Microbiome signature in wastewater is predictive of COVID-19 case rates
- 1University of Minnesota Twin Cities
Abstract
Surveillance of SARS-CoV-2 through wastewater proved crucial during the height of the pandemic for estimating community COVID-19 cases and continues to be useful for monitoring this and other pathogens. Gastrointestinal symptoms of acute COVID-19 have been well characterized, with demonstrated significant effects on the respiratory, oral, and gut microbiomes. With this understanding, we sought to characterize the wastewater microbiome in the context of COVID-19 rates, identify associations with the wastewater SARS-CoV-2 viral loads, and apply modeling to assess the ability of the wastewater microbiome to predict COVID- 19 case rate. We observed numerous microbes associated with case rate including genera that are known to be depleted in vivo during SARS-CoV-2 infection such as keystone SCFA-producers such as Blautia, Dorea, and Akkermansia with implicated pathobionts Ruminococcus gnavus group and Ruminococcus torques group that expand. Non-human origin bacteria including Uruburuella and Stenoxybacter were also strongly associated with community case rates. Our predictive models highlighted a combination between bacteria and SARS-CoV-2 gene copies as an effective combination of covariates to estimate present cases, however microbiome covariates alone proved modestly more useful in predicting future case rates. These results highlight the heavy influence of local ecosystem and urbanicity in defining microbial composition of WWTPs. Alterations in the fecal microbiome from acute COVID-19 infection are detectable in wastewater and strongly associated with case rate, even in low-population areas. Our predictive models underscore the utility of the wastewater microbiome in understanding public health burden of COVID-19 and possibly other infectious diseases.
ImportanceOngoing COVID-19 infections and persistent symptoms continue to contribute to an expanding public health burden that is challenging to track. While overall transmission and symptom severity have tapered in acute infection leading to reduced hospitalizations, thanks in part due to widespread vaccination efforts, predicting cases provides health care units time to mobilize and adapt. This study supports a growing body of evidence that the host gut microbiome is heavily altered from infection and highlights that this consistent alteration can be harnessed to detect microbial shifts in wastewater. Here, we used the wastewater bacterial microbiome to predict community cases weeks ahead of when cases were reported with accuracy matching current standard techniques. This work furthers our understanding of COVID-19s impact on the gut microbiome, advances current wastewater-based epidemiology strategies, offers a new pool of data to better track community infections, and may support surveillance of other pathogens and novel, emerging outbreaks.
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BibTeX
@misc{schroeder2026microbiome,
title = {{Microbiome signature in wastewater is predictive of COVID-19 case rates}},
author = {T. Schroeder and C. M. Basting and E. Swanson and M. Bailey and S. R. Champeau and A. Velez and J. Li and C. Broedlow and T. Schacker and M. Osborn and N. R. Klatt},
howpublished = {medRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.16.26363250},
url = {https://www.medrxiv.org/content/10.64898/2026.09.16.26363250v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Microbiome signature in wastewater is predictive of COVID-19 case rates
AU - T. Schroeder
AU - C. M. Basting
AU - E. Swanson
AU - M. Bailey
AU - S. R. Champeau
AU - A. Velez
AU - J. Li
AU - C. Broedlow
AU - T. Schacker
AU - M. Osborn
AU - N. R. Klatt
PY - 2026
DA - 2026/09/16
PB - medRxiv
DO - 10.64898/2026.09.16.26363250
UR - https://www.medrxiv.org/content/10.64898/2026.09.16.26363250v1
AB - Surveillance of SARS-CoV-2 through wastewater proved crucial during the height of the pandemic for estimating community COVID-19 cases and continues to be useful for monitoring this and other pathogens. Gastrointestinal symptoms of acute COVID-19 have been well characterized, with demonstrated significant effects on the respiratory, oral, and gut microbiomes. With this understanding, we sought to characterize the wastewater microbiome in the context of COVID-19 rates, identify associations with the wastewater SARS-CoV-2 viral loads, and apply modeling to assess the ability of the wastewater microbiome to predict COVID- 19 case rate. We observed numerous microbes associated with case rate including genera that are known to be depleted in vivo during SARS-CoV-2 infection such as keystone SCFA-producers such as Blautia, Dorea, and Akkermansia with implicated pathobionts Ruminococcus gnavus group and Ruminococcus torques group that expand. Non-human origin bacteria including Uruburuella and Stenoxybacter were also strongly associated with community case rates. Our predictive models highlighted a combination between bacteria and SARS-CoV-2 gene copies as an effective combination of covariates to estimate present cases, however microbiome covariates alone proved modestly more useful in predicting future case rates. These results highlight the heavy influence of local ecosystem and urbanicity in defining microbial composition of WWTPs. Alterations in the fecal microbiome from acute COVID-19 infection are detectable in wastewater and strongly associated with case rate, even in low-population areas. Our predictive models underscore the utility of the wastewater microbiome in understanding public health burden of COVID-19 and possibly other infectious diseases. ImportanceOngoing COVID-19 infections and persistent symptoms continue to contribute to an expanding public health burden that is challenging to track. While overall transmission and symptom severity have tapered in acute infection leading to reduced hospitalizations, thanks in part due to widespread vaccination efforts, predicting cases provides health care units time to mobilize and adapt. This study supports a growing body of evidence that the host gut microbiome is heavily altered from infection and highlights that this consistent alteration can be harnessed to detect microbial shifts in wastewater. Here, we used the wastewater bacterial microbiome to predict community cases weeks ahead of when cases were reported with accuracy matching current standard techniques. This work furthers our understanding of COVID-19s impact on the gut microbiome, advances current wastewater-based epidemiology strategies, offers a new pool of data to better track community infections, and may support surveillance of other pathogens and novel, emerging outbreaks.
ER -