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Fuel shortages during hurricanes: Epidemiological modeling and optimal control

Hurricanes are powerful agents of destruction with significant socioeconomic impacts. A persistent problem due to the large-scale evacuations during hurricanes in the southeastern United States is the fuel shortages during the evacuation. Computational models can aid in emergency preparedness and he...

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Autores principales: Islam, Sabique, Namilae, Sirish, Prazenica, Richard, Liu, Dahai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112216/
https://www.ncbi.nlm.nih.gov/pubmed/32236120
http://dx.doi.org/10.1371/journal.pone.0229957
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author Islam, Sabique
Namilae, Sirish
Prazenica, Richard
Liu, Dahai
author_facet Islam, Sabique
Namilae, Sirish
Prazenica, Richard
Liu, Dahai
author_sort Islam, Sabique
collection PubMed
description Hurricanes are powerful agents of destruction with significant socioeconomic impacts. A persistent problem due to the large-scale evacuations during hurricanes in the southeastern United States is the fuel shortages during the evacuation. Computational models can aid in emergency preparedness and help mitigate the impacts of hurricanes. In this paper, we model the hurricane fuel shortages using the SIR epidemic model. We utilize the crowd-sourced data corresponding to Hurricane Irma and Florence to parametrize the model. An estimation technique based on Unscented Kalman filter (UKF) is employed to evaluate the SIR dynamic parameters. Finally, an optimal control approach for refueling based on a vaccination analogue is presented to effectively reduce the fuel shortages under a resource constraint. We find the basic reproduction number corresponding to fuel shortages in Miami during Hurricane Irma to be 3.98. Using the control model we estimated the level of intervention needed to mitigate the fuel-shortage epidemic. For example, our results indicate that for Naples- Fort Myers affected by Hurricane Irma, a per capita refueling rate of 0.1 for 2.2 days would have reduced the peak fuel shortage from 55% to 48% and a refueling rate of 0.75 for half a day before landfall would have reduced to 37%.
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spelling pubmed-71122162020-04-09 Fuel shortages during hurricanes: Epidemiological modeling and optimal control Islam, Sabique Namilae, Sirish Prazenica, Richard Liu, Dahai PLoS One Research Article Hurricanes are powerful agents of destruction with significant socioeconomic impacts. A persistent problem due to the large-scale evacuations during hurricanes in the southeastern United States is the fuel shortages during the evacuation. Computational models can aid in emergency preparedness and help mitigate the impacts of hurricanes. In this paper, we model the hurricane fuel shortages using the SIR epidemic model. We utilize the crowd-sourced data corresponding to Hurricane Irma and Florence to parametrize the model. An estimation technique based on Unscented Kalman filter (UKF) is employed to evaluate the SIR dynamic parameters. Finally, an optimal control approach for refueling based on a vaccination analogue is presented to effectively reduce the fuel shortages under a resource constraint. We find the basic reproduction number corresponding to fuel shortages in Miami during Hurricane Irma to be 3.98. Using the control model we estimated the level of intervention needed to mitigate the fuel-shortage epidemic. For example, our results indicate that for Naples- Fort Myers affected by Hurricane Irma, a per capita refueling rate of 0.1 for 2.2 days would have reduced the peak fuel shortage from 55% to 48% and a refueling rate of 0.75 for half a day before landfall would have reduced to 37%. Public Library of Science 2020-04-01 /pmc/articles/PMC7112216/ /pubmed/32236120 http://dx.doi.org/10.1371/journal.pone.0229957 Text en © 2020 Islam et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Islam, Sabique
Namilae, Sirish
Prazenica, Richard
Liu, Dahai
Fuel shortages during hurricanes: Epidemiological modeling and optimal control
title Fuel shortages during hurricanes: Epidemiological modeling and optimal control
title_full Fuel shortages during hurricanes: Epidemiological modeling and optimal control
title_fullStr Fuel shortages during hurricanes: Epidemiological modeling and optimal control
title_full_unstemmed Fuel shortages during hurricanes: Epidemiological modeling and optimal control
title_short Fuel shortages during hurricanes: Epidemiological modeling and optimal control
title_sort fuel shortages during hurricanes: epidemiological modeling and optimal control
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112216/
https://www.ncbi.nlm.nih.gov/pubmed/32236120
http://dx.doi.org/10.1371/journal.pone.0229957
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AT liudahai fuelshortagesduringhurricanesepidemiologicalmodelingandoptimalcontrol