Compound Disaster Research Articles

Numerical Investigation of coupling hazard zone of coal spontaneous combustion and gas in gob for high-gas mines

As coal mining operations continue to deepen, the frequency of coal spontaneous combustion (CSC) and gas explosion disasters in high-gas mines is increasing. Understanding the distribution patterns of CSC and gas compound disaster zones in the gob during the extraction process is crucial for reducing the risks of combustion and explosion. This study focuses on the 201 working face of the Shuanglong Coal Mine, where a multi-physical field coupling model of pressure, temperature, gas seepage, and diffusion was established to investigate the evolution characteristics of compound disaster zones and propose corresponding prevention and control measures. The results demonstrate that the area with the most severe composite hazard is mainly located at the return roadway side, extending to the middle of the gob. With increased ventilation volume and advance rate, the area of the CSC and gas coupling hazard zone expands continuously. By implementing measures such as brattice cloth and nitrogen injection, the areas of spontaneous combustion and CH4 explosion zones were reduced by 53.6 % and 49.5 %, respectively, effectively controlling the extent of the compound disaster zone and eliminating the risk of gas explosions.

Quantitative characterization, spatiotemporal evolution, and analysis of driving factors of daily dry-wet abrupt alternation: A case study of the Ganjiang River Basin

Study RegionThis study focuses on the Ganjiang River Basin, a major tributary of the Poyang Lake located in southern China. Study FocusWith the growing frequency of extreme weather events driven by climate change, there is increased attention on compound disasters such as Dry-Wet Abrupt Alternation (DWAA). This study aims to quantify and define DWAA in the Ganjiang River Basin by developing and applying a DWAA Index (DWAAI) using a percentile threshold method. The objective is to investigate the spatiotemporal characteristics and patterns of DWAA in the region. Precipitation data from 12 meteorological stations were analyzed to track these events from 1970 to 2019. New Hydrological Insights For the regionThe results of this study provide new insights into DWAA dynamics in the Ganjiang River Basin. Key findings include: (i) The DWAAI effectively captures the extremes of Dry-Wet Abrupt Alternations, especially at the 1st and 99th percentiles; (ii) The basin experienced 37–48 dry-to-wet events (DtWs) during the study period, with higher frequencies observed in the central-eastern, western, and northern mountainous areas, and lower frequencies in the southern regions; (iii) Wet-to-dry events (WtDs) were less common than DtWs and exhibited a distinct spatial and temporal shift from the southern mountains toward the central basin; (iv) Temperature was identified as the dominant factor influencing DWAAI changes, while large-scale atmospheric patterns such as AO, ENSO, PDO, and Sunspot activity showed insignificant correlations. These findings offer critical insights for improving water resource management and climate adaptation efforts in the region.

Compound disaster characteristics of rock burst and coal spontaneous combustion in island mining face: A case study

The island mining face in coal mines often encounters stress concentration and significant air leakage, elevating the risk of rock burst and spontaneous combustion of residual coal in the goaf. This study centers on the investigation of the 9305 island mining face within a mine situated in Shandong Province, China. Leveraging the features of coal spontaneous combustion and data from microseismic and gas monitoring throughout the mining process, a novel method for calculating safe mining speeds under compound disasters is introduced. The safe mining speed of the 9305 island mining face is stratified, and a prevention and control technology integrating long distance directional drilling for impact-spontaneous combustion compound disasters is proposed. Findings suggest that to mitigate spontaneous combustion of residual coal, considering the seam's spontaneous combustion tendency, the safe mining speed should exceed 3.7 m per day. Accounting for the distribution of microseismic events during coal seam extraction, the safe mining speed is maintained below 4.8 m per day in the unprotected mining area and capped at 8 m per day in the protected zone. Through a comprehensive analysis considering coal seam spontaneous combustion tendency, impact tendency, and time to coal seam oxidation to critical temperature, the safe mining speed for the island mining face ranges from 3.7 m per day to 4.8 m per day in the unprotected area and from 5.14 m per day to 8 m per day in the protected area. The proposed long distance directional drilling 'one hole, multiple purposes' scheme enables an integrated approach encompassing pressure relief before coal seam extraction, water injection during mining, and grouting post-mining. This method effectively prevents and controls the compound disasters of rock burst and coal spontaneous combustion, presenting innovative technical solutions for the safe extraction of coal resources.

