Abstract

Objectives:

To evaluate equity in wastewater-based infectious disease surveillance, including equity of inclusion, outbreak detection, and disease forecasting.

Methods:

We assessed New York State’s wastewater surveillance network using census tract–level data to compare social vulnerability and environmental burden across included, sewered but excluded, and unsewered communities during the scale-up of the network (2020–2024) and under changing coverage scenarios. We modeled outbreak detection equity by estimating outbreak sizes required for 95% confidence in the detection of hypothetical pathogens and assessed forecasting equity using county-level COVID-19 hospitalization predictions in relation to population size, coverage, and vulnerability.

Results:

We found similar vulnerability distributions between included and sewered but excluded communities. The 25% most vulnerable communities required median outbreak sizes 3.45 times larger for detection than did the 25% least vulnerable. At medium sensitivity, more than 80% of individuals living in poverty and minoritized populations lived in areas where outbreaks exceeded 10 infections before detection. Forecasting accuracy was lower in smaller (< 20%) than in larger urban (> 60%) counties and increased with population size and network coverage (P < .001).

Conclusions.

Wastewater surveillance was equitable in population coverage but not in outbreak detection and forecasting performance.

Public Health Implications:

Strategies such as upstream sampling, expanded wastewater treatment plant participation in smaller communities, and improved modeling for low-population areas may reduce inequities and enhance the utility of wastewater surveillance.