Flood-Disease ABM: A Multi-Pathway Agent-Based Model for Simulating Flood Disruption and Post-Flood Health Impacts Across the Disaster Lifecycle

Abstract. Flood health burdens extend beyond inundation through displacement, service disruption, contaminated environments, and delayed disease. These processes are often modeled separately or as cause–effect relationships, limiting analysis of feedbacks among human behavior, institutions, and post-flood health. We present the Flood-Disease Agent-Based Model (Flood-Disease ABM), a spatially explicit, hourly modeling framework that integrates flood exposure, human mobility, worldview-informed decision-making, institutional response, economic activity, quality of life, and infectious, vector-borne, and mold-related respiratory disease pathways. Decision-making is differentiated across hierarchist, egalitarian, individualist, and fatalist worldview orientations. A browser-based interactive app enables users to configure scenarios, populations, hazards, service capacity, and policy assumptions and to observe spatial and temporal outcomes. Complementary batch runners support reproducible replications of the same configurations. The framework is implemented for the flood-prone Uvalde, Texas, region using representations of households, businesses, schools, shelters, healthcare facilities, and government. Under the selected assumptions, the compound scenario produces an early flood-related healthcare peak followed by sustained disease-related demand during recovery; mold emerges after floodwater recession; spatially uneven shelter demand exceeds capacity at peak demand; financial stress shifts among households and institutions; and quality-of-life losses are greatest among children and lower-income groups. Results are model-based outcomes and not calibrated forecasts for Uvalde.