Evaluating Design Flood Levels Using a Machine Learning-based Costal Compound Flood Level Model

Coastal floods, a type of compound disaster, results from the interactions between rainfall and tides. However, in Korea, the design flood level for coastal areas typically relies on the average water level according to the tide, ignoring this interaction. This study aimed to address this gap by developing a machine learning-based compound flood level model that incorporates the interactions between rainfall and tides. It also evaluated the adequacy of the design water level in the Taehwa River basin, a representative tidal river. Before developing the model, Discrete Wavelet Transformation (DWT) was used to identify the components of the compound flood level. The DWT results indicated that the compound flood level comprised three elements: rainfall-runoff, tides, and noise. A Long Short-Term Memory (LSTM) model was then created using these elements as input to estimate the compound flood level for a 200-year frequency, which is the design frequency of the Taehwa River. The compound flood level calculated by the model was 6.15 m, which is higher than the established design flood level of the Taehwa river (5.79 m). This discrepancy indicates that the current flood measurements for the Taehwa River are inadequate in accounting for compound flooding. Based on these findings, we recommend incorporating the compound flood concept when calculating the design water levels in coastal areas.

Compounding disaster: Perceptions of coastal risk, extreme events, and oil and gas energy production in the Gulf of Mexico

With more than five million people living in proximity to oil and gas (OGA) infrastructure, the state of Texas has the largest population at risk for developing health problems attributable to the industry in the U.S. The interaction between environmental and technological events, one kind of compound disaster events, has the potential to increase future health risks and aggravate existing social and environmental impacts. To identify current knowledge and awareness of the risks of compound disasters among residents, this article presents findings from interviews conducted in 2017 and 2019 with key stakeholders from Corpus Christi, Texas. The city is a hub of OGA production and transport and has recently suffered from the devastating effects of Hurricane Harvey. The primary set of interviews (n: 23) is also complemented by the analysis of 2 other collections (n: 20) from residents who were affected by Hurricane Harvey and which are stored at Texas A&M University-Corpus Christi's library. Findings underscore the lack of awareness of OGA activities in general and of problems related to environmental racism. We also found a normalization of the impacts of small oil incidents among respondents and biased perceptions of development. Knowledge of the risk of compound events is rare, an issue that poses significant concerns for the future of these communities and their ability to prepare and mitigate.

A framework for using event evolutionary graphs to rapidly assess the vulnerability of urban flood cascade compound disaster event networks

Increasingly frequent flood disasters have caused great losses in recent years. Urban floods induce not only natural geological disasters but also social accidents. These disaster events, called urban flood cascade compound disaster events (UFCCDEs) in this study, have significant cascade, superposition, and amplification effects. However, conventional data sources and processing methods make it difficult to analyze the detailed course of disaster events caused by urban floods, thereby hindering the vulnerability assessment of UFCCDE networks (UFCCDENs). Herein, we propose a framework considering the interactions between disaster events caused by urban floods for rapidly and comprehensively assessing the vulnerability of the UFCCDEN. First, social media data (Sina Weibo) are processed to analyze the spatio-temporal distribution of UFCCDEs and construct a UFCCDEN based on an event evolutionary graph. Second, complex network theory is applied to evaluate the importance of disaster events and the vulnerability of disaster causal chains in the constructed UFCCDEN. Finally, the global efficiency of the network is calculated to assess the propagation efficiency of the UFCCDEN before and after implementing disaster mitigation strategies based on the assessment results to demonstrate the performance of the assessment framework. The coastal megacity Guangzhou was selected as an example. The results showed that, social media data can provide detailed and valid information about UFCCDEs, which can be used to construct the UFCCDEN based on the event evolutionary graph. Waterlogging is found to be the most important disaster event in the UFCCDEN. Furthermore, power facilities, drainage facilities, and roads should be given top priority in the prevention and mitigation of urban floods because of their significant cascading amplification effects. The proposed framework can make the propagation efficiency of the UFCCDEN markedly decrease by 37–62% and 44%, based on the assessment results of disaster events and causal chains, respectively.

