ArticleThe Science of the total environment2022
Spatial and temporal variability and data bias in wastewater surveillance of SARS-CoV-2 in a sewer system.
Article in The Science of the total environment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
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Who cites it
34 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of Methodological Approaches to SARS-CoV-2 Wastewater Surveillance.Viruses · 2026Pooled it
- Toward a quality-managed operational architecture for wastewater surveillance of zoonotic and emerging pathogens.Applied and environmental microbiology · 2026Review
- Transkingdom Interactions Between Viruses and Bacteria: Implications for Wastewater Treatment Efficiency.Food and environmental virology · 2026Review
- High prevalence of tomato brown rugose fruit virus in domestic wastewater as a potential viral indicator for treatment systems.Scientific reports · 2026Article
- Improving surveillance of infectious diseases in child daycare settings: insights from a pilot study in the Netherlands.Frontiers in public health · 2026Article
- Long term assessment of SARS-CoV-2 in wastewater and the transition to evaluate additional viral targets.The Science of the total environment · 2025Article
- Identification of Statewide Hotspots for Respiratory Disease Targets Using Wastewater Monitoring Data.Tropical medicine and infectious disease · 2025Article
- Advancing health equity in wastewater-based epidemiology: A global critical review and conceptual framework.SSM - population health · 2025Review
- Advances in Wastewater-Based Epidemiology for Pandemic Surveillance: Methodological Frameworks and Future Perspectives.Microorganisms · 2025Review
- Viral concentration method biases in the detection of viral profiles in wastewater.Applied and environmental microbiology · 2025Article
- Sewer system sampling for wastewater-based disease surveillance: Is the work worth it?Journal of water and health · 2024Article
- Article
- Advancing Public Health Surveillance: Integrating Modeling and GIS in the Wastewater-Based Epidemiology of Viruses, a Narrative Review.Pathogens (Basel, Switzerland) · 2024Review
- Temporal assessment of SARS-CoV-2 detection in wastewater and its epidemiological implications in COVID-19 case dynamics.Heliyon · 2024Article
- Online trend estimation and detection of trend deviations in sub-sewershed time series of SARS-CoV-2 RNA measured in wastewater.Scientific reports · 2024Article
- Near-source passive sampling for monitoring viral outbreaks within a university residential setting.Epidemiology and infection · 2024Article
- Identifying spatiotemporal trends of SARS-CoV-2 RNA in wastewater: from the perspective of upstream and downstream wastewater-based epidemiology (WBE).Environmental science and pollution research international · 2024Article
- Assessment of sewer connectivity in the United States and its implications for equity in wastewater-based epidemiology.PLOS global public health · 2024Article
- Characterizing Spatial Information Loss for Wastewater Surveillance Using crAssphage: Effect of Decay, Temperature, and Population Mobility.Environmental science & technology · 2023Article
- Structured Ethical Review for Wastewater-Based Testing in Support of Public Health.Environmental science & technology · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The response to disease outbreaks, such as SARS-CoV-2, can be constrained by a limited ability to measure disease prevalence early at a localized level. Wastewater based epidemiology is a powerful tool identifying disease spread from pooled community sewer networks or at influent to wastewater treatment plants. However, this approach is often not applied at a granular level that permits detection of local hot spots. This study examines the spatial patterns of SARS-CoV-2 in sewage through a spatial sampling strategy across neighborhood-scale sewershed catchments. Sampling was conducted across the Reno-Sparks metropolitan area from November to mid-December of 2020. This research utilized local spatial autocorrelation tests to identify the evolution of statistically significant neighborhood hot spots in sewershed sub-catchments that were identified to lead waves of infection, with adjacent neighborhoods observed to lag with increasing viral RNA concentrations over subsequent dates. The correlations between the sub-catchments over the sampling period were also characterized using principal component analysis. Results identified distinct time series patterns, with sewersheds in the urban center, outlying suburban areas, and outlying urbanized districts generally following unique trends over the sampling period. Several demographic parameters were identified as having important gradients across these areas, namely population density, poverty levels, household income, and age. These results provide a more strategic approach to identify disease outbreaks at the neighborhood level and characterized how sampling site selection could be designed based on the spatial and demographic characteristics of neighborhoods.
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