Data from surveys administered after Hurricane Sandy provide a wealth of information that can be used to develop models of evacuation decision-making. We use a model based on survey data for predicting whether or not a family will evacuate. The model uses 26 features for each household including its neighborhood characteristics. We augment a 1.7 million node household-level synthetic social network of Miami, Florida with public data for the requisite model features so that our population is consistent with the survey-based model. Results show that household features that drive hurricane evacuations dominate the effects of specifying large numbers of families as \early evacuators" in a contagion process, and also dominate effects of peer influence to evacuate. There is a strong network-based evacuation suppression effect from the fear of looting. We also study spatial factors affecting evacuation rates as well as policy interventions to encourage evacuation.
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Data-Driven Modeling of Evacuation Decision-Making in Extreme Weather Events
Data from surveys administered after Hurricane Sandy provide a wealth of information that can be used to develop models of
evacuation decision-making. We use a model based on survey data for
predicting whether or not a family will evacuate. The model uses 26 features for each household including its neighborhood characteristics. We
augment a 1.7 million node household-level synthetic social network of
Miami, Florida with public data for the requisite model features so that
our population is consistent with the survey-based model. Results show
that household features that drive hurricane evacuations dominate the
e ects of specifying large numbers of families as "early evacuators" in a
contagion process, and also dominate e ffects of peer influence to evacuate. There is a strong network-based evacuation suppression eff ect from
the fear of looting. We also study spatial factors a ecting evacuation
rates as well as policy interventions to encourage evacuation.
more »
« less
- NSF-PAR ID:
- 10300635
- Date Published:
- Journal Name:
- Complex Networks and their Applications
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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