Understanding Social Equity in Infrastructure Systems Resilience

Natural hazards, such as flooding, hurricanes, wildfires, pose a threat to the well-being of communities by disrupting the infrastructure services people use in their day-to-day lives. The impacts of infrastructure service disruptions are not equal for all the affected households. In particular, socially vulnerable populations tend to suffer more from disaster-induced disruptions in infrastructure systems. Infrastructure resilience has been given growing attention for improving the performance of these systems in the face of disasters. However, current approaches fail to capture the disproportionate impacts and integrate social considerations in resilience assessments. Despite the advancements in the resilience and vulnerability assessment of infrastructure systems, there is a knowledge gap in understanding the societal impacts of infrastructure service disruptions and developing equitable approaches for resilience assessment of these systems. These limitations in considering the social equity considerations in resilience assessment of infrastructure systems are mainly due to 1) lack of empirical findings and theoretical frameworks for examining the societal impacts and 2) limited integrated modeling approaches to capture the emergent societal risks in the interconnected complex network of human-hazard-infrastructure. To overcome these challenges, I developed theoretical frameworks, provided empirical models, and created integrated computational models to understand the societal impacts of infrastructure service disruptions and enable equitable resilience assessment of infrastructure systems. In the first study, I proposed and tested a theoretical framework to examine the disproportionate impact of infrastructure service disruptions on the communities and conducted an exploratory analysis by analyzing household survey data from affected households to identify the determinants of risk disparity due to infrastructure service disruptions. The second study develop empirical survival models to provide an understanding of social susceptibility to infrastructure service disruptions and creates the survival curves for determining the extent of hardship communities face if the duration of service disruptions exceeds different levels. Lastly, the third study implements the empirical findings from the first two studies in addition to theoretical decision-making models to develop a multi-agent simulation model to capture the complex mechanisms leading to the societal impacts and develop equitable approaches for infrastructure resilience assessment. The created theories, findings, methodologies, and models in this research have significant contributions to the resilience and sustainability of infrastructure systems by enabling integration of societal needs, expectations, and social equity in infrastructure planning and prioritizations