RecoveryHelp from friends key to natural disaster recovery

Published 12 October 2018

Natural disasters are life-changers for all involved, and understanding why some communities recover faster than others can be better achieved by looking at both the social and physical networks within these communities and their interplay, according to a four-year study.

Natural disasters are life-changers for all involved, and understanding why some communities recover faster than others can be better achieved by looking at both the social and physical networks within these communities and their interplay, according to a four-year Purdue University study of Hurricane Sandy.

Hurricane Sandy caused the deaths of more than 230 people and caused nearly $70 billion in damage when it hit the Northeastern United States in 2012.

Following the study, the researchers report that family members, friends, neighbors, area organizations and the overall preparedness of a community need to be considered in expediting recovery from disasters, in addition to the attention to the infrastructure, financial and environmental aspects. A video about the study can be viewed here.

“The goal of the project is to understand why some communities recover faster than others after a natural disaster and develop transferable tools to model the recovery of communities by considering interdependencies across multi-layered networks,” said Satish Ukkusuri, the project’s principal investigator and a professor in Purdue’s Lyles School of Civil Engineering. “We typically think the government should be the one to provide these things, but what we found is the people rely more on each other. When a disaster hits, the communities that recovered faster were the ones that already had strong societal connections and better financial resources before the disaster.”

Purdue says that the interdisciplinary Purdue research team applied a number of advanced simulations and game-theory algorithms in the study. The team also is developing a number of advanced network models and algorithms by analyzing millions of social media posts, millions of cell phone call data, survey data and focus group information gathered from communities along the New Jersey shore, which was devastated by Hurricane Sandy. Laura Siebeneck, an associate professor in the University of North Texas Department of Emergency Management and Disaster Science, served on the project team as well. Purdue graduate students also assisted with the project.