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Diasporas and diaspora non-governmental organisations (NGOs) are increasingly important as resource lifelines to their home countries, yet the resources that they mobilise, the types of challenges that they face, and their coping mechanisms are not well explored or understood in the context of disaster recovery. To fill this knowledge gap, this study employed an inductive qualitative methodological approach, using interviews to comprehend the role played by Haitian diaspora NGOs after the catastrophic earthquake in 2010. It found that resources take four common forms: event fundraisers; financial and material donations from supporters; remittances; and volunteer labour. Challenges include an overreliance on diaspora donors, competition among NGOs, and what is perceived as inequitable funding practices towards diaspora NGOs. The findings provide insights centred on better coordination among diaspora NGOs, as well as between diaspora NGOs and other local and international NGOs and local governments and international institutions, to ensure more efficient delivery of services to survivors. 

Hurricanes and extreme weather events can cause widespread damage and disruption to infrastructure services and consequently delay household and community recovery. A subset of data from a cross-sectional survey of 989 households in central and south Florida is used to examine the effects of Hurricane Irma on post-disaster recovery eight months after the landfall. Using logistic regression modeling, we find that physical damage to property, disruption of infrastructure services such as loss of electric power and cell phone/internet services and other factors (i.e., homeowner’s or renter’s insurance coverage, receiving disaster assistance and loss of income) are significant predictors of post-disaster recovery when controlling for age and race/ethnicity. 

Disasters may have significant and lasting impacts on educational programs and academic achievement, yet the examination of differing patterns of school recovery after disasters is understudied. This paper focused on two aims: (i) identification of school academic recovery trajectories; and (ii) examination of potential risk factors associated with these trajectories. We used latent class growth analysis to identify school academic recovery trajectories for a cohort of 462 Texas public schools that were in the path of Hurricane Ike in 2008. Using Texas Assessment of Knowledge and Skills (TAKS) data from 2005 to 2011, we found that attendance and percent of economically disadvantaged youth emerged as significant risk factors for two identified academic recovery trajectories (High-Stable and Low-Interrupted). Higher levels of economically disadvantaged youth were associated with lower likelihood of falling in the High-Stable trajectory, relative to the Low-Interrupted trajectory. Higher levels of attendance were associated with higher likelihood of membership in the High-Stable trajectory, relative to the Low-Interrupted trajectory. These findings are consistent with the notion that disasters do not affect all people or communities equally. Findings highlight the need for policy initiatives that focus on low performing schools, as these schools are at highest risk for adverse outcomes post-disaster. 

Large-scale damage to the power infrastructure from hurricanes and high-wind events can have devastating ripple effects on infrastructure, the broader economy, households, com- munities, and regions. Using Hurricane Irma’s impact on Florida as a case study, we examined: (1) differences in electric power outages and restoration rates between urban and rural counties; (2) the duration of electric power outages in counties exposed to tropical storm force winds versus hurricane Category 1 force winds; and (3) the rela- tionship between the duration of power outage and socioeconomic vulnerability. We used power outage data for the period September 9, 2017–September 29, 2017. At the peak of the power outages following Hurricane Irma, over 36% of all accounts in Florida were without electricity. We found that the rural counties, predominantly served by rural electric cooperatives and municipally owned utilities, experienced longer power outages and much slower and uneven restoration times. Results of three spatial lag models show that large percentages of customers served by rural electric cooperatives and municipally owned utilities were a strong predictor of the duration of extended power outages. There was also a strong positive association across all three models between power outage duration and urban/rural county designation. Finally, there is positive spatial dependence between power outages and several social vulnerability indicators. Three socioeconomic variables found to be statistically significant highlight three different aspects of vulnerability to power outages: minority groups, population with sensory, physical and mental disability, and economic vulnerability expressed as unemployment rate. The findings from our study have broader planning and policy relevance beyond our case study area, and highlight the need for additional research to deepen our understanding of how power restoration after hurricanes contributes to and is impacted by the socioeconomic vulnerabilities of communities.