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

TL;DR

This paper presents a comprehensive agent-based simulation framework that models human mobility, defecation behavior, and disease transmission to improve interpretation of wastewater-based epidemiology data in urban environments.

Contribution

It introduces a novel integrated simulation model combining human behavior, disease spread, and pathogen shedding to better understand wastewater signals.

Findings

Varying infection rates affect epidemic trajectories and wastewater pathogen loads.

The model captures spatial-temporal dynamics of wastewater contamination.

Simulation results highlight the impact of mobility and behavior on wastewater signals.

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.