The COVID-19 pandemic proved that community resilience is not solely dependent on civil infrastructure. Several communities may never reach their pre-pandemic state due to socio-economic impacts, e.g., grief, anxiety, unemployment, etc. In this condition, social infrastructure (e.g., community-based institutions, NGOs, etc.) not only help alleviate post-disaster social distress in communities but also help address tangible needs (e.g., shelter, food, water, etc.). My research focuses on identifying the capacities and needs of the social infrastructure to achieve community resilience, taking community well-being as the recovery metric.
This presentation elaborates on the findings of a case study on post-disaster community well-being after Hurricane Harvey. In the case study, several data sources such as FEMA support programs, phone call, and survey data were used to quantify post-disaster community well-being benchmarked with pre-disaster well-being. Next, the role of social support in achieving higher community well-being was assessed using Bayesian Network Analysis. The Bayesian Model was then used to identify the required capacities for mobilizing post-disaster support to achieve certain levels of community well-being under different hazard scenarios.
The research introduces a new approach to incorporating socio-economic factors in measuring community resilience. The modeling framework addresses the static nature of indicator-based community resilience models by applying phone call data as a timely and inexpensive means to monitoring post-disaster community well-being. Spatial-temporal analysis of community well-being helped identify the disproportionate impacts of Hurricane Harvey on vulnerable populations. The proposed model can be employed to propose capacity buildings strategies to incentivize post-disaster return after hurricanes, which can have huge financial and social benefits for societies.
Ali Morshedi is currently a doctoral candidate at the Lyles School of Civil Engineering at Purdue University. He has earned his bachelor’s and master’s degree in civil engineering from Sharif University of Technology, one of the best engineering schools in Iran. After graduation, he worked for three years at the Center for Infrastructure Sustainability and Resilience (INSURER) at Sharif. During this time, he worked on developing simulation-based decision-support tools to understand the housing market dynamics in response to seismic retrofit promotion policies. During his tenure at Purdue University, Ali has actively participated in various research initiatives, both funded and non-funded. These efforts have resulted in multiple journal publications, conference presentations, and recognitions. His research is centered around incorporating socio-economic factors in measuring the resilience of communities in the face of natural hazards. His expertise spans diverse areas including risk analysis, community well-being, statistical, simulation, and machine learning models, and steel structures. Recently, he has been named Lyle’s Graduate Teaching Fellow by the School of Civil Engineering at Purdue University.