Review of Empirical Quantitative Data Use in Lifeline Infrastructure Restoration Modeling

Disaster recovery is widely regarded as the least understood phase of disaster cycle. In particular, literature around lifeline infrastructure restoration modeling frequently mentions lack empirical quantitative data available. Despite limitations, there a growing body research on restoration, often developed using data. This study reviews this and identifies collection usage patterns present across approaches to inform future efforts We classify into simulation, optimization, statistical modeling. The number publications in domain has increased over time with most rapid growth Electricity modeled, followed by multiple infrastructures, water infrastructure, transportation infrastructure. Interdependency between infrastructures increasingly considered recent literature. Researchers gather from variety sources, including collaborations utility companies, national databases, post-event damage reports. provides discussion recommendations practices within field. Following would facilitate development community practice provide greater opportunities for sharing.