Critical parameters for antibiotic resistance wastewater surveillance framework linking genomic bypass and socio-economic drivers in urban infrastructure—A Case Study of South Bend, Indiana

Urban wastewater systems are key connections between public health and the environment, but it's hard to measure how hydraulic instability affects microbial risk. This research looks at the urban microbiome in South Bend, Indiana, using a mass-balance approach to understand genomic bypass—the share of community-shed antibiotic resistance genes (ARGs) escaping treatment through Combined Sewer Overflows (CSOs). By converting digital PCR data from Kim et al. 2026 into Per-Capita Daily Flux (Φ), we compared South Bend with over 100 U.S. cities. The findings show that South Bend has a positive residual risk, with antibiotic resistance gene fluxes (such as TEM and VanA) reaching 10¹¹–10¹² gene copies per person each day—higher than expected based on population density. A sign test revealed stormwater usually dilutes biological signals, but high-risk targets like VIM showed more than a 20% increase in density during rain, likely due to biofilms being mobilized by pipe cleaning. A Monte Carlo simulation (n = 10,000) estimated a median genomic bypass of 42.6%, with a 95% confidence interval from 36.1% to 47.9%. Sensitivity analysis found that the biological enrichment factor (β) was the main driver of uncertainty in bypass, while CSO volume had little impact. This suggests the bypass scale depends mostly on how much more concentrated untreated sewage is compared to treated water, not small changes in stormwater volume. Machine learning identified population density and urbanization as main risk factors, with socio-economic factors like insurance coverage and poverty also important. These results reveal that current infrastructure underestimates biological loads during wet-weather events. The study sets a baseline for urban genomic health in South Bend, applicable to other cities. The large detected genomic bypass shows that monitoring lacks focus on genomic data, pointing to the need for high-frequency surveillance to track antimicrobial resistance. Ultimately, these findings suggest shifting from chemical-based regulation toward strategies informed by genomic and sociotechnical considerations in managing urban antibiotic resistance.