Hurricane preparedness among elderly residents in South Florida

Kleier, Jo Ann; Krause, Danielle; Ogilby, Terry

doi:10.1111/phn.12344

Cited by 18 publications

(16 citation statements)

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“…Motivating individuals and households to prepare for natural hazards has become an increasingly important strategy in emergency management since the mid-1990s (Ablah et al 2009 Only one full inventory was found for storm preparedness under the definition of storm used in this study and articulated below. This was developed and tested by Moon (2010) and further used by Kleier et al (2018) to measure influences on preparedness for a hurricane. Moon's (2010) inventory was based on a list of activities developed to measure earthquake preparedness by Paton , Smith, Johnston, Johnston and Ronan et al (2003), which they described as key performance indicators for assessing resilience and preparedness (Paton et al 2003, p. 28).…”

Section: Introductionmentioning

confidence: 99%

“…Moon's (2010) instrument, which was also used in association with other phenomenon of interest, such as motivations and vulnerabilities that might affect preparedness activity, showed relatively high internal consistency scores with Cronbach's alpha scores ranging from .731 to .881 (n =153 153) (Moon 2010, p. 73). Kleier et al (2018) reported a Cronbach's alpha score of their preparedness scale of .90 (n =147 147). Some studies have included a small number (nine or fewer) preparedness questions to measure preparedness in conjunction with measurement of some other phenomena in studies of tornado (Chaney et al 2013) and hurricane/cyclone (Sattler et al 2002;).…”

Section: Introductionmentioning

confidence: 99%

“…As well, only two studies have been found that consider storm preparedness and storm inventories, compared with many studies for earthquake, wildfire and flood. Research in Australia indicates that more storm experience predicts better preparation (King et al 2006; Kleier et al 2018;Sattler et al 2000;), which is a problem now that the tropical belt that generates and hosts cyclones in Australia seems to be widening (Seidel et al 2008), exposing inexperienced populations to severe storms. In addition, from 1987 to 2016, storms in Australia took 89 lives, injured 360 people, caused 15,500 people to become homeless and directly affected over four million people (Deloitte Access Economics 2017) in a population of 23.4 million 4 million (Australian Bureau of Statistics, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…However, it seems the further south in Australia a person lives, the lower their preparation for a storm will be, which is most likely a reflection of the northerners' experiences of cyclones and cyclone-generated extensive rain events, with experience being an influencing factor on preparation (Cretikos et al 2008;Kleier et al 2017Kleier et al 2018Mackie et al 2013). Overall though, Australians seem to be generally ill-prepared for all hazards, with their preparation levels calculated to be 3.84 out of a possible 10 (Kelly and Ronan 2018) using a preparedness scale that was developed using an inventory-based questionnaire.…”

Section: Introductionmentioning

confidence: 99%

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How ready is ready? Measuring physical preparedness for severe storms

Ryan

King

2020

Nat Hazards

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This paper investigates use of inventories, or checklists of activities, as an emergency management tool to motivate preparedness action in individuals. It develops the inventory concept to provide the foundation for a more targeted approach to storm preparation communication and community engagement. It also examines the potential efficacy of alternatives to paper-based checklists, such as web or smartphone applications. Academic and grey literature was reviewed to collect activities for a storm inventory for emergency agencies to measure individual preparedness and individuals to measure their preparation progress. The resulting master list was refined for application and tested for useability in a pilot study of semi-structured interviews in a storm-susceptible community in Queensland, Australia. Also, clustering items by type of preparedness activity reveal where strengths and weaknesses exist in individual preparedness. For instance, preparation for leaving and safety planning were shown to be the areas of weakest activity in the pilot sample, while preparation of the house for a storm was the strongest area. In addition, behaviour change literature shows potential for effective use of an inventory-based smartphone application in motivating preparation activity. Data collected by a storm preparedness smartphone application could show where a communication or engagement program for targeted communities should be focused. It is supported by health literature that identifies preferences of individuals to make progress on complex tasks in stages, the value of lists to achievement of goals and demonstrated increase in uptake of activities prompted by smartphone applications over web or paper-based diaries.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

How ready is ready? Measuring physical preparedness for severe storms

Ryan

King

2020

Nat Hazards

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“…There are several studies focusing on the damage of extreme weather events and recovery plans for such events [3]- [7]. Some of the recent studies have investigated the impact of extreme weather conditions on vulnerable populations and searched for more efficient ways for emergency evacuation [6], [8]. Others have specifically performed disasters risk assessment [9], [10].…”

Section: Introductionmentioning

confidence: 99%

Multi-Network Vulnerability Causal Model for Infrastructure Co-Resilience

et al. 2019

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Resilience is mostly considered as a single-dimension attribute of a system. Most of the recent works on resilience treat it as a single-dimension attribute of a system or study the different dimensions of the resilience separately without considering its multi-domain nature. In this paper, we propose an advanced causal inference approach combined with machine learning to characterize the spatio-temporal and multi-domain vulnerability of an urban infrastructure system against extreme weather events. With the proposed causality approach, we perform vulnerability assessment for electricity outages and roadway closures through considering the meteorological, topographic, and demographic attributes of urban areas in the aftermath of the extreme weather events. This proposed holistic approach to multi-network vulnerability assessment paves the ground for characterizing the resilience in a multi-network scheme, which is coined as the concept of ''co-resilience.'' The proposed causal framework for multi-network vulnerability assessment is validated using the actual data for the impacts of the Hurricane Hermine 2016 and the January Storm 2017 on the Tallahassee, FL, USA. The results achieved from the proposed causality approach indicate a high causal relationship among electricity outages, roadway closures, topographic aspects, and meteorological variables in an urban area. Findings show that the proposed multi-network approach for vulnerability assessment improves the performance of the estimation and prediction of the disaster outcomes and the evaluation of the overall system resilience.INDEX TERMS Causality, resilience vs. co-resilience, multi-network vulnerability, extreme events, power outages, roadway closures. FIGURE 1. Multi-layer infrastructure map for the City of Tallahassee, Florida. Layers from top to bottom are population density, all customers, power lines, roadways and land cover respectively.

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