Assessment of urban inundation and prediction of combined flood disaster in the middle reaches of Yellow river basin under extreme precipitation

Watershed Cities often face the dual flood risks of upstream floods and urban waterlogging. This compound disaster is caused by the interaction of multiple factors (topography, storms, upstream water and urban drainage, etc.), and is particularly affected by extreme rainfall events and the large and small drainage carrying capacity. To explore the combined effects of extreme rainfall and drainage systems, this study applied the Chicago rainfall hyetograph method and constructed design under different return periods. A comprehensive model combining the verified SWMM and LISFLOOD hydraulic models was utilised to build one-dimensional and two-dimensional coupled watershed urban flood models, simulating inundation depth and duration. By considering urban rainfall, runoff, topography, and drainage system characteristics, the flood processes under different extreme rainfall scenarios were simulated, and the node overflow and inundation depth were obtained. A flood risk assessment of watershed cities was conducted by combining methods such as the HR threshold method, evaluation level, and threshold division. In this study, Huyi District of Xi’an City, China, was used as the research area. The main research findings show: (1) the precipitation design values for different return periods were calculated based on the proposed method, with amount for a 100-year event being 87.196 mm, suitable for composite flood simulation; (2) applying the SWMM-LISFLOOD coupled model constructed for midstream urban areas ensured the accurate simulation of composite flood processes. Under different extreme rainfall return period scenarios, the percentage of flood inundation depth exceeding 1 m caused by multiple disaster factors increased from 0.73 % to 5.19 %; (3) extreme rainfall leads to different levels of internal flooding risk. When the return period of extreme rainfall is 5 years, the area inundated by composite floods in the research area is 67.21 km2. In comparison, when the return period of extreme rainfall is 50 years, the area inundated by composite floods in the research area significantly increases to a total inundation area of 286.85 km2. This study is expected to provide scientific references for flood prevention planning, composite disaster risk management, and urban resilience building in watershed urban areas while significantly impacting modern economic growth, social stability, and the safety of watershed cities.

Dynamic evolution characteristics and hazard assessment of compound drought/waterlogging and low temperature events for maize

Hazard assessment is fundamental in the field of disaster risk management. With the increase in global warming, compound water and temperature events have become more frequent. Current research lacks risk assessments of low temperatures and their compound events, necessitating relevant hazard assessment work to improve the accuracy and diversity of maize disaster prevention and mitigation strategies. This study comparatively analyzed the dynamic evolution characteristics and hazards of compound drought/waterlogging and low temperature events (CDLEs and CWLEs) for maize in the Songliao Plain during different growth periods from 1981 to 2020. First, composite drought/waterlogging and low temperature magnitude indices (CDLMI and CWLMI) were constructed to quantify the intensity of CDLEs and CWLEs by fitting non-exceedance probabilities. Next, static and dynamic hazard assessment models were developed by fitting probability density and cumulative probability density curves to CDLMI and CWLMI. The results showed that the correlations between SPRI and LTI across different decades were mainly negative during the three growth periods. The hazard ratings for both CDLEs and CWLEs were relatively high in the northern part of the study area, consistent with the higher occurrence, duration, and severity of both CDLEs and CWLEs at higher latitudes. Relative to 2001–2010, the center of gravity of hazard shifted southward for CDLEs and northward for CWLEs in 2011–2020. The mean duration, frequency, and hazard were generally higher for CWLEs, but CDLEs were associated with more severe maize yield reductions. This study provides new insights into compound disaster risk assessment, and the research methodology can be generalized to other agricultural growing areas to promote sustainable development of agricultural systems and food security.

