Implementation of social equity metrics in an engineering-based framework for distributing disaster resources

Abstract

Evidence has shown that populations within diverse communities are affected by natural hazards and disasters disproportionately. Critically, it is suggested that it is the fault of pre-existing socioeconomic conditions and systemic discrimination which lead to such inequitable disaster outcomes, as geophysical phenomena themselves are unable to discriminate between peoples. Despite this understanding, limited studies have been conducted in developing a systematic procedure for alleviating the inequities of disasters; a review of the concepts of equity and equality in the context of disaster resilience is presented.Given these issues, a novel framework for designing disaster resource distributions has been proposed. The Societally-Informed Optimization of Resource Distributions (SIORD) framework provides guidance on designing resource distributions which lead to equitable disaster outcomes. This framework uses both physical and societal indicators to model the characteristics of a community and to predict the resulting population impacts of a given natural hazard event. Computational optimization, through the use of genetic algorithms, serves as the main analytic tool for designing societally fair resource distributions. In order to place social equity metrics as the primary objective function, a novel measurement of social equity in a disaster setting was developed, and ready-to-use social equity metrics are described for use in the framework. Recommendations are provided towards the framework's implementation into practice in the context of the United States.