Reading the Sewer for Signals: An Evaluation of Wastewater Surveillance as a Community Disease Monitoring System
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RN to BSN Program, Aspen University
N493: Community Health II
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Reading the Sewer for Signals: An Evaluation of Wastewater Surveillance as a Community Disease Monitoring System
Public health surveillance means gathering health data continuously and on purpose, making sense of it, and using it to act. Most surveillance in the United States depends on people seeking care: a patient is tested, a laboratory reports a result, and a case enters the system. That dependence creates blind spots, because people who do not seek care, cannot afford it, or have mild illness are never counted. Wastewater surveillance, which measures pathogen levels in community sewage, avoids that dependence entirely. This paper describes how wastewater surveillance works, evaluates it against the attributes the Centers for Disease Control and Prevention uses to judge surveillance systems, applies it to a composite county health department, and considers the ethical questions it raises and the public health nurse's role in using its data.
How Wastewater Surveillance Works
Many pathogens are shed in stool, urine, or other body fluids, including by people with no symptoms. When samples of untreated wastewater are collected at a treatment plant and tested, the concentration of a pathogen's genetic material reflects infection levels across the entire population connected to that sewer system. For SARS-CoV-2, roughly 40 percent of infected people shed viral RNA in stool, so trends in wastewater can track symptomatic and asymptomatic infections alike (Kirby et al., 2021).
The Centers for Disease Control and Prevention launched the National Wastewater Surveillance System in September 2020, and by August 2021 it included 37 states, four cities, and two territories (Kirby et al., 2021). Health departments used the data to issue alerts to local jurisdictions, place mobile testing in areas with rising levels, check for irregularities in case reporting, and forecast hospital needs. Since then, programs have expanded testing to other targets, such as influenza and respiratory syncytial virus, turning a pandemic tool into a broader monitoring system (McClary-Gutierrez et al., 2021).
Evaluating the System Against CDC Attributes
The CDC guidelines for evaluating public health surveillance systems identify attributes that determine a system's usefulness, including simplicity, flexibility, data quality, acceptability, sensitivity, predictive value positive, representativeness, timeliness, and stability (German et al., 2001). Applying six of them to wastewater surveillance shows both its strengths and its limits.
Timeliness is its greatest strength. Wastewater levels often rise before clinical cases are reported, because people shed virus before they feel sick, seek testing, or receive results. Representativeness is a second strength, with an important caveat. Every household connected to the sewer contributes to the sample regardless of insurance, symptoms, or willingness to test, and the ability to conduct wastewater surveillance is not affected by access to health care (Kirby et al., 2021). However, homes on septic systems, common in rural areas, are invisible to it.
Flexibility is high: the same samples can be tested for new targets without changing collection. Sensitivity at the community level is good, since trends are detectable even when individual cases are missed. Data quality and stability are the system's weaknesses. Concentrations vary with rainfall, industrial discharge, and laboratory methods, so single measurements are noisy and trends over several samples are more reliable. Sustaining the system requires laboratory capacity, funding, and partnerships between utilities and health departments that did not exist before the pandemic (McClary-Gutierrez et al., 2021). Wastewater surveillance tells a health department that infection is rising in a sewershed; it cannot tell the department who is sick.
Application: A Composite County Health Department
Consider a composite county of about 180,000 residents served by two wastewater treatment plants, one serving the county seat and one serving a smaller town with a large meatpacking plant. The health department tests samples from both plants twice weekly for SARS-CoV-2 and influenza A. In late autumn, influenza A levels at the smaller plant rise steadily across four consecutive samples while reported cases remain low, because many workers are uninsured and do not seek testing.
The public health nurse uses the signal to act before clinical data would have justified it. The nurse contacts the meatpacking plant's occupational health office and the town's federally qualified health center to schedule an on-site influenza vaccination clinic, alerts local clinicians and the school district to watch for influenza-like illness, and works with community health workers to share bilingual messages about vaccination and staying home when sick. When clinical cases do begin to rise two weeks later, the vaccination clinic has already reached several hundred workers.
Ethical Considerations
Because wastewater surveillance samples entire communities without individual consent, it raises ethical and legal questions. Sampling at a treatment plant that serves tens of thousands of people carries little privacy risk, but sampling at the level of a single building, such as a dormitory, a jail, or a workplace, could reveal information about identifiable groups and lead to stigma or punitive action. Legal scholars have argued that wastewater monitoring should follow principles of transparency, proportionality, and community engagement, and that data should be used to direct resources toward communities rather than against them (Gable et al., 2020). In the composite county, the health department publishes its data at the treatment-plant level only, explains the program on its website, and uses rising levels to offer services, not to single out a workplace publicly.
