Suchergebnisse

Guided by influential theories of disaster research and gerontology, this study examines health resilience associated with tornadoes, particularly focusing on how individuals' tornado-associated stress, financial losses, and family members' well-being affected posttraumatic distress (PTD), posttraumatic growth (PTG), and self-reported changes in health among adults. To reach this goal, this study collected data from residents affected by two violent tornadoes in 2013, with the assistance of a professional survey lab which implemented a random-digit-dialling telephone survey. The working sample included 517 respondents with oversampled older adults. Multinomial logistic regression, Poisson regression, and Ordinary Least Square Regression were conducted separately for younger and older adults. The results indicated a significant effect of stress levels on PTG among older adults only. Nonetheless, the differences in effect sizes between the two groups were not significant. Meanwhile, respondents' financial losses and their family members' declined health were significant predictors of improved health among older adults. Similarly, family members' declined mental health was a significant predictor of PTD among older adults, but not younger adults. Compared to young adults, older adults were more vulnerable to their family members' declined mental health, but also more resilient to stressful situations, financial losses, and family members' declined physical health. Lastly, although risk and resilience factors could be constructed with the same set of items, they function differently among different groups of people. Hence, more studies on heterogeneity are needed to further refine resilience frameworks.

Abstract
Timely communication of warnings is essential to protection of lives and properties during tornado outbreaks. Both official and personal channels of communication prove to have considerable impact on the overall outcome. In this study, an agent-based model is developed to simulate warning's reception–dissemination process in which a person is exposed to, receives, and sends information while interacting with others. The model is applied to an EF5 tornado (EF indicates enhanced Fujita scale) that struck Moore, Oklahoma, in 2013. The parameters are calibrated using publicly available data or a poststorm telephone survey or were derived from literature reviews, expert judgement, and sensitivity analysis. The result shows a reasonable agreement between modeled and observed reception rates for older and younger adults and for different channels, with errors of less than 20 percentage points. Similar agreement is also seen for the average numbers of warning sources. The subsequent simulation indicates that, in the absence of tornado sirens, the overall reception rates for younger and older adults would drop from the baseline by 17 and 6 percentage points, respectively. Concurrently, there is a large decline in the number of warning sources. When a persons' social network is enlarged, the reception rate for older adults improves from 77% to 80%, whereas for younger adults it stays unchanged. The impact of increased connectivity is more pronounced when people are not watching television or a tornado siren is not available.

Significance Statement
Every year, tornadoes cause significant property damage and numerous casualties in the United States. This study aims to understand how tornado warnings reach the at-risk public through various communication channels. Using the agent-based model and simulation, we are able to reconstruct the dynamic patterns of warning's reception–dissemination process for older and younger adults within a historical EF5 tornado. Further analysis confirms the importance of tornado sirens in not only alerting more residents about the dangerous weather condition but also prompting protective actions. In the meantime, an increase in social connectivity among residents would compensate for the lack of exposure to television and tornado siren. Future work should investigate the robustness of this model and its parameters when applied to other tornado outbreaks.

Abstract. Hurricanes cause extensive harm to local economies, and in some
cases the recovery may take years. As an adequate, skilled, and trained
workforce is a prerequisite for economic development and capacity building,
employment plays an important role in disaster reduction and mitigation
efforts. The statistical relationship between hurricane landfalls and
observed changes in employment at the county level is investigated.
Hurricane impact is classified into temporary and permanent categories. In
the former category, the level of economic activities is lowered following a
hurricane landfall but quickly recovers to the pre-storm norm. In contrast,
the permanent shift alters the mean value of the data and results in lasting
losses in future years. The results show that Hurricane Katrina produced
significant permanent impact on Orleans County, Louisiana. Chambers and Fort
Bend counties experienced a significant temporary impact due to the landfall
of Hurricane Ike. The results are further discussed through a qualitative
analysis of various social, economic, and engineering factors in these
affected communities. The findings support the notion that a higher resilience
level leads to quicker recovery after a disaster. However, the underlying
data-generating processes are characterized and tested in a more detailed
manner.

AbstractHurricanes disrupt business processes and activities, energy distribution and consumption, and services of infrastructure and lead to a reallocation of resources and their uses. This research models the relationship among economic and engineering measures of the state of the built environment in order to provide insight into a region's ability to withstand and recover from a future hurricane. As such, we provide a quantitative approach to modeling and measuring a region's economic resiliency. The findings have implications for developing strategies for long‐term sustainability of economic regions.

In the United States, residents and businesses in the Atlantic and Gulf Coastal regions are confronted with an increasing risk of hurricane-induced damages. It is often too costly and labor intensive to survey every structure within a large area affected by a major storm. Therefore, this paper is aimed at proposing and evaluating three sampling methods specifically designed for post-hurricane damage survey: Simple Random Sampling, Equal Spatial Sampling, and Route Based Sampling. After describing their general formation, a case study is presented in which these three sampling methods are applied to 1,020 residential houses affected by Hurricane Katrina in 2005, allowing for systematic and objective selection of samples for ground inspection. Then the distributions of damage conditions of samples are compared with that of population. The result shows that the sample sets selected by the Equal Spatial Sampling and Route Based Sampling methods reasonably represent the full data set with a few exceptions in high damage categories while the performance of the Simple Random Sampling is far less consistent. This work could serve as a guidance for designing a balanced sampling scheme with the consideration of expected performance and available resources in future post-disaster damage surveys.