Wastewater surveillance is increasingly an effective public health tool for responding to epidemics and preparing for annual cycles of respiratory illnesses. We measured genetic markers from Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), influenza A virus (IAV) and influenza B virus (IBV) in untreated wastewater of a university campus and its local residential community over a four-year period using digital Polymerase Chain Reaction (PCR) methods. These data were then analyzed and compared to clinical case data reported to the state by zip code. The campus community is contrasted to the surrounding community by its high degree of congregate living, fluctuating population due to semester breaks, and a narrower age distribution. We show that semester breaks, when students depopulate campus, drive subsequent peaks in the transmission of SARS-CoV-2 upon their return. SARS-CoV-2 and IAV and IBV exhibit significant correlations in the level of campus and local community concentrations at 0.48, 0.63, and 0.45, respectively, demonstrating connectivity between the two populations. While IAV and IBV concentrations are highly correlated with one another, we find no relationship between influenza and SARS-CoV-2 concentrations. Like previous studies, we found a high degree of correlation between wastewater concentrations and clinical case data, with strong alignment in peaks and hence no evidence of leading or lagging indicators. Our data highlights the effectiveness of wastewater surveillance, a passive monitoring method, to estimate the current trajectory of the epidemic curve.