Disaster Risk Science: A Geographical Perspective and a Research Framework

On the relationship between disaster risk science and risk science

Risk disaster science aims to improve our knowledge on hazardous events and related consequences, their mitigation, preparedness, response, and recovery, as well as how to support decision making on the best way to handle such events and consequences. Risk science addresses many of the same types of issues, with its focus on concepts, principles, theories, models, approaches, and methods for understanding, assessing, communicating, and handling risk, with applications. This article aims to clarify how these fields and sciences relate to each other; what are the overlaps, and in what ways do they differ? The article argues that disaster risk science can be viewed as applied risk science. The implications of such a perspective are discussed and measures suggested for how to enhance these fields and their interactions.

The spatial-temporal evolution patterns of landslide-oriented resilience in mountainous city: A case study of Chongqing, China

Cities, as complex systems with multi-interconnected subsystems, face significant challenges from both rapid urbanization and climate change. Ensuring high resilience in urban areas is essential for managing these dynamic risks effectively. This study introduces an innovative, data-driven approach to quantitatively analyze the spatial-temporal evolution patterns of urban resilience, validated through a case study of Chongqing, a representative mountainous city in China. Based on historical landslide data from Chongqing (2010-2020), which includes 4464 events, along with indicator data from the Chongqing Statistical Yearbook, we developed a comprehensive assessment framework. This framework incorporates 33 variables, covering indicators of physical-environmental resilience (PER) and socio-economic resilience (SER). The model integrates the Random Forest (RF) algorithm, Analytic Hierarchy Process (AHP), and Coupling Coordination Degree (CCD) model. Key findings include: (1) Social development in mountainous cities like Chongqing follows a point-to-area pattern. Although there is an overall increase in SER, the CCD in more developed areas (Chongqing urban circle) was generally higher than in less developed areas (northeastern and southeastern Chongqing) (2) The PER model demonstrated exceptional performance (AUC values consistently above 0.95). Spatiotemporal evolution models reveal that Chongqing maintains a high overall PER. Notably, from 2019 to 2020, the proportion of administrative units classified as highly resilient peaked at 24.5%, marking a historical high. (3) Multi-year average rainfall primarily impacts PER (ranked first), while Gross Domestic Product (GDP) significantly affect SER. The development of multi-dimensional recovery indicators provides a robust framework for assessing resilience against landslides in mountainous cities. The CCD model illustrates the importance of regional dynamic coordinated development in resilience trajectories. This study provides a detailed blueprint for the scientific development of resilient mountainous cities, emphasizing the need for a spatial-temporal perspective on resilience and the benefits of coordinated regional development.

The barriers to uptake of disaster risk management science in urban planning: A political economy analysis

There is increasing effort in science to support disaster risk management (DRM) and climate change adaptation in urban environments. It is now common for research calls and projects to reference coproduction methods and science uptake goals. This paper identifies lessons for researchers, research funders, and research users wishing to enable useful, useable, and used science based on the perspectives of research users in urban planning from low- and middle-income countries. DRM-supporting science is viewed by policy actors as: complicated and poorly communicated; presenting inadequate, partial, and outdated information; misaligned with policy cycles; and costly to access and inadequately positioned to overcome the policy barriers that hinder integration of DRM into urban planning. Addressing these specific concerns points to more systematic collection and organisation of data and enhancement of supporting administrative structures to facilitate better sight of human vulnerability and its link to development decision-making and wider processes of urban risk creation.

Investigation of Psychometric Properties and Correlation with Psychological Distress after Hurricane Hazards in Puerto Rico

BACKGROUND

Puerto Rico (PR) is highly vulnerable to hurricanes, which severely impact cancer survivors by causing healthcare disruptions and increasing stress. This study investigates the reliability and factor structure of the Hurricane Hazards Inventory (HHI) and its relationship with psychological distress among cancer survivors and non-cancer controls in PR.

