Susceptibility curves for humans: Empirical survival models for determining household-level disturbances from hazards-induced infrastructure service disruptions

Abstract

Abstract In natural hazard engineering, fragility curves are used to determine the likelihood of damage to an engineered system under different magnitudes of hazard intensity. Analogous to fragility curves for engineered systems, survival models developed in the present study determine the extent of disturbances for shelter-in-place households caused by infrastructure service disruptions during disasters. This study used empirical data from household surveys collected in the aftermath of Hurricane Harvey, Hurricane Florence, and Hurricane Michael to create empirical survival models for determining household-level disturbances related to eight infrastructure services: power, water, communication, sewer systems, transportation, solid waste collection, grocery stores, and healthcare facilities. The survival models considered various influencing factors, such as sociodemographic factors, previous experience, risk perception, and access to resources to determine what percentage of households in a community would experience considerable hardship under varying durations of service disruptions. The developed curves suggested that although the susceptibility patterns are similar for short durations of infrastructure service disruptions, prolonged service disruptions pose varying levels of disturbance in different communities based on the household characteristics and contextual factors. Susceptibility curves could be implemented with current tools for assessing the reliability and resilience of infrastructure systems to promote understanding of the societal impacts that disruptions in these services pose to the affected communities. The resulting empirical survival models provide necessary tools and insights for determining the susceptibility of communities to disruptions of various infrastructure services during disasters. Hence, the outcomes of this study provide new empirical insights and models enabling decision-makers to integrate human-centric dimensions into infrastructure retrofit and restoration processes to more equitably reduce societal impacts of service disruptions. Such human-centric approaches enable designing socially resilient cities and contribute to designing sustainable infrastructure systems.