Suchergebnisse

Land-use planning tools have been extensively applied in the U.S. to achieve environmental sustainability and disaster resiliency for local communities. An important issue related to land-use planning tools is planners' beliefs about the ways in which these tools differ from each other and, thus, how planners choose among these tools for environmental hazard mitigation. A web-based survey collected data from planners in counties (or boroughs) in the five U.S. Pacific states (where county land-use planning is limited to unincorporated areas). The results indicate that planners substantially, but not completely, agreed in their perceptions of planning tools, that planners' perceptions of planning tools are minimally related to their personal characteristics and those of their jurisdictions, and that planners' perceptions of planning tools are significantly correlated with the capacity of their planning agencies. Planners viewed effectiveness (a desirable attribute) as positively correlated with economic costs and other impediments (which are undesirable attributes) so they must make trade-offs among these attributes and choose the most appropriate tool when formulating a growth management strategy.

The study of migrations and mobility has historically been severely limited by the absence of reliable data or the temporal sparsity of available data. Using geospatial digital trace data, the study of population movements can be much more precisely and dynamically measured. Our research seeks to develop a near real-time (one-day lag) Twitter census that gives a more temporally granular picture of local and non-local population at the county level. Internal validation reveals over 80% accuracy when compared with users' self-reported home location. External validation results suggest these stocks correlate with available statistics of residents/non-residents at the county level and can accurately reflect regular (seasonal tourism) and non-regular events such as the Great American Solar Eclipse of 2017. The findings demonstrate that Twitter holds the potential to introduce the dynamic component often lacking in population estimates. This study could potentially benefit various fields such as demography, tourism, emergency management, and public health and create new opportunities for large-scale mobility analyses.

This study tested a series of models predicting household expectations of participating in hurricane hazard mitigation incentive programs. Data from 599 households in Florida revealed that mitigation incentive adoption expectations were most strongly and consistently related to hazard intrusiveness and risk perception and, to a lesser extent, worry. Demographic and hazard exposure had indirect effects on mitigation incentive adoption expectations that were mediated by the psychological variables. The results also revealed differences in the factors affecting mitigation incentive adoption expectations for each of five specific incentive programs. Overall, the results suggest that hazard managers are more likely to increase participation in mitigation incentive programs if they provide messages that repeatedly (thus increasing hazard intrusiveness) remind people of the likelihood of severe negative consequences of hurricane impact (thus increasing risk perception).

AbstractHurricanes are one of the most dangerous catastrophes faced by the USA. The associated life losses can be reduced by proper planning and estimation of evacuation demand by emergency planners. Traditional evacuation demand estimation involves a sequential process of estimating various decisions such as whether to evacuate or stay, evacuation destination, and accommodation type. The understanding of this sequence is not complete nor restricted to strict sequential ordering. For instance, it is not clear whether the evacuation destination decision is made before the accommodation type decision, or the accommodation type decision is made first or both are simultaneously made. In this paper, we develop a nested logit model to predict the relative ordering of evacuation destination and accommodation type that considers both sequential and simultaneous decision making. Household survey data from Hurricane Matthew is used for computing empirical results. Empirical results underscore the importance of developing a nested structure among various outcomes. In addition to variables related to risk perception and household characteristics, it is found that social networks also affect this decision-making process.

AbstractBuilding an interdisciplinary team is critical to disaster response research as it often deals with acute onset events, short decision horizons, constrained resources, and uncertainties related to rapidly unfolding response environments. This article examines three teaming mechanisms for interdisciplinary disaster response research, including ad hoc and/or grant proposal driven teams, research center or institute based teams, and teams oriented by matching expertise toward long‐term collaborations. Using hurricanes as the response context, it further examines several types of critical data that require interdisciplinary collaboration on collection, integration, and analysis. Last, suggesting a data‐driven approach to engaging multiple disciplines, the article advocates building interdisciplinary teams for disaster response research with a long‐term goal and an integrated research protocol.

This study was designed to determine if respondents in the United States (Texas State) and China (Anhui province) differed in their perceptions of three stakeholder types (authorities, news media, and peers) with respect to three stakeholder characteristics (expertise, trustworthiness, and protection responsibility) and if these stakeholder perceptions were significantly correlated with protective actions for influenza. Both Texas and Anhui respondents rated expertise, trustworthiness, and protection responsibility as highest for public health authorities and lowest for Internet/social media. However, the differences between ratings for authorities and peers were greater in Texas than in Anhui and the correlations of stakeholder characteristics with protective action were quite different between Texas and Anhui. These results suggest that public health authorities should recognize that there are differences across countries in people's perceptions of authorities, news media and peers. These differences are important because people's perceptions of different stakeholders are significantly correlated with their protective actions in response to pandemic influenza.

Abstract
Epidemiological evidence suggests that exposure to per- and polyfluoroalkyl substances (PFAS) is associated with lipid profile levels, but with inconsistent conclusions from different studies. The aim of this study was to conduct a meta-analysis of the relationship between PFAS exposure and lipid profile levels based on population-based epidemiological studies. Embase, PubMed, Ovid database, The Cochrane Library and Web of Science database were used to search appropriate studies (before September 6, 2022) on the correlation between PFAS exposure and lipid profile levels. β value, odd ratio (OR) and 95 % confidence intervals (CIs) were extracted from studies. In this study, we found that higher low-density lipoprotein (LDL) levels were associated with exposure to perfluoroundecanoic acid (PFUnDA) (β value=0.13, 95 % CIs: 0.02, 0.24) and perfluorooctane sulfonic acid (PFOS) (β value=0.13, 95 % CIs: 0.04, 0.21). PFOA, PFOS and PFNA exposure were significantly related to the higher levels of total cholesterol (TC) with the pooled effect estimates of 0.08 (95 % CI: 0.02, 0.14), 0.13 (95 % CI: 0.05, 0.21) and 0.14 (95 % CI: 0.08, 0.20) respectively. In sum, our results identified that PFOA, PFOS, PFNA and PFUnDA were the most important risk factors for abnormal levels of lipid profile, indicating that we should prevent cerebrovascular disease by reducing and controlling PFAS exposure.

AbstractBuilding community resilience has become a national imperative. Substantial uncertainties in dynamic environments of emergencies and crises require real‐time information collection and dissemination based on big data analytics. These, in turn, require networked communities and cross‐sector partnerships to build lasting resilience. This viewpoint article highlights an interdisciplinary approach to building community resilience through community‐engaged research and partnerships. This perspective leverages existing community partnerships and network resources, undertakes an all‐hazard and whole‐community approach, and evaluates the use of state‐of‐the‐art information communication technologies. In doing so, it reinforces the multifaceted intergovernmental and cross‐sector networks through which resilience can be developed and sustained.