604
Views
5
CrossRef citations to date
0
Altmetric
Papers

Hurricane evacuation beliefs and behaviour of inland vs. coastal populations

, ORCID Icon, , , ORCID Icon &
Pages 363-381 | Received 27 Apr 2020, Accepted 17 Sep 2020, Published online: 08 Oct 2020
 

ABSTRACT

Although hurricanes can cause severe hazard effects well inland, little is known about the evacuation behaviour of inland populations compared to coastal populations. Using survey data collected in the United States after Hurricanes Florence (2018), Michael (2018), Barry (2019), and Dorian (2019), we investigate differences between coastal and inland populations in evacuation decisions and timing, and their causes. The data indicate that coastal populations evacuated at a higher rate than their inland counterparts (those not in coastal counties) in every hurricane studied. Chi-square tests identified differences in characteristics of coastal and inland populations, and a multiple logistic regression identified variables associated with evacuation. Together they suggest multiple factors that help explain the difference in evacuation rates. The most significant findings were related to geographic differences in the issuance of evacuation orders and reported receiving of orders (whether or not orders were actually issued). Most interestingly, the analysis indicates that variance between inland and coastal evacuation is not fully explained by the factors suggested in existing literature. We suggest here that differences between inland and coastal evacuation may also result from risk perception, in particular, a view that hurricanes are a coastal phenomenon and therefore do not apply to inland populations.

Acknowledgements

This work was supported by the National Science Foundation under Grant CMMI-1331269. The statements, findings, conclusions are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Science Foundation under Grant CMMI-1331269.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 315.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.