Predictive modelling of fuel shortages during hurricane evacuation: An epidemiological approach

High-volume evacuations, disruptions to the supply chain, and fuel hoarding from non-evacuees have led to localized fuel shortages lasting several days during recent hurricanes. While news reports mention fuel shortages in past hurricanes, the crowdsource platform Gasbuddy has quantified the fuel shortages in the recent hurricanes. The analysis of this fuel shortage data suggested fuel shortages exhibited characteristics of an epidemic. Here, a Susceptible- Infected-Recovered (SIR) epidemic model is developed to study the evolution of fuel shortage during a hurricane evacuation. Additionally, the authors apply optimal control theory to identify an effective intervention strategy. The study found a linear correlation between traffic demand during the evacuation of Hurricane Irma and the resulting fuel shortage data. This correlation is used in conjunction with the Statewide Regional Evacuation Study Program (SRESP) surveys to estimate the evacuation traffic and fuel shortages for potential hurricanes affecting south Florida. Results indicate that evacuation of Miami-Dade County in the event of a Category-3 hurricane landfall in the region, could lead to fuel shortages in up to 90% of the local refuelling stations. The model indicates that this reduces to 28% by providing relief to 75% of the gas stations during the first two days of the evacuation.

• Record URL:
  https://doi.org/10.1049/itr2.12083
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/1751956X
• Supplemental Notes:
  • © 2021 Sabique Islam et al.
• Authors:
  • Islam, Sabique
  • Parr, Scott
  • Prazenica, Richard
  • Liu, Dahai
  • Namilae, Sirish
• Publication Date: 2021-8

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 1064-1075
• Serial:
  • IET Intelligent Transport Systems
  • Volume: 15
  • Issue Number: 8
  • Publisher: Institution of Engineering and Technology (IET)
  • ISSN: 1751-956X
  • EISSN: 1751-9578
  • Serial URL: https://ietresearch.onlinelibrary.wiley.com/journal/17519578
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Epidemiology; Evacuation; Fuels; Hurricanes; Predictive models; Shortages
• Identifier Terms: Hurricane Irma
• Geographic Terms: Miami-Dade County (Florida)
• Subject Areas: Security and Emergencies; Transportation (General);

Filing Info

• Accession Number: 01780319
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 27 2021 2:56PM