Willingness to Prepare for Disasters among Individuals with Disabilities: An Essential Component for Building Disaster Resiliency

This study focuses on exploring the factors influencing individuals’ preparedness for disasters. Drawing upon the protection motivation theory (PMT) and the prototype willingness model (PWM), a conceptual framework was proposed to investigate the determinants of willingness to prepare for disasters and its impact on disaster preparedness. Data was collected through an online survey, involving 377 participants with disabilities and medical special needs residing in the Rio Grande Valley (RGV). The collected data was analyzed using generalized structural equation modeling (GSEM) to examine the associations among the selected study variables. The findings indicate that both coping appraisal and threat appraisal significantly influence individuals’ willingness to prepare for disasters, which, in turn, has a notable impact on disaster preparedness. Recognizing the significance of disaster preparedness in building resilience and effectively responding to and recovering from disasters, it is crucial to acknowledge the importance of the willingness component in these efforts to cope effectively with future extreme events

An Exploratory Study on the Association between Community Resilience and Disaster Preparedness in the Rio Grande Valley

(1) Background: Severe weather events have impacted over 100 million Americans in the past two years, highlighting the importance of individual disaster preparedness in building community resilience. This study aims to investigate the factors influencing individuals’ perceived disaster resiliency and preparedness in the Rio Grande Valley, Texas. (2) Methods: Data were collected from 846 respondents using the Communities Advancing Resilience Toolkit (CART) Assessment Survey instrument. The study employed structural equation modeling (SEM) to explore the association between disaster preparedness and community resilience. (3) Results: The findings of the study revealed a significant association between disaster preparedness and perceived community resilience. (4) Conclusions: The study’s findings provide an assessment of the community strengths (assets) in the Rio Grande Valley, which can be utilized to develop initiatives and programs aimed at enhancing community resilience and individual disaster preparedness. These findings contribute significantly to the theoretical understanding of the interplay between community resilience and individual preparedness for disasters

Managerial networking of public and private sector: a study of Thai executives

This research proposes a perspective of managerial networking based on an integration of resource dependence theory and social exchange theory. In order to test applicability of the proposed framework, the study conceptualizes five critical elements of managerial networking, namely motives, activities, relational development, relational strength, and performance due to networking that explain the managerial networking mechanism. All statistical analyses revealed that motives for managerial networking, networking exchange activities, networking relational development and networking relational strength are positively and significantly associated with performance contributed to individual and organizational levels due to their managerial networking. In addition, it was found that the conceptual framework’s explanatory power was similar in two different sub-groups of sample

Public Exposure to U.S. Commercial Nuclear Power Plants Induced Disasters

This study explores the potential risks associated with the 65 U.S.-based commercial nuclear power plants and the distribution of those risks among the populations of both their respective host communities and of the communities located in outlying areas. First, it starts by examining the racial/ethnic composition of the host community populations, as well as the disparities in socioeconomic status that exist, if any, between the host communities and communities located in outlying areas. Second, it utilizes two independent-sample T tests to identify any differences in the sociodemographic compositions of the two areas. Third, it explores regional demographic trends by looking at the percent change in demographic variables in the host communities and communities located in outlying areas in 1990–2000 and 2000–2010. Findings reveal that during the past two decades more people were exposed to the risks as population living in the host communities increased

An Assessment of Storm Surge Risk in Coastal Communities in the Rio Grande Valley

Cameron County, which is located in the Rio Grande Valley, holds historical records for storm surges with noticeable property damage, fatalities, and injuries; (2) Methods: using storm surge hazard datasets from the National Oceanic and Atlantic Agency (NOAA), and American Community Survey (ACS) 2019 datasets and Geographic Information System (GIS), the study estimates at-risk population and their socio-demographic attributes; (4) Conclusions: Estimated water levels of a storm surge could be reached up to 5 feet in category 1 event, 9 feet in category 2, 17 feet in category 3, and above 20 feet in category 4 and 5. In the category 5 event, there is an estimated 37% (159,659) of the total county’s population (434,294) will be under flooded water. Suggestions are made to better prepare and successfully evaluate

A Longitudinal Study of Human Exposure to Potential Nuclear Power Plant Risk

This study constructs a potential risk index (PRI) for the 65 U.S.-based commercial nuclear power plant (NPP) sites in relation to their surrounding populations. Four risk levels are defined: low risk, moderate risk, high risk, and very high risk. Discrepancies that exist in the sociodemographic characteristics of the host communities’ populations are examined as sorted by risk-level category. It is found that a greater percentage of minority groups are exposed to the highest levels of risk. In addition, percent “Hispanic” and percent “Other,” a grouping that includes multiracial, mixed, interracial, as well as Hispanic and Latino groups (for example, Mexican, Puerto Rican, Cuban, or Spanish) are categories that show the greatest percent change in both the period 1990–2000 and 2000–2010

