Spatial aggregation methods for interpreting wastewater concentrations at jurisdictional scales

[摘要] Spatial aggregation of wastewater concentrations is necessary to summarize wastewater monitoring data across multiple wastewater treatment plants (WWTPs) because public health practitioners often enact public health action at broader spatial scales. We applied various approaches for spatially aggregating wastewater concentrations and evaluated how well aggregated wastewater metrics correlated with clinical disease metrics on the same spatial scale. We used wastewater SARS-CoV-2 RNA concentrations from two wastewater monitoring programs. One included 188 WWTPs across the USA and a single laboratory; the other included 78 WWTPs across California and two distinct laboratories. We spatially aggregated wastewater concentrations across WWTPs using the following approaches: median, unweighted average, and population-weighted average. We considered wastewater concentrations with and without normalization by pepper mild mottle virus RNA concentrations and with and without transformation using the wastewater viral activity level prior to aggregation. For the single laboratory program, we spatially aggregated wastewater concentrations to the state, Health and Human Services (HHS) region, and USA spatial scales. For the multi-laboratory program, we spatially aggregated wastewater concentrations to the county and state (California) spatial scales. We then assessed the correlation between spatially aggregated wastewater metrics and clinical COVID-19 test positivity on a weekly basis for the following spatial scales: California, HHS region, and USA. Wastewater metrics and test positivity were positively and significantly correlated using all spatial aggregation methods at each spatial scale considered (median tau: 0.56; range: 0.39–0.72; p < 0.0001), and no method was superior. Public health practitioners should adopt a spatial aggregation method that is suitable for the setup of a wastewater monitoring program.

[发布日期] 2026-09-11