53 Pages Posted: 21 Mar 2021 Last revised: 6 Aug 2021
Date Written: March 19, 2021
Vulnerability drives disaster law—defining its successes and illustrating its failures. Although understanding vulnerability is critical to disaster law and scholarship, the literature lacks both an overarching analysis of the different aspects of vulnerability and a nuanced examination of the factors that shape disaster outcomes. This paper attempts to fill those holes.
Despite its centrality to disaster law and policy, vulnerability often lurks in the shadows of a disaster, evident only once the worst is past and the bodies have been counted. The COVID-19 pandemic is a notable exception to this historical pattern: from the beginning of the pandemic, it has been clear that the virus poses different risks to different people, depending on different vulnerability variables. This most recent pandemic experience thus provides a useful vantage point for considering vulnerability in a more nuanced way and for illuminating how a data-driven approach to vulnerability could improve disaster policy more generally.
Drawing on new empirical data, as well as experience from past disasters, we introduce and develop three dimensions of vulnerability and their implications for policymakers. First, we explore the geography of vulnerability. Using statistical analysis and GIS mapping, our team of public health, statistics, and legal experts develops perhaps the most sophisticated and detailed empirical tool ever deployed to understand disaster vulnerability—an innovative COVID-19 vulnerability index that draws on a rich dataset and uses statistical modeling of case fatality rates to accurately identify the country’s most vulnerable counties. We then demonstrate how this vulnerability index could have been used to inform two critical and contentious policy decisions that occupied decision-makers from the onset of the pandemic: mask mandates and voter accommodations during the 2020 elections. Building upon the lessons of COVID-19, we then show how similar modeling and thinking could make disaster management more proactive—better able to anticipate needs and prioritize disaster mitigation and response resources.
Incorporating insights from our exploration of the geographic dimension of vulnerability, we then explore a second aspect of disaster vulnerability: competing or conflicting vulnerabilities. These are situations in which policymakers must navigate choices that require prioritizing one vulnerable group’s needs over another or one aspect of a group’s vulnerability over another. To illustrate these issues, we consider two other important problems that have challenged policymakers during the pandemic: school closures and vaccine distribution.
Finally, we explore political vulnerability. This analysis encompasses a variety of ways that disasters make already vulnerable groups even more vulnerable to certain kinds of harms, including political neglect, stigmatization, disenfranchisement, displacement, and other forms of exploitation. In particular, we consider how vulnerability data may be both an unintended roadmap for exploitation and an important check on disaster inequity. In sum, this Article draws upon the costly lessons of COVID-19 for the most vulnerable to suggest a more robust academic and policy framework for assessing and responding to vulnerability in future disasters.
Keywords: disaster, vulnerability, social vulnerability, COVID-19, GIS mapping
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