Wastewater-based epidemiology framework: Collaborative modeling for sustainable disease surveillance

Abstract

Many wastewater-based epidemiology (WBE) programs are being implemented worldwide due to their usefulness in monitoring residents' health. Modeling wastewater dynamics in outbreak scenarios can provide important data for designing wastewater surveillance plans. For outbreak modeling to be effective, researchers must coordinate with public health authorities and laboratory services, using frameworks to ensure that their modeling and output data are relevant for informed decision-making. However, theoretical and institutional frameworks typically omit modeling, and the connection between theoretical frameworks and models is often unrecognized. A framework that surpasses theoretical conceptualization for promoting collaboration between actors by integrating modeling can achieve the required synchrony toward sustainable wastewater surveillance plans. First, we build on an existing theoretical framework to create a collaborative framework that integrates modeling and suggests stakeholder activities for designing WBE programs. Then, we demonstrate our framework for developing a WBE plan via a COVID-19 case study where we answer when, how often, and where to sample wastewater to detect and monitor an outbreak. We evaluate the results in space and time for three outbreak phases (early detection, peak, and tail). The modeling outputs indicate the need for different sampling strategies for these outbreak phases. Our results also quantify the differences in the likelihood of capturing viral events in wastewater between the sampling hours at different disease phases for COVID-19 and various spatial locations in the sewer network. This framework lays the foundation for sustainable WBE to improve the detection efficiency of wastewater surveillance plans.