METHODS

Using secondary data from a longitudinal study following Hurricane Maria (HM), the baseline assessment included sociodemographic data from participants, HHI, Patient Health Questionnaire (PHQ-8), and Generalized Anxiety Disorder (GAD-7). Statistical analyses involved descriptive statistics, Exploratory Factor Analysis (EFA), and Partial Least Squares Structural Equation Modeling (PLS-SEM).

RESULTS

Among 260 participants, 78.7% were women, with a median age of 58.0 years. EFA reduced the HHI to 17 items grouped into three factors explaining 62.6% of the variance with excellent reliability (Cronbach's alpha 0.91). The three factors also showed good to excellent reliability (alpha 0.81 to 0.92). The median HHI score was 11.0 (range 4.0-26.5) out of 68. PLS-SEM revealed a direct effect of being a cancer survivor and tertiary hazards on depression and anxiety.

CONCLUSION

The HHI is a valid and reliable tool for assessing mental health impact in cancer survivors after hurricanes. However, the study had limitations, including its small sample size and lack of control for all confounding variables. Future research with larger and more diverse samples is needed to further validate the HHI and examine its generalizability.

Global insights from local actions: a case study on enhancing flood disaster management efficiency in China's Greater Bay Area

This study examines the flood disaster management network within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 2015 to 2021, identifying government department involvement and influence shifts. Key findings indicate a decrease in the centrality of the Public Security Office and Department of Transportation, suggesting a strategic shift toward more specialized, technology-driven disaster management. Conversely, the Science Bureau's increased engagement, from 8.43% to 12.84%, highlights a policy shift toward scientific research and technological innovation in managing flood risks. The analysis reveals underutilized communication between the Central Committee, the Poverty Alleviation Office, and the Publicity Department, highlighting opportunities for improved integration in disaster management and public communication strategies. To address these issues, the study suggests strengthening inter-departmental collaboration to leverage technological advancements in disaster management. It also recommends integrating flood disaster management with poverty alleviation initiatives to support affected populations comprehensively. Increasing the involvement of the Publicity Department is crucial for improving timely and transparent communication of flood-related data to the public. The conclusions advocate for an adaptive, strategically planned network approach to flood disaster management in the GBA, aiming to bolster responsiveness and preparedness for future flood events.

Rapid assessment of public interest in drought and its likely drivers in South Africa

The monthly search volumes for drought were extracted from Google® for South Africa using the Keywordsevery-where.com plugin from January 2004 until June 2022. To identify the potential qualitative drivers for such public interest the following data extracted by the plugin were investigated and analysed: the drought-related keywords, the long-tail keywords similar to drought, and the "people also searched for category" from the South African users. The Google Trends monthly score was extracted for South Africa and the Eastern Cape Province, and specific local municipalities/towns/cities in the province. The aim was to assess the relative significance of the drought interest in comparison to public interest in other search terms. The results of the Kruskal-Wallis analyses of variance by ranks showed that there was a statistically significant difference between individual values of the monthly search volumes for drought in South Africa, as a function of time of data extraction (5 percent level of significance; p-value ≤ 4.7 × 10-14). The monthly search volumes increased with time, which is based on the results of the Mann-Kendall test at a 5 percent level of significance (p-value ≤ 0.0092). Analyses of the Google Trends scores indicate that the relative interest in drought in South Africa and the Eastern Cape Province increased with time between January 2004 and June 2022 (the Mann-Kendall test at a 5 percent level of significance; p-value = 0.0011). The population's searches for drought were relatively low when compared to other search terms on Google. Drought adaptation of the South African community could be considered a driver of the Google searches for drought, but it is a marginal topic compared to other topics in Google searches. It might be necessary to increase this significance by investigating the "Google-search patterns for droughts" in the areas of Tshikaro, Mafusini, Cofimvaba, and Nxotsheni in the Eastern Cape Province of South Africa.

