Wastewater Treatment Plants as Representative Sentinel Sites in Infectious Disease Surveillance
- 1Syracuse University
Abstract
Wastewater-based epidemiology (WBE) has emerged as a powerful population-level surveillance tool, but its coverage is structurally concentrated in in-network urban areas, potentially leaving rural populations underrepresented. Routine human movement between sewered (in-network) and unsewered (off-network) areas may, however, cause wastewater treatment plant (WWTP) measurements to reflect infectious disease dynamics beyond sewer boundaries. We evaluated this hypothesis using daily clinical COVID-19 testing data (January 2021-April 2022) across New York State excluding New York City (NYC). We disaggregated weekly cases and tests into in- network (WWTP catchment area) and off-network (outside WWTP catchment area) components applied to two geographic frameworks: administrative counties (N = 53 mixed-coverage) and mobility-defined communities identified through Walktrap community detection applied to census tract-level movement networks (N = 32 mixed-coverage). In/off-network COVID-19 trends were strongly correlated under both frameworks. County-level statewide aggregate correlations were high (incidence r = 0.994, positivity r = 0.996), as were individual county correlations (median r = 0.909 and 0.932, respectively). Mobility-defined community-level statewide correlations were similarly strong (r = 0.990 and 0.992), with comparable unit-level medians (r = 0.877 and 0.894). The mobility-defined community framework provided better population balance between in-network and off-network strata (87.5% vs. 69.8% in balanced range) and a higher floor on representativeness (minimum r = 0.440 vs. 0.177). Population size was the dominant predictor of in-network/off-network alignment at both scales; wastewater infrastructure density and off-network signal variability provided additional explanatory power at the mobility-defined community level. WWTPs broadly represent COVID-19 dynamics in surrounding off-network populations, supporting their use as sentinel surveillance sites. Representativeness weakens in smaller, more rural communities, and mobility-defined communities provide a complementary framework for identifying where this occurs.
Significance StatementMunicipal wastewater samples can be tested for infectious diseases circulating in sewered populations, but most surveillance systems exclude rural communities lacking sewer connections. Using clinical COVID-19 data from New York State, we demonstrate that routine human movement between in-network and off-network areas causes wastewater signals to reflect disease dynamics across sewer boundaries. In-network and off-network epidemic trends were highly correlated across both counties and mobility-defined communities, and testing wastewater can effectively surveil infectious diseases among populations beyond the limits of wastewater infrastructure. However, representativeness weakens in smaller communities, and 42% of mobility-defined communities have no wastewater infrastructure. Expanding wastewater surveillance to rural facilities should be treated as a surveillance-equity priority to ensure equitable early-warning capabilities for all communities.
Related
- Second-year sentinel surveillance of bacterial meningitis in Jordan, Egypt, and Iraq: year 2 findings from the MenMap Network (2024–2025)
- Community-Level Wastewater Surveillance of Nicotine Biomarkers Tracks Cardiovascular Disease Burden and Myocardial Infarction
- Development and Evaluation of a Regional Health Information Exchange (HIE)-Based Platform for Population-Level Infectious Disease Surveillance
- Measuring infectious disease stigma in the German population: Psychometric properties of stigma scales related to COVID-19, Long Covid and non-vaccination in a representative population sample.
- A bilateral US-UK airplane wastewater monitoring pilot demonstrates the feasibility of an international wastewater surveillance network
BibTeX
@misc{fiatsonu2026wastewater,
title = {{Wastewater Treatment Plants as Representative Sentinel Sites in Infectious Disease Surveillance}},
author = {E. Fiatsonu and D. Hill and D. Christopher and D. Larsen},
howpublished = {medRxiv},
year = {2026},
month = aug,
doi = {10.64898/2026.08.27.26361522},
url = {https://www.medrxiv.org/content/10.64898/2026.08.27.26361522v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Wastewater Treatment Plants as Representative Sentinel Sites in Infectious Disease Surveillance
AU - E. Fiatsonu
AU - D. Hill
AU - D. Christopher
AU - D. Larsen
PY - 2026
DA - 2026/08/27
PB - medRxiv
DO - 10.64898/2026.08.27.26361522
UR - https://www.medrxiv.org/content/10.64898/2026.08.27.26361522v1
AB - Wastewater-based epidemiology (WBE) has emerged as a powerful population-level surveillance tool, but its coverage is structurally concentrated in in-network urban areas, potentially leaving rural populations underrepresented. Routine human movement between sewered (in-network) and unsewered (off-network) areas may, however, cause wastewater treatment plant (WWTP) measurements to reflect infectious disease dynamics beyond sewer boundaries. We evaluated this hypothesis using daily clinical COVID-19 testing data (January 2021-April 2022) across New York State excluding New York City (NYC). We disaggregated weekly cases and tests into in- network (WWTP catchment area) and off-network (outside WWTP catchment area) components applied to two geographic frameworks: administrative counties (N = 53 mixed-coverage) and mobility-defined communities identified through Walktrap community detection applied to census tract-level movement networks (N = 32 mixed-coverage). In/off-network COVID-19 trends were strongly correlated under both frameworks. County-level statewide aggregate correlations were high (incidence r = 0.994, positivity r = 0.996), as were individual county correlations (median r = 0.909 and 0.932, respectively). Mobility-defined community-level statewide correlations were similarly strong (r = 0.990 and 0.992), with comparable unit-level medians (r = 0.877 and 0.894). The mobility-defined community framework provided better population balance between in-network and off-network strata (87.5% vs. 69.8% in balanced range) and a higher floor on representativeness (minimum r = 0.440 vs. 0.177). Population size was the dominant predictor of in-network/off-network alignment at both scales; wastewater infrastructure density and off-network signal variability provided additional explanatory power at the mobility-defined community level. WWTPs broadly represent COVID-19 dynamics in surrounding off-network populations, supporting their use as sentinel surveillance sites. Representativeness weakens in smaller, more rural communities, and mobility-defined communities provide a complementary framework for identifying where this occurs. Significance StatementMunicipal wastewater samples can be tested for infectious diseases circulating in sewered populations, but most surveillance systems exclude rural communities lacking sewer connections. Using clinical COVID-19 data from New York State, we demonstrate that routine human movement between in-network and off-network areas causes wastewater signals to reflect disease dynamics across sewer boundaries. In-network and off-network epidemic trends were highly correlated across both counties and mobility-defined communities, and testing wastewater can effectively surveil infectious diseases among populations beyond the limits of wastewater infrastructure. However, representativeness weakens in smaller communities, and 42% of mobility-defined communities have no wastewater infrastructure. Expanding wastewater surveillance to rural facilities should be treated as a surveillance-equity priority to ensure equitable early-warning capabilities for all communities.
ER -