Wastewater-based epidemiology for COVID-19 surveillance and beyond: A survey
Chen Chen,
Yunfan Wang,
Gursharn Kaur,
Aniruddha Adiga,
Baltazar Espinoza,
Srinivasan Venkatramanan,
Andrew Warren,
Bryan Lewis,
Justin Crow,
Rekha Singh,
Alexandra Lorentz,
Denise Toney,
Madhav Marathe
Affiliations
Chen Chen
Department of Computer Science, University of Virginia, Charlottesville, 22904, United States; Corresponding author.
Yunfan Wang
Department of Computer Science, University of Virginia, Charlottesville, 22904, United States
Gursharn Kaur
Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
Aniruddha Adiga
Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
Baltazar Espinoza
Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
Srinivasan Venkatramanan
Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
Andrew Warren
Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
Bryan Lewis
Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
Justin Crow
Virginia Department of Health, Richmond, 23219, United States
Rekha Singh
Virginia Department of Health, Richmond, 23219, United States
Alexandra Lorentz
Division of Consolidated Laboratory Services, Department of General Services, Richmond, 23219, United States
Denise Toney
Division of Consolidated Laboratory Services, Department of General Services, Richmond, 23219, United States
Madhav Marathe
Department of Computer Science, University of Virginia, Charlottesville, 22904, United States; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively track the prevalence of COVID-19 within communities. The traditional way to estimate the disease prevalence is to estimate from reported clinical test data or surveys. However, the coverage of clinical tests is often limited and the tests can be labor-intensive, requires reliable and timely results, and consistent diagnostic and reporting criteria. Recent studies revealed that patients who are diagnosed with COVID-19 often undergo fecal shedding of SARS-CoV-2 virus into wastewater, which makes wastewater-based epidemiology for COVID-19 surveillance a promising approach to complement traditional clinical testing. In this paper, we survey the existing literature regarding wastewater-based epidemiology for COVID-19 surveillance and summarize the current advances in the area. Specifically, we have covered the key aspects of wastewater sampling, sample testing, and presented a comprehensive and organized summary of wastewater data analytical methods. Finally, we provide the open challenges on current wastewater-based COVID-19 surveillance studies, aiming to encourage new ideas to advance the development of effective wastewater-based surveillance systems for general infectious diseases.
