Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2023 Jun:33:100458.
doi: 10.1016/j.coesh.2023.100458. Epub 2023 Mar 7.

Moving forward with COVID-19: Future research prospects of wastewater-based epidemiology methodologies and applications

Affiliations
Review

Moving forward with COVID-19: Future research prospects of wastewater-based epidemiology methodologies and applications

Guangming Jiang et al. Curr Opin Environ Sci Health. 2023 Jun.

Abstract

Wastewater-based epidemiology (WBE) has been demonstrated for its great potential in tracking of coronavirus disease 2019 (COVID-19) transmission among populations despite some inherent methodological limitations. These include non-optimized sampling approaches and analytical methods; stability of viruses in sewer systems; partitioning/retention in biofilms; and the singular and inaccurate back-calculation step to predict the number of infected individuals in the community. Future research is expected to (1) standardize best practices in wastewater sampling, analysis and data reporting protocols for the sensitive and reproducible detection of viruses in wastewater; (2) understand the in-sewer viral stability and partitioning under the impacts of dynamic wastewater flow, properties, chemicals, biofilms and sediments; and (3) achieve smart wastewater surveillance with artificial intelligence and big data models. Further specific research is essential in the monitoring of other viral pathogens with pandemic potential and subcatchment applications to maximize the benefits of WBE beyond COVID-19.

Keywords: Artificial intelligence; COVID-19; Influenza; SARS-CoV-2; Sewer; Wastewater-based epidemiology.

PubMed Disclaimer

Conflict of interest statement

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Guangming Jiang reports financial support was provided by Australian Research Council. Yanchen Liu reports financial support was provided by National Natural Science Foundation of China. Yanchen Liu reports financial support was provided by Tsinghua University. Guangming Jiang reports financial support was provided by Australian Academy of Science.

Figures

Figure 1
Figure 1
Workflow and methodological uncertainties for wastewater-based epidemiology of viral infectious diseases [17].
Figure 2
Figure 2
In-sewer factors (black font) and processes (red font, underlined) affecting the stability and partitioning of viral biomarkers in wastewater. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

References

    1. Kumar M., Jiang G., Kumar Thakur A., Chatterjee S., Bhattacharya T., Mohapatra S., Chaminda T., Kumar Tyagi V., Vithanage M., Bhattacharya P., et al. Lead time of early warning by wastewater surveillance for COVID-19: geographical variations and impacting factors. Chem Eng J. 2022;441:135936. - PMC - PubMed
    1. Jiang G., Wu J., Weidhaas J., Li X., Chen Y., Mueller J., Li J., Kumar M., Zhou X., Arora S., et al. Artificial neural network-based estimation of COVID-19 case numbers and effective reproduction rate using wastewater-based epidemiology. Water Res. 2022;218:118451. - PMC - PubMed
    2. This paper for the first time developed and demonstrated the smart wastewater surveillance based on artificial neural network for the tracking of COVID-19 prevalence and transmission in communities. The study was based on a large and year long dataset from Wisconsin and Utah sewage surveillance programs. It has been transferred to Wisconsin Department of Health for their test and implementation shortly after the publication.

    1. Larsen D.A., Wigginton K.R. Tracking COVID-19 with wastewater. Nat Biotechnol. 2020;38:1151–1153. - PMC - PubMed
    1. Wu F., Zhang J., Xiao A., Gu X., Lee W.L., Armas F., Kauffman K., Hanage W., Matus M., Ghaeli N., et al. SARS-CoV-2 titers in wastewater are higher than expected from clinically confirmed cases. mSystems. 2020;5 e00614-20. - PMC - PubMed
    1. McMahan C.S., Self S., Rennert L., Kalbaugh C., Kriebel D., Graves D., Colby C., Deaver J.A., Popat S.C., Karanfil T., et al. COVID-19 wastewater epidemiology: a model to estimate infected populations. Lancet Planet Health. 2021;5:e874–e881. - PMC - PubMed

LinkOut - more resources