Sci. Total Environ. 730, 138875 (2020).
Hiatt, C. W. Kinetics of the inactivation of viruses. Bacteriol. Rev. 28, 150–163 (1964).
Ahmed, W. et al. Decay of SARS-CoV-2 and surrogate murine hepatitis virus RNA in untreated wastewater to inform application in wastewater-based epidemiology. Environ. Res. 191, 110092 (2020).
De Oliveira, L. C. et al. Viability of SARS-CoV-2 in river water and wastewater at different temperatures and solids content. Water Res. 195, 117002 (2021).
Lau, H. et al. Evaluating the massive underreporting and undertesting of COVID-19 cases in multiple global epicenters. Pulmonology 27, 110–115 (2021).
Phan, T. et al. Modeling the emergence of viral resistance for SARS-CoV-2 during treatment with an anti-spike monoclonal antibody. PLoS Pathog. 20, e1011680 (2024).
Han, M. S. et al. Viral RNA load in mildly symptomatic and asymptomatic children with COVID-19, Seoul, South Korea. Emerg. Infect. Dis. 26, 2497–2499 (2020).
Schmitz, B. W. et al. Enumerating asymptomatic COVID-19 cases and estimating SARS-CoV-2 fecal shedding rates via wastewater-based epidemiology. Sci. Total Environ. 801, 149794 (2021).
Wu, F. et al. Making waves: wastewater surveillance of SARS-CoV-2 in an endemic future. Water Res. 219, 118535 (2022).
Wu, F. et al. SARS-CoV-2 titers in wastewater are higher than expected from clinically confirmed cases. mSystems 5, e00614-20 (2020).
Angulo, F. J., Finelli, L. & Swerdlow, D. L. Estimation of US SARS-CoV-2 infections, symptomatic infections, hospitalizations, and deaths using seroprevalence surveys. JAMA Netw. Open 4, e2033706 (2021).
Radu, E. et al. Emergence of SARS-CoV-2 Alpha lineage and its correlation with quantitative wastewater-based epidemiology data. Water Res. 215, 118257 (2022).
Schill, R., Nelson, K. L., Harris-Lovett, S. & Kantor, R. S. The dynamic relationship between COVID-19 cases and SARS-CoV-2 wastewater concentrations across time and space: considerations for model training data sets. Sci. Total Environ. 871, 162069 (2023).
Hewitt, J. et al. Sensitivity of wastewater-based epidemiology for detection of SARS-CoV-2 RNA in a low prevalence setting. Water Res. 211, 118032 (2022).
Hong, P.-Y. et al. Estimating the minimum number of SARS-CoV-2 infected cases needed to detect viral RNA in wastewater: to what extent of the outbreak can surveillance of wastewater tell us? Environ. Res. 195, 110748 (2021).
Nauta, M. et al. Early detection of local SARS-CoV-2 outbreaks by wastewater surveillance: a feasibility study. Epidemiol. Infect. 151, e28 (2023).
Hegazy, N. et al. Understanding the dynamic relation between wastewater SARS-CoV-2 signal and clinical metrics throughout the pandemic. Sci. Total Environ. 853, 158458 (2022).
Armas, F. et al. Contextualizing wastewater-based surveillance in the COVID-19 vaccination era. Environ. Int. 171, 107718 (2023).
Peng, K. K. et al. An exploration of the relationship between wastewater viral signals and COVID-19 hospitalizations in Ottawa, Canada. Infect. Dis. Model. 8, 617–631 (2023).
Chowell, G., Sattenspiel, L., Bansal, S. & Viboud, C. Mathematical models to characterize early epidemic growth: a review. Phys. Life Rev. 18, 66–97 (2016).
Pell, B., Phan, T., Rutter, E. M., Chowell, G. & Kuang, Y. Simple multi-scale modeling of the transmission dynamics of the 1905 plague epidemic in Bombay. Math. Biosci. 301, 83–92 (2018).
Saikia, D., Bora, K. & Bora, M. P. Counting the uncounted: estimating the unaccounted COVID-19 infections in India. Nonlinear Dyn. 112, 9703–9717 (2024).
Jewell, N. P. & Lewnard, J. A. On the use of the reproduction number for SARS-COV-2: estimation, misinterpretations and relationships with other ecological measures. J. R. Stat. Soc. Ser. A Stat. Soc. 185, S16–S27 (2022).