Escalating tropical cyclone precipitation extremes and landslide hazards in South China under global warming

Tropical cyclones (TCs) are expected to produce more intense precipitation under global warming. However, substantial uncertainties exist in the projection of coarse-resolution global climate models. Here, we use deep learning to aid targeted cloud-resolving simulations of extreme TCs. Contrary to the Clausius-Clapeyron (CC) scaling, which indicates a 7% moisture increase per K warming, our simulations reveal more complex responses of TC rainfall. TCs will not intensify via strengthened updrafts but through the expansion of deep convective cores with suppression of shallow cumulus and congestus. Consequently, while localized hourly rainfall may adhere to the CC scaling, precipitation accumulation over city-sized areas could surge by 18%K-1. This super-CC intensification due to changing TC structure has profound implications for floods and landslides. Estimations using Hong Kong’s slope data confirm this concern and suggest an up to 215% increase in landslide risks with 4-K warming, highlighting amplified threats from compound disasters under climate change.

Increasing Risk of a “Hot Eastern‐Pluvial Western” Asia

AbstractObservations have revealed that the deadly “hot eastern‐pluvial western” climate pattern in Asia in summer 2022 is by no means an exception. In recent decade this pattern is becoming much more frequent owing to the notable westward extension and enhancement of the western Pacific subtropical high (WPSH). The anomalously enhanced WPSH fills the gap in geopotential heights between the Arabian Sea‐Iranian Plateau and the western Pacific, produces a heat dome over eastern Asia and intensifies the moisture convergence over western Asia by changing the water vapor transportation path. Projections of 19 CMIP6 models show that both the temperature in eastern Asia and precipitation in western Asia will remarkably increase under Shared Socioeconomic Pathway (SSP) 2‐4.5, SSP 3‐7.0, and SSP 5‐8.5 scenarios, with temperature anomalies 0.8°C, 1.5°C, and 2.4°C higher and the percentages of precipitation anomaly 6.3%, 9.4%, and 12.5% larger than the reference period in the near, middle, and long terms under the moderate emission scenario (SSP2‐4.5). Therefore, the “hot eastern‐pluvial western” Asia is becoming a new normal and exacerbating the risk of compound disasters.

Rapid Crisis Response in Resilient Cities: Emergency Response to and Reconnaissance of Earthquake Disasters in Taiwan

The devastating Chichi earthquake in Taiwan in 1999 highlighted the importance of disaster prevention and relief operations. In response to the challenge of extreme events and compound disasters, the National Science and Technology Center for Disaster Reduction (NCDR) contributes to operations at the Central Emergency Operation Center (CEOC) of Taiwan by providing integrated information and timely suggestions, and it delivers a common operational picture to central and local governments through a decision support system. This study was undertaken to explore the emergency response towards the reconnaissance of earthquake disasters in Taiwan to illustrate how resilient cities ensure rapid crisis response with a focus on the NCDR disaster response decision support system. This study examines the decision support system used following the 2016 ML 6.6 Meinong earthquake. The results demonstrate that the first line of relief for the emergency response commander is data-driven decision-making.

Study on the Influence of Different Gas Concentrations on Coal Spontaneous Combustion

ABSTRACT The coexistence of gas and spontaneous coal combustion poses a serious threat to mine production safety. Therefore, studying the compound disaster of gas and spontaneous coal combustion and revealing the impact of gas concentration on the characteristic parameters of coal spontaneous combustion are of great significance for understanding the mechanism of compound disasters involving coal and gas and for comprehensive management. Based on theoretical analysis, this paper selects four typical types of cannel coal、non-caking coal、meager coal、anthracite coal as research subjects, and conducts programmed heating experiments on coal samples under different gas concentration conditions, aiming to provide a theoretical basis for the prevention and control of spontaneous coal combustion in a gas environment. Experimental results show that with the increase in temperature of the coal samples, the oxygen consumption rate and heating emission intensity exhibit a trend of slow increase followed by rapid increase. With the increase in gas concentration in the environment, the production of CO and CO2, oxygen consumption rate, and heat emission intensity of coal spontaneous combustion all show a decreasing trend. This is mainly because the high gas concentration occupies the adsorption sites on coal molecules, thereby hindering the reaction between coal and oxygen. Additionally, by calculating the thermodynamic parameters of the coal samples, it was found that the apparent activation energy increases with the increase in gas concentration, further confirming that the increase in gas concentration in the environment significantly inhibits the spontaneous combustion process of coal.

