Marron Civic Analytics researchers Constantine Kontokosta, Boyeong Hong, and Bartosz Bonczak, along with NYU professor Arpit Gupta, have published “Measuring Inequality in Community Resilience to Natural Disasters Using Large-Scale Mobility Data” in Nature Communications. This study uses “800,000 anonymized mobile devices in Houston, Texas, representing approximately 35% of the local population, in response to Hurricane Harvey in 2017 to understand social inequities in disaster evacuation and recovery.” The goal of this research is to provide the “basis for data-driven public sector decisions that prioritize the equitable allocation of resources to vulnerable neighborhoods.” The authors write:
Understanding hyper-local disaster response is an important foundation for effective and equitable community planning and urban resilience strategies. Spatiotemporal evacuation and recovery patterns, represented by mobility dynamics before, during, and after a disaster, are directly connected to the socio-behavioral resilience of urban systems. This requires the identification and quantification of emergent mobility networks within and across neighborhoods impacted, directly or indirectly, by an event of sufficient magnitude to disrupt normal activity patterns. Since individuals and neighborhoods represent interconnected social and physical urban systems, their dynamics at high spatiotemporal resolution can signal local distress, growth, and recovery. This information can be used to assess disaster-related impacts and community resilience at scale and thus inform both operational emergency management decisions and long-range community planning and preparedness.