ArticlemSphere2026
Rapid identification of COVID wastewater surges in the absence of case data.
Article in mSphere, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Genetic testing of community wastewater (wastewater surveillance) is a valuable tool for following trends in the abundance of SARS-CoV-2 and other infectious disease pathogens over time. Wastewater surveillance is increasingly important in the absence of corresponding epidemiological data, particularly for infectious diseases with limited timely data on clinical case incidences. Due to the inherent noise in wastewater data, a single sample is not sufficient to identify a sustained trend in the abundance of a target. This challenge is magnified in resource-limited settings where samples may be collected only once or twice per week. In this work, we collected 24-h composite samples of wastewater daily from a single facility for nearly 4 years. We use this high-frequency data set to describe a method for identifying trends in SARS-CoV-2 abundance in wastewater based on a variety of collection frequencies. Our results indicate that collecting two 24-h composites per week for 2 weeks is sufficient to accurately identify a SARS-CoV-2 surge. We conclude that low-frequency wastewater sampling performs reasonably well in identifying trends in a timely fashion.IMPORTANCEWastewater surveillance is increasingly being used to track trends in infectious disease targets such as SARS-CoV-2, often in the absence of widespread clinical data. In order to interpret the results of wastewater surveillance appropriately in these contexts, it is important to understand how to identify a surge in abundance in time to provoke appropriate downstream responses. This information can be used to adjust collection strategies to optimize target surveillance, particularly in resource-limited settings.
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Registered trials
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