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Documents authored by Tuccillo, Joseph V.


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Short Paper
Building Alternative Indices of Socioeconomic Status for Population Modeling in Data-Sparse Contexts (Short Paper)

Authors: Angela R. Cunningham, Joseph V. Tuccillo, and Tyler J. Frazier

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)


Abstract
Population modeling requires clear definitions of socioeconomic status (SES) to ensure overall estimate accuracy and locate potentially underserved subpopulations. This presents a challenge as SES can be measured in myriad ways and for divergent purposes, and the data required to calculate these metrics may be lacking, particularly in low and middle income countries (LMICs). To support more refined SES measurement, we explore improvements upon the Demographic and Health Survey’s (DHS) Wealth Index (DHS-WI) using alternative characterizations of SES based on multiple correspondence analysis (MCA) and hierarchical clustering. We produce the MCA-derived metrics first on a full suite of household economic, demographic, and dwelling variables, then on a reduced set of occupant-only SES characteristics. We explore the utility of these metrics relative to DHS-WI based on their ability to 1) differentiate DHS household types and 2) identify mixtures of SES levels within DHS samples and mapped at high spatial resolution. We find that our full suite MCA yields more clearly defined SES segments and that our reduced MCA delineates occupant SES most clearly, suggesting potential pathways to improve upon the DHS-WI in future population modeling efforts for LMICs.

Cite as

Angela R. Cunningham, Joseph V. Tuccillo, and Tyler J. Frazier. Building Alternative Indices of Socioeconomic Status for Population Modeling in Data-Sparse Contexts (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 25:1-25:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{cunningham_et_al:LIPIcs.GIScience.2023.25,
  author =	{Cunningham, Angela R. and Tuccillo, Joseph V. and Frazier, Tyler J.},
  title =	{{Building Alternative Indices of Socioeconomic Status for Population Modeling in Data-Sparse Contexts}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{25:1--25:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.25},
  URN =		{urn:nbn:de:0030-drops-189204},
  doi =		{10.4230/LIPIcs.GIScience.2023.25},
  annote =	{Keywords: Demographic and Health Survey, multiple correspondence analysis, population modeling, socioeconomic status, spatial statistics}
}
Document
Short Paper
An Interpretable Index of Social Vulnerability to Environmental Hazards (Short Paper)

Authors: Joseph V. Tuccillo

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)


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.

Cite as

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)


Copy BibTex To Clipboard

@InProceedings{tuccillo:LIPIcs.GIScience.2023.74,
  author =	{Tuccillo, Joseph V.},
  title =	{{An Interpretable Index of Social Vulnerability to Environmental Hazards}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{74:1--74:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.74},
  URN =		{urn:nbn:de:0030-drops-189699},
  doi =		{10.4230/LIPIcs.GIScience.2023.74},
  annote =	{Keywords: Social Vulnerability, Environmental Hazard, Synthetic Population, Census, Veteran}
}
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