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 that are a public health burden. 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.