Epidemiological model can forecast COVID-19 outbreaks from wastewater-based surveillance in rural communities

Meadows, Tyler; Coats, Erik R.; Narum, Solana; Top, Eva M.; Ridenhour, Benjamin J.; Stalder, Thibault

doi:10.1016/j.watres.2024.122671

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Epidemiological model can forecast COVID-19 outbreaks from wastewater-based surveillance in rural communities

1 01 2025
By Meadows, Tyler ; Coats, Erik R. ; Narum, Solana ; ...
Source: Water Res. 268(Pt A):122671

Public Access Version Available on: January 01, 2026, 12:00 AM

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English

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Alternative Title:

Water Res
Personal Author:

Meadows, Tyler ; Coats, Erik R. ; Narum, Solana ; Top, Eva M. ; Ridenhour, Benjamin J. ; ... More +

Meadows, Tyler ; Coats, Erik R. ; Narum, Solana ; Top, Eva M. ; Ridenhour, Benjamin J. ; Stalder, Thibault Less -
Description:

Wastewater has emerged as a crucial tool for infectious disease surveillance, offering a valuable means to bridge the equity gap between underserved communities and larger urban municipalities. However, using wastewater surveillance in a predictive manner remains a challenge. In this study, we tested if detecting SARS-CoV-2 in wastewater can forecast outbreaks in rural communities. Under the CDC National Wastewater Surveillance program, we monitored the SARS-CoV-2 in the wastewater of five rural communities and a small city in Idaho (USA). We then used a particle filter method coupled with a stochastic susceptible-exposed-infectious-recovered (SEIR) model to infer active case numbers using quantities of SARS-CoV-2 in wastewater. Our findings revealed that while high daily variations in wastewater viral load made real-time interpretation difficult, the SEIR model successfully factored out this noise, enabling accurate forecasts of the Omicron outbreak in five of the six towns shortly after initial increases in SARS-CoV-2 concentrations were detected in wastewater. The model predicted outbreaks with a lead time of 0 to 11 days (average of 6 days +/- 4) before the surge in reported clinical cases. This study not only underscores the viability of wastewater-based epidemiology (WBE) in rural communities-a demographic often overlooked in WBE research-but also demonstrates the potential of advanced epidemiological modeling to enhance the predictive power of wastewater data. Our work paves the way for more reliable and timely public health guidance, addressing a critical gap in the surveillance of infectious diseases in rural populations.
Subjects:

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COVID-19 Disease Outbreaks Epidemiological Models Forecasting Humans Idaho Rural Population SARS-CoV-2 Wastewater Wastewater-Based Epidemiological Monitoring
Keywords:

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Rural Communities SEIR Wastewater-based Epidemiology (WBE)
Source:

Water Res. 268(Pt A):122671
Pubmed ID:

39488168
Pubmed Central ID:

PMC11614685
Document Type:

Journal Article
Funding:

P20 GM104420/GM/NIGMS NIH HHSUnited States/ ; R43 CK000544/CK/NCEZID CDC HHSUnited States/

P20 GM104420/GM/NIGMS NIH HHSUnited States/ ; R43 CK000544/CK/NCEZID CDC HHSUnited States/ Less -
Volume:

268
Collection(s):

CDC Public Access
Main Document Checksum:

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urn:sha-512:c8ac895296866ca2b30a8f6c8b50f6acf83236716ebe138b9d7cff17c6139a369ab8dd2ef69bc7bc76cd9ca5a88dd07a094c9161550f15dfa492fd51f790b4b6
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