USA - Assessing Social Equity in Disasters
Natural hazard impacts and resources allocated for risk reduction and disaster recovery are often inequitably distributed. New research is developing and applying methods to measure these inequities.
Disasters stemming from hazards like floods, wildfires, and disease often garner attention because of their extreme conditions and heavy societal impacts. Although the nature of the damage may vary, major disasters are alike in that socially vulnerable populations often experience the worst repercussions. For example, we saw this following Hurricanes Katrina and Harvey, each of which generated widespread physical damage and outsized impacts to low-income and minority survivors.
Social vulnerability researchers seek to understand the impediments and capacities of people and communities to prepare for, respond to, and recover from extreme natural hazards. A major tool in this work is social vulnerability modeling, the use of which is expanding in large part because of growing awareness of the social equity implications of disasters.
This modeling applies knowledge garnered from disaster case studies describing how chronic marginalization translates to disproportionate adverse outcomes to identify the most vulnerable population groups. Such populations often include those living in poverty, the very old and young, minoritized ethnic and racial groups, renters, and recent immigrants [National Academies of Sciences, Engineering, and Medicine, 2019]. Social vulnerability modelers select demographic variables representing these groups and combine them to construct spatial indicators and indexes that enable comparisons of social vulnerability across places.
Mapping Social Vulnerability
Figure 1a is a typical map of social vulnerability across the United States at the census tract level based on the Social Vulnerability Index (SoVI) algorithm of Cutter et al. . Spatial representation of the index depicts high social vulnerability regionally in the Southwest, upper Great Plains, eastern Oklahoma, southern Texas, and southern Appalachia, among other places. With such a map, users can focus attention on select places and identify population characteristics associated with elevated vulnerabilities.