ABSTRACT
The intensity of extreme events like hurricanes is predicted to increase. As such, the role of federal disaster aid programmes in assisting community recovery will also grow, and potential inequities in these programmes could compound in an increasing disaster landscape. This study analyzes recovery efforts after Hurricane Florence (2018) to identify trends in areas that were targeted for recovery aid. Using a series of Ordinary Least Square (OLS) and spatial lag models, divergences in aid are investigated after controlling for physical damage and the study suggests that these divergences can be partially predicted by social and community factors, including characteristics that are typically associated with increased social vulnerability (such as high renter population, older housing stock, and high population of non-white residents). In addition, because North Carolina experienced two major hurricanes in the period of just two years (Hurricane Matthew in 2016), this study also analyzes the role of successive extremes in the outcomes of aid concentration and finds that communities successful in achieving aid after Hurricane Matthew were similarly successful after Hurricane Florence. Finally, the paper emphasises the importance of monitoring potential inequities in federal recovery aid payout, which can provide actionable opportunities for potential improvements to these programmes.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
These analyses were derived from publicly available data as noted in the references. Detailed methodological information is available from the corresponding author upon reasonable request.
Notes
1 This product uses the Federal Emergency Management Agency’s OpenFEMA API, but is not endorsed by FEMA. The Federal Government or FEMA cannot vouch for the data or analyses derived from these data after the data have been retrieved from the Agency's website(s).