Aeolian disaster risk evaluation in the African Sahel

The Sahel is facing a serious environmental crisis due to aeolian disaster that has seriously affected the local development and survival of residents. Thus, evaluating the aeolian disaster risk levels and their variation in the Sahel is important. This study established an optimal model by evaluating the applicability of different models in the aeolian disaster risk determination in the Sahel. Using this model, the spatiotemporal changes in the risk subsystem of aeolian disaster (hazard, sensitivity, vulnerability, and restorability) and the aeolian disaster risk in the Sahel from 2000 to 2020 were analyzed. Based on this analysis, the impact of climate change and human activities on the aeolian disaster risk in the Sahel was evaluated. Results revealed that the variable fuzzy recognition (VFR) based on the aeolian disaster risk index (ADRI) model had the highest accuracy, reaching 89.72 %. The middle of the Sahel, located in the desert-grassland transition zone, exhibited a high hazard, sensitivity, and vulnerability, rendering it highly susceptible to aeolian disaster. The proportion of areas with very low and very high aeolian disaster risk levels decreased from 2000 to 2020, while those with low and high levels increased, and the change in moderate risk level areas remained relatively stable. Areas of low, moderate, and high risk are more sensitive to climate change and human activities and are subjected to greater pressure for change. Human activities were the main factor for the change of ADRI in the Sahel, accounting for 69.74 and 58.19 % of the increased and decreased areas of ADRI, respectively. This study evaluated the level of aeolian disaster risk in the Sahel and identified the main driving factors, providing a reference for Sahel countries to better implement the Green Great Wall (GGW) program in Africa, thereby mitigating the adverse effects of aeolian disaster.

Exploring the spatial pattern of house collapse rates caused by extreme rainfall in central China: The role of natural and social factors

The collapse of houses represents a prominent hazard associated with floods, mudslides, and other disastrous events resulting from extreme rainfall. Nevertheless, previous research in this area has been insufficiently dedicated to comprehending the factors that specifically contribute to house collapse triggered by extreme rainfall. This study endeavors to address this knowledge gap by proposing a hypothesis that the occurrence of house collapse, induced by extreme rainfall, demonstrates spatial heterogeneity and is subject to the interactive impacts of various factors. In the study, we investigate the relationship between house collapse rates and natural and social factors in the provinces of Henan, Shanxi, and Shaanxi provinces in 2021. These provinces are representative of flood-prone areas in central China. Spatial scan statistics and GeoDetector model were used to analyze spatial hotspot areas of house collapse rates and determinant power of natural and social factors on the spatial heterogeneity of house collapse rates, respectively. Our analysis reveals that the spatial hotspot areas predominantly concentrated in regions characterized by high rainfall, including areas along riverbanks and low-lying regions. Multiple factors contribute to the variations in house collapse rates. Among these factors, precipitation (q = 0.32) is the most significant, followed by the ratio of brick-concrete houses (q = 0.24), per capita GDP (q = 0.13), elevation (q = 0.13) and other factors. Notably, the interaction of precipitation and slope explains 63 % of the damage pattern, making it the strongest causal factor. The results substantiate our initial hypothesis and underscore the fact that the pattern of damage does not solely rely on a singular factor but rather on the interaction of multiple factors. These findings hold significance in advancing the formulation of more precise strategies aimed at bolstering safety measures and safeguarding properties within regions susceptible to flooding.

Development of a dynamical statistical analog ensemble forecast model for landfalling typhoon disasters

In this report, the development of a Dynamical Statistical Analog Ensemble Forecast model for landfalling typhoon disasters (LTDs) and some applications over coastal China are described. This model consists of the following four elements: (i) obtaining the forecast track of a target landfalling typhoon, (ii) constructing its generalized initial value (GIV), (iii) identifying its analogs based on the GIV, and (iv) assembling typhoon disasters of the analogs. Typhoon track, intensity, and landfall date are introduced in GIV at this early development stage. The pre-assessment results show that the mean threat scores of two important damage levels of LTDs reach 0.48 and 0.55, respectively. Of significance is that most of the damage occurs near the typhoon centers around the time of landfall. These results indicate the promising performance of the model in capturing the main damage characteristics of typhoon disasters, which would help coastal community mitigate damage from destructive typhoons.