Karthikeyan, S. et al. Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission. Nature 609, 101–108 (2022).
Amman, F. et al. Viral variant-resolved wastewater surveillance of SARS-CoV-2 at national scale. Nat. Biotechnol. 40, 1814–1822 (2022).
Vigil, K. et al. Long-term monitoring of SARS-CoV-2 variants in wastewater using a coordinated workflow of droplet digital PCR and nanopore sequencing. Water Res. 254, 121338 (2024).
Xu, X. et al. High-resolution and real-time wastewater viral surveillance by nanopore sequencing. Water Res. 256, 121623 (2024).
Ciupe, S. M. & Tuncer, N. Identifiability of parameters in mathematical models of SARS-CoV-2 infections in humans. Sci. Rep. 12, 14637 (2022).
Zitzmann, C., Ke, R., Ribeiro, R. M. & Perelson, A. S. How robust are estimates of key parameters in standard viral dynamic models? PLoS Comput. Biol. 20, e1011437 (2024).
Eyre, D. W. et al. Effect of Covid-19 vaccination on transmission of Alpha and Delta variants. N. Engl. J. Med. 386, 744–756 (2022).
Atmar, R. L. et al. Norwalk virus shedding after experimental human infection. Emerg. Infect. Dis. 14, 1553–1557 (2008).
Leon, J. S. et al. Randomized, double-blinded clinical trial for human norovirus inactivation in oysters by high hydrostatic pressure processing. Appl. Environ. Microbiol. 77, 5476–5482 (2011).
Rouphael, N. et al. Dose-response of a norovirus GII.2 controlled human challenge model inoculum. J. Infect. Dis. 226, 1771–1780 (2022).
Phan, T. et al. Modeling suggests SARS-CoV-2 rebound after nirmatrelvir-ritonavir treatment is driven by target cell preservation coupled with incomplete viral clearance. J. Virol. 99, e0162324 (2025).
Edelstein, G. E. et al. SARS-CoV-2 virologic rebound with nirmatrelvir–ritonavir therapy: an observational study. Ann. Intern. Med. 176, 1577–1585 (2023).
Anderson, A. S., Caubel, P. & Rusnak, J. M. Nirmatrelvir–ritonavir and viral load rebound in Covid-19. N. Engl. J. Med. 387, 1047–1049 (2022).
Krivoňáková, N. et al. Mathematical modeling based on RT-qPCR analysis of SARS-CoV-2 in wastewater as a tool for epidemiology. Sci. Rep. 11, 19456 (2021).
Sanjuán, R. & Domingo-Calap, P. Reliability of wastewater analysis for monitoring COVID-19 incidence revealed by a long-term follow-up study. Front. Virol. 1, 776998 (2021).
Bertels, X. et al. Factors influencing SARS-CoV-2 RNA concentrations in wastewater up to the sampling stage: a systematic review. Sci. Total Environ. 820, 153290 (2022).
Gundy, P. M., Gerba, C. P. & Pepper, I. L. Survival of coronaviruses in water and wastewater. Food Environ. Virol. 1, 10 (2009).
Wiesner-Friedman, C. et al. Characterizing spatial information loss for wastewater surveillance using crAssphage: effect of decay, temperature, and population mobility. Environ. Sci. Technol. 57, 20802–20812 (2023).
Chahal, C. et al. Pathogen and particle associations in wastewater. Adv. Appl. Microbiol. 97, 63–119 (2016).
Walker, D. I. et al. Piloting wastewater-based surveillance of norovirus in England. Water Res. 263, 122152 (2024).
Wolfe, M. K. et al. Wastewater-based detection of two influenza outbreaks. Environ. Sci. Technol. Lett. 9, 687–692 (2022).
Hughes, B. et al. Respiratory syncytial virus (RSV) RNA in wastewater settled solids reflects RSV clinical positivity rates. Environ. Sci. Technol. Lett. 9, 173–178 (2022).
Oghuan, J. et al. Wastewater analysis of Mpox virus in a city with low prevalence of Mpox disease: an environmental surveillance study. Lancet Reg. Health Am. 28, 100639 (2023).
Van Kampen, J. J. A. et al. Duration and key determinants of infectious virus shedding in hospitalized patients with coronavirus disease-2019 (COVID-19). Nat. Commun. 12, 267 (2021).