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1. How Valid Are Social Vulnerability Models?

   Rufat, S.; Tate, E.; Emrich, C.; and Antolini, F. (March 2019, Annals of the American Association of Geographers)

   Social vulnerability models are becoming increasingly important for hazard mitigation and recovery planning,but it remains unclear how well they explain disaster outcomes. Most studies using indicators and indexes employ them to either describe vulnerability patterns or compare newly devised measures to existing ones. The focus of this article is construct validation, in which we investigate the empirical validity of a range of models of social vulnerability using outcomes from Hurricane Sandy. Using spatial regression, relative measures of assistance applicants, affected renters, housing damage, and property loss were regressed on four social vulnerability models and their constituent pillars while controlling for flood exposure. The indexes best explained housing assistance applicants, whereas they poorly explained property loss. At the pillar level,themes related to access and functional needs, age, transportation, and housing were the most explanatory.Overall, social vulnerability models with weighted and profile configurations demonstrated higher construct validity than the prevailing social vulnerability indexes. The findings highlight the need to expand the number and breadth of empirical validation studies to better understand relationships among social vulnerability models and disaster outcomes. 

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2. State Hazard Mitigation Plans and Social Vulnerability

   https://doi.org/10.1515/jhsem-2024-0023  

   Painter, Mary Angelica; Villarreal, Melissa; Peek, Lori (January 2025, Journal of Homeland Security and Emergency Management)

   Abstract U.S. states, territories, and tribal areas develop State Hazard Mitigation Plans (SHMPs) to reduce the impact of disasters. The Federal Emergency Management Agency (FEMA) approves SHMPs every five years as required for states to receive disaster relief grants and mitigation project funding. In 2023, FEMA’s updated policy guidance for SHMPs took effect, recommending more robust use of social vulnerability as an assessment of equity in multi-hazard risk assessments. Such approaches are necessary because social vulnerability emerges from systemic inequities that result in marginalized populations facing disproportionate exposure and impacts from natural hazards. We developed two novel datasets on the different population groups, definitions, and measures of social vulnerability included in SHMPs for all 50 U.S. states and the 5 inhabited U.S. territories. Our analysis shows that states differ in terms of how (and if) social vulnerability is defined and measured. All plans include at least one vulnerable population in their guidance – most often the elderly, children, or people with disabilities. Inclusion of other populations such as immigrants, LGBTQIA + persons, or unhoused persons is much more varied. The study concludes with recommendations for how SHMPs can advance equitable and inclusive planning processes that center robust definitions and measures of social vulnerability and socially vulnerable populations. 

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3. Personality Traits as Predictors for Social Engineering Vulnerability

   Imanaka, J.; Ogawa, M.B; Crosby, M.E. (September 2023, International Conference on Human-Computer Interaction)

   Schmorrow, D.; Fidopiastis, C. (Ed.)

   As security measures to protect against cyberattacks increase, hackers have begun to target the weakest link in the cybersecurity chain–people. Such attacks are categorized as Social Engineering and rely on the manipulation and deception of people rather than technical security flaws [4]. This study attempts to examine the relationship between people and their vulnerability to Social Engineering attacks by posing the following questions: (1) what relationship, if any, exists between personality traits and Social Engineering vulnerability, and (2) what relationship, if any, exists between personality traits and the speed at which an individual makes cybersecurity-related decisions. To answer these questions, 79 undergraduate students at the University of Hawaii were surveyed to measure their personality traits and cybersecurity awareness. The survey results indicated that there was no significant correlation between the measured personality traits and measured vulnerability. The relationship between different personality traits and the elapsed time to complete the survey was slightly more significant; how-ever, it was still statistically insignificant overall. 

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4. 2016-2021 State Hazard Mitigation Plans and Social Vulnerability

   https://doi.org/10.17603/ds2-sc34-as63  

   Painter, Mary Angelica; Villarreal, Melissa; Peek, Lori (January 2023, Designsafe-CI)

   This dataset includes information regarding 55 State Hazard Mitigation Plans (SHMPs) for all 50 U.S. states and the 5 inhabited U.S. territories. Washington DC’s SHMP is not publicly available and can only be accessed through signing a Non-Disclosure Agreement. As such, it is not included in our dataset. These plans were approved by FEMA between 2016-2021. This data publication includes: (1) the State Hazard Mitigation Plan dataset; (2) a data dictionary with description of each variable output; and (3) variable definitions for the population groups included in State Hazard Mitigation Plans. The dataset was generated through reviewing publicly available plans and coding for socially vulnerable populations. This dataset allows for quantitative analysis of the inclusion (or exclusion) of vulnerable populations in SHMPs. The envisioned audience for this data and information includes government officials, researchers, and others who are interested in understanding patterns in the inclusion or exclusion of socially vulnerable populations in SHMPs. 

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5. Integrating Social Equity and Vulnerability with Infrastructure Resilience Assessment

   https://doi.org/10.1061/9780784483954.031  

   Dhakal, Sunil; Zhang, Lu (March 2022, Construction Research Congress 2022)