Pandemic impacts and experiences after disaster in Australia: qualitative study of compound impacts following the Black Summer bushfires.

The first cases of the COVID-19 pandemic in Australia were recorded in January 2020, which was during the 'Black Summer' bushfires of 2019-20 and prior to additional disasters in some regions. Few studies have considered the compound impact of disasters and the pandemic. To improve understanding of the impact on mental health and well-being of the pandemic in disaster-affected communities. We conducted semi-structured interviews (n = 18) with community members and online focus groups (n = 31) with help providers from three regions of rural Australia affected by bushfires and the pandemic. Six themes were produced: (a) 'Pulling together, pulling apart', describing experiences after bushfires and prior to impacts of the pandemic; (b) 'Disruption of the 'normal response', encompassing changes to post-disaster recovery processes attributed to the pandemic; (c) 'Escalating tensions and division in the community', describing impacts on relationships; (d) 'Everywhere you turn you get a slap in the face', acknowledging impacts of bureaucratic 'red tape'; (e) 'There are layers of trauma', highlighting intersecting traumas and pre-existing vulnerabilities; and (f) 'Where does the help come from when we can't do it?', encompassing difficulties accessing services and impacts on the helping workforce. This study furthers our understanding of compound disasters and situates pandemic impacts in relation to processes of adjustment and recovery from bushfires. It highlights the need for long-term approaches to resilience and recovery, investment in social infrastructure, multi-component approaches to workforce issues, and strategies to increase mental health support and pathways across services.

Resilience in complex disasters: Florida's hurricane preparedness, response, and recovery amid COVID-19

The COVID-19 pandemic and active hurricane seasons posed complex challenges for coastal communities, requiring innovative and adaptive emergency management approaches. Using in-depth interviews with Florida emergency management professionals, this study examines emerging challenges and strategies implemented by governmental and nonprofit agencies during the hurricane-pandemic compound disasters of the 2020 and 2021 hurricane seasons. Our findings reveal the interconnectedness of challenges across different disasters and their interplay with existing vulnerabilities. We find that social distancing due to COVID-19 strained human and financial resources for hurricane preparedness, response, and recovery. Moreover, the increased remote work due to COVID-19 increased reliance on information communication technologies (ICTs), which intensified the negative impacts of the existing urban-rural digital divide in Florida. These ICT challenges impeded inter-agency collaboration and external funding for rural communities, further amplifying disparities in hurricane response and recovery. Our study also uncovers multifaceted strategies addressing competing priorities between hurricane evacuation and COVID-19 prevention, resource limitations, information and communication gaps, and collaboration challenges. These insights provide practical guidance to coastal communities to enhance future preparedness and response efforts in hurricane-pandemic compounding disasters.

Exploring the spatial and temporal changes of compound disasters: A case study in Gaoping River, Taiwan

Global climate change has resulted in unusual climatic events of increasing intensity and frequency with severe impacts. An individual disaster is often coupled with another at the same time or in the form of a cascade. Major issues discussed in disaster management range from risks, environmental vulnerability, and resiliency, to the identification of human disaster-inducing land uses and their locations across a region, particularly in watersheds. The accurate identification of these disaster-inducing areas – that is, those locations of land use that may cause or contribute to making downstream impacts worse than they would be in the absence of such land uses – would be of assistance for disaster management agencies in order to mitigate disasters in advance. This study applies spatial autocorrelation statistics to explore the spatial and temporal dynamics associated with compound disasters. The study then utilizes the Soil and Water Assessment Tool (SWAT) to calculate runoff volume and sediment discharge to identify the locations of human disaster-inducing land uses. Our modeling outcomes show that there are various kinds of spatial and temporal clusters among compound disasters, and that certain areas are affected by similar disasters regularly while other locations might be the cause of these regular disasters.

Comparative analysis of permeability model construction and risk fields evaluation by roof cutting along the gob in a coal mine.

