High-throughput molecular analysis of sewage is a promising tool for precision public health. Here, we combine sewer network and demographic data to identify a residential catchment for sampling, and explore the potential of applying untargeted genomics and metabolomics to sewage to collect actionable public health data. We find that wastewater sampled upstream in a residential catchment is representative of the human microbiome and metabolome, and we are able to identify glucuronidated compounds indicative of direct human excretion, which are typically degraded too quickly to be detected at treatment plants. We show that diurnal variations during 24-hour sampling can be leveraged to discriminate between biomarkers in sewage that are associated with human activity from those related to the environmental background. Finally, we putatively annotate a suite of human-associated metabolites, including pharmaceuticals, food metabolites, and biomarkers of human health and activity, suggesting that mining untargeted data derived from residential sewage can expand currently-used biomarkers with direct public health or policy relevance. process sewage non-stop through one day, and for Herbie from Cambridge Public Works for providing his good humor and professional insights during our many sampling trips. We thank the generous sponsorship of the Kuwait Foundation for Advancement of Sciences, and the MIT Center for Microbiome Informatics and Therapeutics provided support for computational resources. We thank the WHOI FT-MS facility for sample analysis and Krista Longnecker for training in metabolomics data analysis and discussions throughout the study.