Saragat WR, Mae S. Zuñiga HR, Gumasing MJJ. Antecedents of behavioral intentions for purchasing safety tools among women

The rise of crimes and violence against women are evident worldwide. The self-protection and behavioral aspects however are underexplored. The need for assessment for safety such as the purchasing intentions of safety tools should be considered to promote the mitigation and reduction of violence and crimes against women, may it be in households or outdoors. This study aimed to holistically analyze the determinants of behavioral intentions to purchase self-defense tools among women. Focusing on the Philippines, the structural equation modeling considering the extended theory of planned behavior (TPB) and protection motivation theory (PMT) integrated model was completely analyzed. A total of 553 valid respondents were purposively gathered to completely assess the behavioral domains and protective behaviors of women. From the results, self-efficacy showed the most significant factor affecting purchasing intentions, followed by behavioral intentions, and the behavioral domains under TPB. Moreover, indirect effects of PMT variables to purchasing intentions were seen; highest from understanding of safety, perceived risk, and then perceived severity. The extended latent variable such as perceived safety showed an indirect effect while buying impulse showed a direct significant effect on purchasing intentions. This is considered as the first study that assessed the different variables affecting purchasing intentions of self-defense tools. The findings of this study would provide a gateway as benchmark for how women feel, behave, and seeks protection. Implementing the suggestion with other aspects would end up promoting the overall safety of a country, not just for women, but for all victims against crime and violence.

Multi-Disaster Integrated Risk Assessment in City Range-A Case Study of Jinan, China

Urban multi-disaster integrated risk assessment is an important part of urban sustainable development and territorial spatial planning. Based on the results of integrated risk assessment, the scientific and effective performance of disaster prevention and reduction can be effectively improved. This study determines a multi-disaster integrated risk assessment system. The system evaluates the hazard level of disasters, the exposure level of disaster bearing bodies, the vulnerability level of disaster bearing bodies, and the urban resilience level, and determines the city's integrated risk level on this basis. Taking Jinan as an example, the risk, exposure, vulnerability, resilience, and integrated risk level of Jinan City were analyzed. The results show that the system reasonably analyzes the multi-disaster integrated risk level, and according to the assessment results, countermeasures for disaster prevention and suggestions for territorial spatial planning were put forward.

Level of emergency and disaster preparedness of public hospitals in Northwest Ethiopia: A cross-sectional study

•

Low- and middle-income countries like Sub Saharan Africa repeatedly experience natural and manmade disasters.

•

Emergencies and disasters frequently have serious consequences for people's health, including the loss of many lives and significant disruptions in community functioning.

•

Emergency and disaster preparedness, on the other hand, is still in its early stages in Africa.

•

Personnel shortages, weakened health systems, mishandling of scarce resources, and political instability are among the challenges facing disaster management in Africa.

•

This study is projected to fill an information gap about the state of hospitals’ emergency and disaster preparedness.

Background

From time to time, the magnitude and type of health emergencies and disasters are increasing. Hospital emergency and disaster preparedness, on the other hand, is still in its early stages in many low- and middle-income countries. In Ethiopia, research on hospital disaster preparedness is severely limited. As a result, the purpose of this study was to determine the level of hospital emergency and disaster preparedness at public hospitals in the east Gojjam zone of Northwest Ethiopia.

Methods

A census method was used to include ten hospitals in the East Gojjam zone in a cross-sectional descriptive study. An adopted World Health Organization observation checklist was used to assess disaster and emergency preparedness. Each question was assigned a score out of three points, with one indicating low readiness and three indicating the highest level of preparation. Finally, the level of preparedness was classified as “low“ if the average percentage score ranged from 33.3% to 66.6 %, and as “high” if the percentage score ranged from 66.7 % to 100 %. The results were then presented in the form of texts, tables, and percentages.