The Public Health Nurse's Role
Public health nurses turn surveillance data into action. They interpret trends for community partners in plain language, target outreach such as vaccination and testing to the places where levels are rising, and connect with clinicians who can confirm what wastewater suggests. They also represent communities in decisions about how data are collected and shared, ensuring that residents understand the program and that the data serve them. As wastewater surveillance becomes a permanent part of public health infrastructure, nurses who understand both its power and its limits will be well placed to use it.
Conclusion
Wastewater surveillance measures the health of a community without waiting for its members to seek care. Evaluated against the CDC attributes, it is timely, flexible, and broadly representative of connected households, but its data are noisy, it cannot identify individuals, and it depends on sustained funding and partnerships. Used alongside case-based surveillance, with attention to privacy and community trust, it gives health departments an early signal, and public health nurses the chance to act on it before an outbreak fills clinics and hospitals.
References
Gable, L., Ram, N., & Ram, J. L. (2020). Legal and ethical implications of wastewater monitoring of SARS-CoV-2 for COVID-19 surveillance. Journal of Law and the Biosciences, 7(1), Article lsaa039. https://doi.org/10.1093/jlb/lsaa039
German, R. R., Lee, L. M., Horan, J. M., Milstein, R. L., Pertowski, C. A., & Waller, M. N. (2001). Updated guidelines for evaluating public health surveillance systems: Recommendations from the Guidelines Working Group. MMWR Recommendations and Reports, 50(RR-13), 1-35.
Kirby, A. E., Walters, M. S., Jennings, W. C., Fugitt, R., LaCross, N., Mattioli, M., Marsh, Z. A., Roberts, V. A., Mercante, J. W., Yoder, J., & Hill, V. R. (2021). Using wastewater surveillance data to support the COVID-19 response: United States, 2020-2021. MMWR. Morbidity and Mortality Weekly Report, 70(36), 1242-1244. https://doi.org/10.15585/mmwr.mm7036a2
McClary-Gutierrez, J. S., Mattioli, M. C., Marcenac, P., Silverman, A. I., Boehm, A. B., Bibby, K., Balliet, M., de los Reyes, F. L., Gerrity, D., Griffith, J. F., Holden, P. A., Katehis, D., Kester, G., LaCross, N., Lipp, E. K., Meiman, J., Noble, R. T., Brossard, D., & McLellan, S. L. (2021). SARS-CoV-2 wastewater surveillance for public health action. Emerging Infectious Diseases, 27(9), 1-8. https://doi.org/10.3201/eid2709.210753
How this N 493 Module 1 example is structured
N493 opens with epidemiology, disease transmission and surveillance, and in many sections the first written work asks students to analyze how communities detect and track disease. Aspen does not publish module deliverables, so your classroom's prompt decides the exact question; read this as a model of the analysis. The example describes one surveillance system, evaluates it attribute by attribute using the CDC's own guidelines, shows its value in a composite county where case reporting fails, addresses ethics and closes on what the nurse does with the data.
N493 Module 1 questions, answered
What does N493 Module 1 usually ask for?
The course opens with epidemiology and disease transmission, and early written work commonly asks students to analyze how disease is detected and tracked in communities or to apply epidemiologic concepts to a public health problem. Aspen does not publish module deliverables, so check your classroom for the exact prompt, length and sources.
How do I evaluate a surveillance system rather than just describe it?
Use the CDC's evaluation attributes, such as timeliness, representativeness, sensitivity, flexibility, data quality and stability, and judge the system on each with reasons. The sample applies six attributes and identifies both strengths and weaknesses, which is what makes it an evaluation.
Where does nursing fit in a paper about surveillance?
In turning data into action: interpreting trends for partners, targeting outreach and vaccination, connecting with clinicians and advocating for communities in how data are used. The sample shows these roles in a composite county response.
Write yours, or have the desk draft it
This paper is an original model document written by our desk, not a submitted student paper and not an official Aspen University document. Read it for the moves, then write your own to the instructions in your classroom. If you want one built to your exact prompt and rubric, the first custom sample is free and arrives in 24 to 48 hours.