Wastewater surveillance
- Collection:
- Health Policy and Services Research
- Series Title(s):
- Science & tech spotlight
- Contributor(s):
- United States. Government Accountability Office, issuing body. United States. Congress, issuing body.
- Publication:
- [Washington, DC] : United States Government Accountability Office, April 2022
- Language(s):
- English
- Format:
- Text
- Subject(s):
- Government Regulation Waste Water -- legislation & jurisprudence Wastewater-Based Epidemiological Monitoring United States
- Genre(s):
- Technical Report
- Abstract:
- Why this matters. Wastewater surveillance can be an efficient way to detect community-level disease outbreaks and other health threats. It has the potential to identify a COVID-19 outbreak 1 to 2 weeks sooner than clinical testing and allow for a more rapid public health response. However, the lack of national coordination and standardized methods pose challenges to wider adoption. What is it? Wastewater surveillance, also known as wastewater-based epidemiology, is the monitoring of pathogens (e.g., viruses), as well as pharmaceuticals and toxic or other chemicals by testing sewage (see fig. 1). Public health officials can use this approach to monitor for outbreaks, identify threats (e.g., antibiotic-resistant bacteria), and, in response, support the mobilization of resources. Pathogens and chemicals can enter sewer systems through human waste. Wastewater surveillance programs collect sewage samples from these systems and treatment plants and send them to laboratories for testing. Officials can use test data, for example, to assess whether there is a viral outbreak or increasing drug use and then decide what actions to take to protect public health. These actions might include increased clinical testing in an area, or alerting local clinics and hospitals to prepare for an increase in patients.
- Copyright:
- The National Library of Medicine believes this item to be in the public domain. (More information)
- Extent:
- 1 online resource (1 PDF file (2 unnumbered pages))
- Illustrations:
- Illustrations
- NLM Unique ID:
- 9918434587806676 (See catalog record)
- Permanent Link:
- http://resource.nlm.nih.gov/9918434587806676