  To enable integrating social equity considerations in infrastructure
resilience assessments, this study created a new computational multi-agent
simulation model which enables integrated assessment of hazard, infrastructure
system, and household elements and their interactions. With a focus on
hurricane-induced power outages, the model consists of three elements: 1) the
hazard component simulates exposure of the community to a hurricane with
varying intensity levels; 2) the physical infrastructure component simulates
the power network and its probabilistic failures and restoration under
different hazard scenarios; and 3) the households component captures the
dynamic processes related to preparation, information seeking, and response
actions of households facing hurricane-induced power outages. We used empirical
data from household surveys in conjunction with theoretical decision-making
models to abstract and simulate the underlying mechanisms affecting experienced
hardship of households. The multi-agent simulation model was then tested in the
context of Harris County, Texas, and verified and validated using empirical
results from Hurricane Harvey in 2017. Then, the model was used to examine
effects of different factors such as forewarning durations, social network
types, and restoration and resource allocation strategies on reducing the
societal impacts of service disruptions in an equitable manner. The results
show that improving the restoration prioritization strategy to focus on
vulnerable populations is an effective approach, especially during
high-intensity events. The results show the capability of the proposed
computational model for capturing the dynamic and complex interactions in the
nexus of humans, hazards, and infrastructure systems to better integrate
human-centric aspects in resilience planning and into assessment of
infrastructure systems in disasters.