Who Will Stay, Who Will Leave: Decision-Making of Residents Living in Potential Hurricane Impact Areas During a Hypothetical Hurricane Event in the Rio Grande Valley

The Rio Grande Valley (RGV) has been impacted by various hurricanes throughout history. While Hurricane evacuation has been studied extensively in other contexts, there is limited systematic research on the warning and response to a large-scale severe weather event in South Texas. This study attempts to understand the evacuation decision-making behavior of Southern residents in the event of a Hurricane making landfall over the Rio Grande Valley. The study uses an online survey questionnaire with 1060 participants: 275 students attending the University of Texas-Rio Grande Valley and the remaining 785 are members of the community. Throughout the course of the study, information was gathered about selected elements: demographic characteristics, living conditions, the following and awareness of authority recommendations, decision maker roles, reasons for not wanting to leave a disaster-prone area facing an emergency, perception of a safe place, and expected help from both, governments and non-governmental organizations (NGOs) during evacuation that could impact residents’ evacuation decision. Findings reveal there are a number of individuals who will remain in their place of residence, even in the deadliest of hurricane Category 5. The study provides complex factors influencing the nature of evacuation decision-making of individuals who are Hispanics living in a unique geographical location of RGV

Social Connectedness, Physical Distancing, and Anxiety in Complying with Shelter-In-Place Orders and Advisories during the Once-In-A-Century COVID-19 Pandemic in the US: A Study of Social Media and Internet Users

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease (COVID-19), was first identified in Wuhan, China, in December 2019. As of 20 October 2020, the virus had infected 8,202,552 people, with 220,061 deaths in US, and in countries around the world, over 38 million people have become infected and over one million have died. The virus usually spreads via respiratory droplets from an infected person. At the time of compiling this paper, while countries around the world are still striving to find a pharmaceutical intervention (PI) , including treatments and vaccines, they are left with only non-pharmaceutical interventions (NPIs) , such as physical distancing, wearing masks, and maintaining personal hygiene. In the US, all 50 states, the District of Columbia, and five US territories issued mandatory stay-at-home orders between March 1 and 31 May 2020 to lower the risk of virus transmission. This study empirically examined how social connectedness and anxiety interact with shelter-in-place compliance and advisories during the pandemic. The study collected information from 494 adults using an online survey during April and July 2020

Exploring Spatial Patterns of Virginia Tornadoes Using Kernel Density and Space-Time Cube Analysis (1960-2019)

This study evaluates the spatial-temporal patterns in Virginia tornadoes using the National Weather Service Storm Prediction Center’s Severe Weather GIS (SVRGIS) database. In addition to descriptive statistics, the analysis employs Kernel Density Estimation for spatial pattern analysis and space-time cubes to visualize the spatiotemporal frequency of tornadoes and potential trends. Most of the 726 tornadoes between 1960–2019 occurred in Eastern Virginia, along the Piedmont and Coastal Plain. Consistent with other literature, both the number of tornadoes and the tornado days have increased in Virginia. While 80% of the tornadoes occurred during the warm season, tornadoes did occur during each month including two deadly tornadoes in January and February. Over the 60-year period, a total of 28 people were killed in the Commonwealth. Most tornado activity took place in the afternoon and early evening hours drawing attention to the temporal variability of risk and vulnerability. Spatial analysis results identify significant, non-random clusters of tornado activity and increasing temporal frequency. While this study improves weather-related literacy and addresses a need in the Commonwealth, more research is necessary to further evaluate the synoptic and mesoscale mechanisms of Virginia tornadoes

Empirical evaluation of disaster preparedness for hurricanes in the Rio Grande Valley

Individual emergency preparedness is critical to mitigate and minimize the negative impacts from disasters. Preparing for future disasters could enhance capacity to better cope with the external shocks and achieve a faster return to normalcy after the disaster event. This study investigates how individuals living in the Rio Grande Valley prepare themselves for the future hurricane disasters. The study investigates the state of objective and subjective preparedness and any discrepancy between the two types of disaster preparedness. Using collected data from590 respondents via an online survey instrument, the study examines the relationships between the states of individual preparedness and selected twelve socio-demographic variables. Findings show that there is a small percent of the total respondents who are actual prepared for disasters. The study concludes with a list of recommendations in order to encourage individuals to better prepare themselves with an aim of enhancing hurricane disaster resiliency in the valley