Vulnerability of Renters and Low-Income Households to Storm Damage: Evidence From Hurricane Maria in Puerto Rico

Abstract

Objectives. To identify disparities in home damage from Hurricane Maria among Puerto Rican households with different housing tenure and income levels. Methods. Using household inspection data obtained by the Federal Emergency Management Agency (FEMA), including an ordinal damage severity measure, we used generalized ordered logistic regression to estimate the relative risks of damage severities between renters and homeowners, and between households with different incomes. Results. With respect to the FEMA damage-severity classifications of “minor,” “major,” and “destroyed,” renters were more at risk than homeowners for both “major-or-destroyed” and “destroyed” outcomes. Similarly, lower-income households were at greater risk for both “major-or-destroyed” and “destroyed” outcomes. When we allowed for an interaction between income and housing tenure, the difference in risk of “destroyed” outcomes between renters and homeowners was substantially greater at lower income levels. Conclusions. These results provide evidence at the individual household level that renters and lower-income households are most vulnerable to hurricane damage. Our interaction results suggest that lower-income renters are particularly vulnerable to severe home damage. Public Health Implications. Disaster preparedness policies should raise structural standards for low-income housing to reduce risks of severe damage.

Risky Development: Increasing Exposure to Natural Hazards in the United States

“…Finally, we separately calculated the relative proportion of vulnerable to total structures in areas where the differences between flood depths in the undefended and defended models were <−0.5, −0.5 to 0, 0–0.5, and >0.5 m. Vulnerable land use refers to unsafe structures, properties with large numbers of inhabitants, and critical/institutional facilities, that is, mobile homes, trailer parks; multi‐family dwellings; welfare, social‐service, and low‐income housing; apartment buildings with more than 100 units; high‐rise apartments; boarding and rooming houses; transient lodging; motels; medical buildings, and clinics; private and public hospitals; public‐health care facilities, nursing, rest, convalescent, handicap, and retired homes; residential group homes; public schools, and correctional facilities. We selected these groups based on land‐use types that were identified in the literature as particularly vulnerable to hazards (Cutter, Boruff, & Shirley, 2003 ; Ma & Smith, 2020 ; Petal, 2004 ; Segal et al., 2017 ; Wilson et al., 2019 ).…”

“…based on land-use types that were identified as particularly vulnerable to hazards in the literature (Cutter et al, 2003;Petal, 2004;Segal et al, 2017;Wilson et al, 2019;Ma & Smith, 2020).…”

When disaster management agencies create disaster risk: a case study of the US's Federal Emergency Management Agency

“…Laska et al (2018) explains that FEMA's recovery framework centers on (typically wealthier) homeowners while routinely leaving out (typically lower-income) renters. Yet, in the case of Hurricane Maria, Ma and Smith (2020) find renters, many of whom were lowerincome, suffered substantially more damage than homeowners: "Even though renters constituted less than 8% of the primary residents experiencing structural damage, nearly two-thirds (66%) of the 8,802 homes suffering major damage were renter-occupied" (Ma and Smith, 2020). Logan (2006) similarly found that neighborhoods in New Orleans with higher percentages of renters tended to suffer higher rates of home damage following Hurricane Katrina (Logan, 2006).…”

“…Such differences in access to FEMA resources appear consistent over time. For instance, in their article on response to Hurricane Andrew, which occurred in 1995, Cherry and Cherry (1997) described a disregard for certain marginalized populations and for lowersocioeconomic categories such as renters; over 30 years later, a series of studies on more recent disasters has arrived at similar conclusions (Koch et al, 2017;Ma and Smith, 2020;Domingue and Emrich, 2019).…”

Quantifying the Role of Vulnerability in Hurricane Damage via a Machine Learning Case Study

“…Since Hurricane María passed diagonally across the center of Puerto Rico, all structures were exposed to some degree of wind forcing, revealing areas of poor infrastructure investment and high structural vulnerability. Ma and Smith (2020) analyzed Individual Assistance data from the Federal Emergency Management Agency (FEMA) and determined that María's wind was the cause of 99% of the destroyed homes in Puerto Rico. They also concluded that renters and lower income populations sustained higher levels of damage than homeowners or higher income households.…”