Where do We Poop? City-Wide Simulation of Defecation Behavior for Wastewater-Based Epidemiology

2026-01-03

AI Summary

This study addresses a critical limitation in conventional wastewater-based epidemiology, which assumes static populations and excretion exclusively at residential locations, thereby neglecting daily human mobility, social interactions, and heterogeneity in toileting behaviors—factors that can lead to misinterpretation of upstream wastewater signals. To overcome this, the authors propose a city-scale agent-based geospatial simulation framework that, for the first time, integrates real human mobility trajectories, social networks, physiologically driven defecation cycles, infectious disease transmission dynamics, and pathogen shedding models. By coupling the Patterns of Life behavioral model with geographic information systems, the framework achieves high-fidelity reproduction of epidemic progression and spatiotemporal dynamics of pathogen loads in wastewater within a 10,000-agent simulation of Fulton County, substantially enhancing the spatial resolution of wastewater signals and transcending the constraints of the static residential assumption.

Technology Category

• Multiagent Systems: Agent-Based Simulation and Emergent Behavior
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Cognitive Modeling & Cognitive Systems: Agent Architectures

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Web Mining and Content Analysis: Web data generation and simulation
• Social Networks and Social Media: Computational social science

Abstract

Wastewater surveillance, which regularly examines the pathogen biomarkers in wastewater samples, is a valuable tool for monitoring infectious diseases circulating in communities. Yet, most wastewater-based epidemiology methods, which use wastewater surveillance results for disease inferences, implicitly assume that individuals excrete only at their residential locations and that the population contribute to wastewater samples are static. These simplifying assumptions ignore daily mobility, social interactions, and heterogeneous toilet use behavior patterns, which can lead to biased interpretation of wastewater results, especially at upstream sampling locations such as neighborhoods, institutions, or buildings. Here, we introduce an agent-based geospatial simulation framework: Building on an established Patterns of Life model, we simulate daily human activities, mobility, and social contacts within a realistic urban environment and extend this agent-based framework with a physiologically motivated defecation cycle and toilet usage patterns. We couple this behavioral model with an infectious disease model to simulate transmissions through spatial and social interactions. When a defecation occurs for an infected agent, we use a pathogen shedding model to determine the amount of pathogen shed in the feces. Such a framework, integrating population mobility, disease transmission, toilet use behavior, and pathogen shedding models, is capable to simulate the Spatial-temporal dynamics of wastewater signals for a city. Using a case study of 10,000 simulated agents in Fulton County, Georgia, we examine how varying infection rates alter epidemic trajectories, pathogen loads in wastewater, and the spatial distribution of contamination across time.

Problem

• wastewater-based epidemiology
• defecation behavior
• population mobility
• toilet usage patterns
• spatial bias

Innovation

• agent-based modeling
• wastewater-based epidemiology
• human mobility
• defecation behavior
• pathogen shedding