Results

The evaluated hospitals' overall level of emergency and disaster preparedness falls into the low category, with an average calculated preparedness score of 54.75 %. The domain with the lowest preparedness is logistics and finance (43.33 %), while the domain with the highest preparedness is patient care and support services (60 %).

Conclusion

According to the findings of this study, the level of emergency and disaster preparedness in the hospitals studied is low. It is therefore recommended that the ministry of health, regional health bureaus, and hospital administrators collaborate to develop an appropriate intervention strategy to address this issue.

Disaster resilience framework indicators for a city’s disaster resilience planning strategy

Determining the level of a city’s disaster resilience and developing a disaster resilience strategy is an important process towards understanding the current and potential future risk of cities. However, the process of determining and mapping the level of urban disaster resilience presents a challenge for the City of Tshwane, as it requires a consolidated and coordinated commitment and collaboration from various role players. This research study developed disaster resilience framework indicators for the City of Tshwane to determine its current disaster resilience and to contribute to its disaster resilience and sustainable development planning strategy. The research assumed a case study design using a qualitative approach to gather data through document analysis and one-on-one interviews. Ten disaster resilience framework indicators were identified as essential indicators in assisting the City of Tshwane with its endeavour to be a disaster resilient city.

Reducing livestock snow disaster risk in the Qinghai-Tibetan Plateau due to warming and socioeconomic development

Global warming can have positive or negative impacts on society depending on sectors and changes in climate impact drivers, resulting in opportunities or risks. The same holds true for social-economic changes. However, past research has mostly focused on assessing risks, leaving potential opportunities under-addressed. Here, we simulated the impact of climate change and socioeconomic development on livestock snow disasters over the Qinghai-Tibetan Plateau during 1986-2100, by integrating the drivers of climate and socioeconomic changes via an event-based disaster risk assessment model. Model results show climate change and socioeconomic development contributes about equally to reducing livestock loss in snow disasters by 4% yr^-1 up to 2100 under representative concentration pathway 8.5 and shared-socioeconomic pathway 5. The marginal benefit from climate change was projected to be a 43.2% reduction in annual average loss per degree kelvin warming, and that from socioeconomic development was a 12.4% reduction per 100% increase in gross domestic production. In a 2 °C warmer world, the annual average loss could be 91% smaller compared with the baseline period (1986-2005). Limiting global warming to 1.5 °C instead of 2 °C would reduce the benefit by 5%, requiring a 135% increase in the marginal benefits of prevention capacity to offset the reduction.

Risk Assessment of Population Loss Posed by Earthquake-Landslide-Debris Flow Disaster Chain: A Case Study in Wenchuan, China

Earthquakes often cause secondary disasters in mountainous areas, forming the typical earthquake-landslide-debris flow disaster chain for a long time that results in a series of losses. It is important to improve the risk assessment method from the perspective of cascading effect of such a disaster chain, by strengthening quantitative research on hazards of the debris flows which are affected by landslide volume and rainstorm intensity. Taking Wenchuan County as an example, the risk assessment method for population loss of the disaster chain is established and the risks are evaluated in this paper. The results show that the population loss risk is 2.59–2.71 people/km2 under the scenarios of the Wenchuan Ms8.0 earthquake and four rainstorm intensities. The impacts of landslide and debris flow after the earthquake were long-term and profound. A comparison of risks caused by each element of the chain revealed that the risk associated with the earthquake accounted for the highest proportion, and landslide and debris flow accounted for 38.82–37.18% and 3.42–7.50%, respectively. As the earthquake intensity increases, the total risk posed by the disaster chain increases significantly. The risk caused by the earthquake is the highest in high earthquake intensity zones; while in the lower-intensity zones, landslides and debris flows pose relatively high risks. The risk assessment results were verified through comparison with actual data, indicating that the simulation results are quite consistent with the existing disaster information and that the risk assessment method based on the earthquake-landslide-debris flow cascade process is significant for future risk estimation.