Automated Neighborhood Characteristics for Community Resilience Planning

Sociodemographic characteristics, such as race and ethnicity, have been shown to have a strong correlation with community resilience. Evidence suggests that neighborhoods with higher concentrations of Black and Hispanic households experience increased negative impacts and slower recoveries. While post disaster field researchers attempt to collect information on household demographic characteristics, this data may not be available for many households not present during survey data collection, especially households that have been dislocated from their homes for extended periods of time. Census block group data may provide a proxy for the missing household characteristics. This project provides example code that automates the process to obtain, clean, and explore census block group data. The data outputs include csv files required to run a post disaster population dislocation model currently in use by IN-CORE. This project applies the code to six community testbeds (Seaside, OR; Joplin, MO; Galveston, TX; Lumberton, NC; Memphis MSA; and Mobile, AL) to illustrate the generalizability of the code. The code utilizes Census API and may be modified to identify some of the socio-demographic and socio-economic characteristics of a neighborhood's social vulnerability.