skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Evacuate or social distance? Modeling the influence of threat perceptions on hurricane evacuation in a dual‐threat environment
Abstract This study investigates how different risk predictors influenced households’ evacuation decisions during a dual‐threat event (Hurricane Laura and COVID‐19 pandemic). The Protective Action Decision Model (PADM) literature indicates that perceived threat variables are the most influential variables that drive evacuation decisions. This study applies the PADM to investigate a dual‐threat disaster that has conflicting protective action recommendations. Given the novelty, scale, span, impact, and messaging around COVID‐19, it is crucial to see how hurricanes along the Gulf Coast—a hazard addressed seasonally by residents with mostly consistent protective action messaging—produce different reactions in residents in this pandemic context. Household survey data were collected during early 2021 using a disproportionate stratified sampling procedure to include households located in mandatory and voluntary evacuation areas across the coastal counties in Texas and parishes in Louisiana that were affected by Hurricane Laura. Structural equation modeling was used to identify the relationships between perceived threats and evacuation decisions. The findings suggest affective risk perceptions strongly affected cognitive risk perceptions (CRPs). Notably, hurricane and COVID‐19 CRPs are significant predictors of hurricane evacuation decisions in different ways. Hurricane CRPs encourage evacuation, but COVID‐19 CRPs hinder evacuation decisions.  more » « less
Award ID(s):
2051578
PAR ID:
10439316
Author(s) / Creator(s):
 ;  ;  ;  
Publisher / Repository:
Wiley-Blackwell
Date Published:
Journal Name:
Risk Analysis
ISSN:
0272-4332
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Cao, Jason Xinyu; Ge, Ying-En (Ed.)
    This study explores household-level evacuation decision-making in response to Hurricane Laura, in a context where hurricane risk reduction measures contradicted COVID-19 risk reduction measures. Data were collected using a mail-based survey approach from households along the coast of Texas and Louisiana to explore drivers of and barriers to evacuation, including COVID-19 measures such as negative affect, risk perceptions, protective actions, and exposure. Testing for direct and indirect effects among the drivers of and barriers to evacuation, we find that many of our COVID-19 measures did not have a direct effect on evacuation but did have indirect effects through other factors. We also found evidence of both direct and indirect relationships with regards to more conventional drivers of evacuation found in the literature. We close with a discussion of the limitations and implications of this study. 
    more » « less
  2. null (Ed.)
    Understanding human responses to pandemics can improve public health. A survey of US residents (n = 2004) February 28, 2020, very early in the coronavirus pandemic, tested predictors of five “protective” actions: washing hands, wearing masks, avoiding travel, avoiding large public gatherings, and avoiding Asians (given COVID-19’s first appearance in China). We added to the Protective Action Decision Model—positing threat, protective action, and stakeholder perceptions as immediate predictors of intentions—objective and subjective coronavirus knowledge as predictors of these perceptions, and psychological distance to predict threat perceptions. We presumed objective and subjective knowledge were affected by following US and China news about COVID-19. Structural equation modeling indicated adequate fit for this parsimonious model; variance explained in behavioral intentions ranged from .12 (handwashing) to .33 (Asians). Behavioral intentions rose with higher threat, action, and stakeholder (trust) perceptions, psychological distance reduced threat perceptions, objective knowledge reduced threat and action perceptions but increased trust, and subjective knowledge did the opposite. Coronavirus-news following increased both objective and subjective knowledge, but subjective knowledge exhibited stronger associations and US news dominated China news. Moderate model fit and variance explained might reflect model parsimony and/or data collection when US cases were in the low double digits. 
    more » « less
  3. The decisions of whether and how to evacuate during a climate disaster are influenced by a wide range of factors, including emergency messaging, social influences, and sociodemographics. Further complexity is introduced when multiple hazards occur simultaneously, such as a flood evacuation taking place amid a viral pandemic that requires physical distancing. Such multihazard events can necessitate a nuanced navigation of competing decision-making strategies wherein a desire to follow peers is weighed against contagion risks. To better understand these trade-offs, we distributed an online survey during a COVID-19 pandemic surge in July 2020 to 600 individuals in three midwestern and three southern states in the United States with high risk of flooding. In this paper, we estimate a random parameter discrete choice model in both preference space and willingness-to-pay space. The results of our model show that the directionality and magnitude of the influence of peers’ choices of whether and how to evacuate vary widely across respondents. Overall, the decision of whether to evacuate is positively impacted by peer behavior, while the decision of how to evacuate (i.e., ride-type selection) is negatively impacted by peer influence. Furthermore, an increase in flood threat level lessens the magnitude of peer impacts. In terms of the COVID-19 pandemic impacts, respondents who perceive it to be a major health risk are more reluctant to evacuate, but this effect is mitigated by increased flood threat level. These findings have important implications for the design of tailored emergency messaging strategies and the role of shared rides in multihazard evacuations. Specifically, emphasizing or deemphasizing the severity of each threat in a multihazard scenario may assist in: (1) encouraging a reprioritization of competing risk perceptions; and (2) magnifying or neutralizing the impacts of social influence, thereby (3) nudging evacuation decision-making toward a desired outcome. 
    more » « less
  4. Bristol Bay in Alaska is home to the world’s largest commercial salmon fishery. During an average fishing season, the population of the Bristol Bay region more than doubles as thousands of workers from out of state converge on the fishery. In the months leading up to the 2020 commercial fishery opening, as the COVID-19 pandemic exploded worldwide, great uncertainty existed about the health risks of opening the fishery. Bristol Bay residents had not yet experienced any cases of COVID-19, yet the livelihoods of most were closely tied to the commercial fishery opening. To better understand how COVID-19 risk perceptions affected decisions to participate in the fishery, we administered an online survey to community members and fishery participants. We collected standard socioeconomic data and posed questions to gauge risk perceptions related to COVID-19. We find that COVID-19 risk perceptions vary across race/ethnic groups by residency and income. People with below median income who are members of minority groups—notably, non-resident Hispanic workers and resident Alaska Native respondents—reported the highest risk perceptions related to COVID-19. This study highlights the important linkages among risk perceptions, socioeconomic characteristics, and employment decisions during an infectious disease outbreak. 
    more » « less
  5. Online social networks allow different agencies and the public to interact and share the underlying risks and protective actions during major disasters. This study revealed such crisis communication patterns during Hurricane Laura compounded by the COVID-19 pandemic. Hurricane Laura was one of the strongest (Category 4) hurricanes on record to make landfall in Cameron, Louisiana, U.S. Using an application programming interface (API), this study utilizes large-scale social media data obtained from Twitter through the recently released academic track that provides complete and unbiased observations. The data captured publicly available tweets shared by active Twitter users from the vulnerable areas threatened by Hurricane Laura. Online social networks were based on Twitter’s user influence feature (i.e., mentions or tags) that allows notification of other users while posting a tweet. Using network science theories and advanced community detection algorithms, the study split these networks into 21 components of various size, the largest of which contained eight well-defined communities. Several natural language processing techniques (i.e., word clouds, bigrams, topic modeling) were applied to the tweets shared by the users in these communities to observe their risk-taking or risk-averse behavior during a major compounding crisis. Social media accounts of local news media, radio, universities, and popular sports pages were among those which heavily involved and closely interacted with local residents. In contrast, emergency management and planning units in the area engaged less with the public. The findings of this study provide novel insights into the design of efficient social media communication guidelines to respond better in future disasters. 
    more » « less