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Population as a Proxy for Infrastructure in the Determination of Event Response and Recovery Resource Allocations

Stamber Kevin L. (), Unis Carl J., Shirah Donald N., Gibson Jessica A., Fogleman William E. and Kaplan Paul
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Shirah Donald N.: Sandia National Laboratories, Albuquerque, NM, USA
Fogleman William E.: Geo-Relational Information Systems, Albuquerque, NM, USA
Kaplan Paul: Sandia National Laboratories, Albuquerque, NM, USA (retired)

Journal of Homeland Security and Emergency Management, 2016, vol. 13, issue 1, 35-50

Abstract: Research into modeling of the quantification and prioritization of resources used in the recovery of lifeline critical infrastructure following disruptive incidents, such as hurricanes and earthquakes, has shown several factors to be important. Among these are population density and infrastructure density, event effects on infrastructure, and existence of an emergency response plan. The social sciences literature has a long history of correlating the population density and infrastructure density at a national scale, at a country-to-country level, mainly focused on transportation networks. This effort examines whether these correlations can be repeated at smaller geographic scales, for a variety of infrastructure types, so as to be able to use population data as a proxy for infrastructure data where infrastructure data is either incomplete or insufficiently granular. Using the best data available, this effort shows that strong correlations between infrastructure density for multiple types of infrastructure (e.g. miles of roads, hospital beds, miles of electric power transmission lines, and number of petroleum terminals) and population density do exist at known geographic boundaries (e.g. counties, service area boundaries) with exceptions that are explainable within the social sciences literature. The correlations identified provide a useful basis for ongoing research into the larger resource utilization problem.

Keywords: disaster response; infrastructure density; modeling; population density; resource prioritization; resource quantification (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1515/jhsem-2015-0023

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