An Interpretable Index of Social Vulnerability to Environmental Hazards (Short Paper)

Author Joseph V. Tuccillo



PDF
Thumbnail PDF

File

LIPIcs.GIScience.2023.74.pdf
  • Filesize: 2.07 MB
  • 6 pages

Document Identifiers

Author Details

Joseph V. Tuccillo
  • Oak Ridge National Laboratory, TN, USA

Cite AsGet BibTex

Joseph V. Tuccillo. An Interpretable Index of Social Vulnerability to Environmental Hazards (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 74:1-74:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.GIScience.2023.74

Abstract

Index-based measures of social vulnerability to environmental hazards are commonly modeled from composites of population-level risk factors. These models overlook individual context in communities' experiences of environmental hazards, producing metrics that may hinder spatial decision support for mitigating and responding to hazards. This paper introduces an interpretable, high-resolution model for generating an individual-oriented social vulnerability index (IOSVI) for the United States built on synthetic populations that couples individual and social determinants of vulnerability. The IOSVI combines an individual vulnerability index (IVI) that ranks individuals in an area’s synthetic population based on intersecting risk factors, with a social vulnerability index (SVI) based on the population’s cumulative distribution of IVI scores. Interpretability of the IOSVI procedure is demonstrated through examples of national, metropolitan, and neighborhood (census tract) level spatial variation in index scores and IVI themes, as well as an exploratory analysis examining risk factors affecting a specific sub-population (military veterans) in areas of high social and environmental vulnerability.

Subject Classification

ACM Subject Classification
  • Information systems → Geographic information systems
Keywords
  • Social Vulnerability
  • Environmental Hazard
  • Synthetic Population
  • Census
  • Veteran

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads

References

  1. W Neil Adger. Vulnerability. Global environmental change, 16(3):268-281, 2006. Google Scholar
  2. Susan L Cutter, Bryan J Boruff, and W Lynn Shirley. Social vulnerability to environmental hazards. Social science quarterly, 84(2):242-261, 2003. Google Scholar
  3. Oronde Drakes and Eric Tate. Social vulnerability in a multi-hazard context: a systematic review. Environmental research letters, 2022. Google Scholar
  4. David M Eddy, William Hollingworth, J Jaime Caro, Joel Tsevat, Kathryn M McDonald, and John B Wong. Model transparency and validation: a report of the ispor-smdm modeling good research practices task force-7. Medical Decision Making, 32(5):733-743, 2012. Google Scholar
  5. Alexander Fekete. Spatial disaster vulnerability and risk assessments: challenges in their quality and acceptance. Natural hazards, 61:1161-1178, 2012. Google Scholar
  6. Barry E Flanagan, Edward W Gregory, Elaine J Hallisey, Janet L Heitgerd, and Brian Lewis. A social vulnerability index for disaster management. Journal of homeland security and emergency management, 8(1), 2011. Google Scholar
  7. Alice Fothergill, Enrique GM Maestas, and JoAnne DeRouen Darlington. Race, ethnicity, and disasters in the united states: A review of the literature. Disasters, 23(2):156-173, 1999. Google Scholar
  8. Alice Fothergill and Lori A Peek. Poverty and disasters in the united states: A review of recent sociological findings. Natural hazards, 32(1):89-110, 2004. Google Scholar
  9. June L Gin, Claudia Der-Martirosian, Christine Stanik, and Aram Dobalian. Roadblocks to housing after disaster: homeless veterans’ experiences after hurricane sandy. Natural Hazards Review, 20(3):04019005, 2019. Google Scholar
  10. Ganlin Huang and Jonathan London. Mapping cumulative environmental effects, social vulnerability, and health in the san joaquin valley, california. American journal of public health, 102(5):830-832, 2012. Google Scholar
  11. Brenda Jones and Jean Andrey. Vulnerability index construction: methodological choices and their influence on identifying vulnerable neighbourhoods. International journal of emergency management, 4(2):269-295, 2007. Google Scholar
  12. Sang-Il Lee. Developing a bivariate spatial association measure: an integration of pearson’s r and moran’s i. Journal of geographical systems, 3:369-385, 2001. Google Scholar
  13. Zachary C Lipton. The mythos of model interpretability: In machine learning, the concept of interpretability is both important and slippery. Queue, 16(3):31-57, 2018. Google Scholar
  14. Binbin Lu, Paul Harris, Martin Charlton, and Chris Brunsdon. The gwmodel r package: further topics for exploring spatial heterogeneity using geographically weighted models. Geo-spatial Information Science, 17(2):85-101, 2014. Google Scholar
  15. Maria I Marshall, Linda S Niehm, Sandra B Sydnor, and Holly L Schrank. Predicting small business demise after a natural disaster: an analysis of pre-existing conditions. Natural Hazards, 79:331-354, 2015. Google Scholar
  16. Nicholas N Nagle, Barbara P Buttenfield, Stefan Leyk, and Seth Spielman. Dasymetric modeling and uncertainty. Annals of the Association of American Geographers, 104(1):80-95, 2014. Google Scholar
  17. New York City Department of Health and Mental Hygiene. Vulnerable populations: A function-based vulnerability measure for the new york city region. https://www1.nyc.gov/assets/doh/downloads/pdf/em/regional_hazards_vulnerability_measures.pdf, 2013.
  18. Alessandro Paro, J Madison Hyer, Adrian Diaz, Diamantis I Tsilimigras, and Timothy M Pawlik. Profiles in social vulnerability: the association of social determinants of health with postoperative surgical outcomes. Surgery, 170(6):1777-1784, 2021. Google Scholar
  19. Samuel Rufat, Eric Tate, Christopher T Emrich, and Federico Antolini. How valid are social vulnerability models? Annals of the American Association of Geographers, 109(4):1131-1153, 2019. Google Scholar
  20. Seth E Spielman, Joseph Tuccillo, David C Folch, Amy Schweikert, Rebecca Davies, Nathan Wood, and Eric Tate. Evaluating social vulnerability indicators: criteria and their application to the social vulnerability index. Natural hazards, 100:417-436, 2020. Google Scholar
  21. Joseph Tuccillo and James Gaboardi. Likeness: a toolkit for connecting the social fabric of place to human dynamics. Technical report, Oak Ridge National Lab.(ORNL), Oak Ridge, TN (United States), 2022. Google Scholar
  22. Joseph Tuccillo, Robert Stewart, Amy Rose, Nathan Trombley, Jessica Moehl, Nicholas Nagle, and Budhendra Bhaduri. Urbanpop: A spatial microsimulation framework for exploring demographic influences on human dynamics. Applied Geography, 151:102844, 2023. Google Scholar
  23. Joseph V Tuccillo and Seth E Spielman. A method for measuring coupled individual and social vulnerability to environmental hazards. Annals of the American Association of Geographers, 112(6):1702-1725, 2022. Google Scholar
  24. W. N. Venables and B. D. Ripley. Modern Applied Statistics with S. Springer, New York, fourth edition, 2002. ISBN 0-387-95457-0. URL: https://www.stats.ox.ac.uk/pub/MASS4/.
  25. Benjamin Wisner, Piers M Blaikie, Piers Blaikie, Terry Cannon, and Ian Davis. At risk: Natural Hazards, People’s Vulnerability, and Disasters. Psychology Press, 2004. Google Scholar
  26. Casey Zuzak, Matthew Mowrer, Emily Goodenough, Jordan Burns, Nicholas Ranalli, and Jesse Rozelle. The national risk index: establishing a nationwide baseline for natural hazard risk in the us. Natural Hazards, 114(2):2331-2355, 2022. Google Scholar
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail