Daan Liang’s research while affiliated with University of Alabama and other places

Economic resilience defines a community’s ability to prevent, withstand, and quickly recover from major disruptions to its economic base. Instead of having repeated damage and need for outside assistance, resilient communities proactively protect themselves against hazards, build self-sufficiency, and become more sustainable over the long term. Within these communities, small businesses are an important driver of economic growth and employment. However, small businesses are extremely vulnerable to natural disasters: about 40–60 percent of them never reopen their doors after a disaster. To gain an insight into the vulnerability and resilience of small businesses, we collected firm-level data through an online survey of primary decision-makers of small businesses located in 2017 Hurricane Harvey impacted counties. The questions in the survey covered five broad categories: general business characteristics; finance impact; operation impact; built environment impact; and mitigation actions. The analysis shows a small variation in recovery time between industry groups. However, the contrast between firms that invested in resilience and firms that did not is significant. We then modeled the small business recovery as a stochastic process and used the survey data to select probability models and then estimate model parameters. If firms chose to invest in resilience, the mean and median times could be reduced by 57% and 8.5%, respectively. Using the baseline provided, a firm could estimate the length of recovery expected and prepare a business continuity plan accordingly. In a hurricane’s aftermath, their performance can be benchmarked against that of their peers. The findings would serve as basis for public policies towards incentivizing prestorm mitigation and resilience-building actions.

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.

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.

This study examined the association between age and preparedness for the continuation of COVID-19. The moderation effects of three types of social support, namely, emotional, financial, and instrumental assistance were also tested. Using a sample of 443 adults in Dallas county which has the most confirmed cases in Texas, results of multiple linear regressions showed that compared to those aged between 18 and 64, older adults aged 65 and reported better preparedness for the continuation of COVID-19. Receiving emotional, financial, and instrumental assistance were respectively more important for older people to get better prepared than for younger adults, which is consistent with the socioemotional selectivity theory. Our findings directed attention to the strengths and resilience of older adults during COVID-19 from a life course perspective and highlighted the importance of social support and social relationship in their post-disaster recovery and ongoing preparedness.

This study examined age differences in barriers to preparing for disasters and how caregiving responsibilities are associated with these barriers among different age groups. Using a sample of 1,142 individuals from the 2017 Federal Emergency Management Agency National Household Survey, binary and multinomial logistic regressions were conducted to investigate the likelihood of encountering any or one of the two types of barriers, namely, barriers related to coping appraisal (i.e., capacity) and those related to threat appraisal (i.e., risk perception). Age was the key predictor and was categorized into five groups: 18 - 34, 35-49, 50 - 64, 65 - 74, and 75+. The results showed that the 18 - 34, 35 - 49, and 75+ age groups were more likely to have coping appraisal barriers than those aged between 65 and 74. In addition, being a caregiver increased the likelihood of having coping appraisal barriers. Interestingly, relative to the 65 - 74 age group, being a caregiver in the 18 - 34, 35 - 49, and 50 - 64 age groups would be more likely to have coping appraisal barriers. Our findings highlighted age patterns and heterogeneity among older adults. This study also directed attention to how disaster preparation behaviors were shaped by life course experiences.

Objective: This study investigated how the effectiveness of household emergency plans during tornadoes was associated with family discussions, and the attributes of the plan for different age groups. Methods: A telephone survey was conducted in 2014, one year after two 2013 Enhanced Fujita 4/5 tornadoes. The working sample included 223 respondents who reported having a household emergency plan before the tornadoes. The latent class analysis was used to identify the patterns of the plans and develop a typology based on their content. Logistic regression was used to examine predictors for plan effectiveness. Results: Two classes of plans were identified: quality plans that were rich in content and limited plans that had lower levels of content richness. Older adults were less likely to have quality plans and less likely to have family discussions. Quality of the plan and discussions with family members increased plan effectiveness among older adults, but not younger adults. Conclusions: Better emergency planning could be more important for older than for younger adults. The findings were discussed from a gerontological perspective that focuses on older adults' unique needs, vulnerabilities, and resilience factors.

Objective This study examined factors that were associated with the effectiveness of pre-existing household emergency plans during the 2011 EF5 Joplin and EF4 Tuscaloosa tornadoes. We focused on whether discussing with family members helped increase the plan’s effectiveness. Methods A telephone survey based on random sampling was conducted in 2012 with 1006 respondents in both cities. Each city experienced huge losses, injuries, and casualties. The working sample included 494 respondents who had a household emergency plan in place before these tornadoes. Results Multinomial logistic regression showed that discussing with family members increased the helpfulness of the plan in Joplin, where people had not experienced tornadoes frequently and were less prepared for tornadoes relative to residents in Tuscaloosa. Conclusions This study provides empirical evidence on the importance of encouraging family involvement when making household emergency plans, especially in places that are less prepared for disasters than those that are better prepared.

Brightness of nighttime lights (NTL) collected by the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) is compatible across different times of images thanks to the on-board calibration system. However, the NTL radiance observed by the S-NPP VIIRS shows clear seasonality corresponding to the seasonal changes in the albedo of land surface. Additionally, the existence of many uncertain factors (e.g. complex atmospheric conditions) renders it inappropriate to directly use the NTL radiances to derive changes on the ground. In this study, we adopt a statistical procedure of time series analysis, namely seasonal and trend decomposition using Loess (STL), to model the time series observations of NTL brightness by decomposing the observations into three separable time series components (i.e. trend, seasonality, and remainder). Based on the time series model, forecast can be made for short-term future with confidence measure, and by comparing the model forecast with observed NTL brightness, significant changes can then be detected at pixel levels. We applied this method to the Puerto Rico area to detect and assess the damages caused by Hurricanes Irma and Maria, and to monitor the recovery after the disaster. Our results show that the proposed method successfully captures the changes of NTL brightness due to the damage of the hurricanes and general economic decline. Moreover, we also find that after removing the seasonal and remainder components, the time series of NTL image can more accurately reflect the temporal trends of economic status in Puerto Rico.