The productivity of coal mines is seriously threatened by the combined disasters of gas and coal spontaneous combustion, which have become a common disaster mode. It is unclear how the gas and coal spontaneously combusted in the roof cutting along gob working face. The goal of this study is to identify the distinctive features of combined disasters in gob from two different types of roof cutting along working faces. In these two different types of roof cutting along gob working faces, the paper constructs the permeability model of the gob. The findings demonstrate that the data from the field experiment and the simulation results agree, which validates the simulation's reliability. In contrast to single sided roof cutting along gob working faces, double sided roof cutting along gob working faces clearly has a thinner oxidation zone. Moreover, the oxidation zone of the double side roof cutting along gob working faces is closer to the working face, which is located in the shallow area of the gob 50m behind the working face. The gas explosion area and the coal spontaneous combustion area are divided by the double side roof cutting along gob working face, which reduces the risk of compound disasters. Important theoretical direction for the prevention and control of gob disasters in the roof cutting along gob working face is provided by the simulation results.

Improving mental health following multiple disasters in Australia: a randomized controlled trial of the Skills for Life Adjustment and Resilience (SOLAR) programme

ABSTRACT Background: The mental health impacts of climate change-related disasters are significant. However, access to mental health services is often limited by the availability of trained clinicians. Although building local community capability for the mental health response is often prioritised in policy settings, the lack of evidence-based programs is problematic. The aim of this study was to test the efficacy of the Skills for Life Adjustment and Resilience programme (SOLAR) delivered by trained local community members following compound disasters (drought, wildfires, pandemic-related lockdowns) in Australia. Method: Thirty-six community members were trained to deliver the SOLAR programme, a skills-based, trauma informed, psychosocial programme. Sixty-six people with anxiety, depression and/or posttraumatic stress symptoms, and impairment were randomised into the SOLAR programme or a Self-Help condition. They were assessed pre, post and two months following the interventions. The SOLAR programme was delivered across five 1-hourly sessions (either face to face or virtually). Those in the Self-Help condition received weekly emails with self-help information including links to online educational videos. Results: Multigroup analyses indicated that participants in the SOLAR condition experienced significantly lower levels of anxiety and depression, and PTSD symptom severity between pre – and post-intervention (T1 to T2), relative to the Self-Help condition, while controlling for scores at intake. These differences were not statistically different at follow-up. The SOLAR programme was associated with large effect size improvements in posttraumatic stress symptoms over time. Conclusion: The SOLAR programme was effective in improving anxiety, depression and posttraumatic stress symptoms over time. However, by follow-up the size of the effect was similar to an active self-help condition. Given the ongoing stressors in the community associated with compounding disasters it may be that booster sessions would have been useful to sustain programme impact. Trial registration: Australian New Zealand Clinical Trials Registry identifier: ACTRN12621000283875..

A study on compound flood prediction and inundation simulation under future scenarios in a coastal city

Coastal cities are affected by the compound effects of flood hazard systems, including the ocean, river, and coastal land, within which the disaster-induced factors interact complexly. To explore the combined effects of multiple disaster-causing factors under changing environment, this study first constructed univariate distribution by maximum daily precipitation of the year at Zhuhai Station from 1962 to 2020 and maximum daily average river discharge of the year at Makou Station from 1951 to 2005. Based on the integrated model of the validated Delft3D-FLOW and HEC-RAS hydrodynamic models, the river level process of compound floods was simulated for 24 h, and the effects of extreme compound flood events involving storm surge, rainfall and river flood under future scenarios is analyzed. In this study, the Modaomen waterway in Zhuhai City of China is used as the study area. The results show: (1) The Lognormal distribution is selected as the optimal distribution, and the design values of precipitation and discharge in different recurrence periods are calculated based on Lognormal distribution. The precipitation and discharge for the 100-year return period were 450.3 mm and 51000 m3, respectively, which could be used in the compound flood simulation; (2) The application of Delft3D-FLOW model ensures the accurate simulation of the compound flood process. In the different future scenarios of rising sea levels and increasing wind intensity (WI), the effect of multiple disaster-causing factors results to a more serious inundation than that of a single disaster-causing factor, with the increase of maximum storm surge level from 8.09 % to 20.31 %; and (3) Fluvial flooding and storm surge became the major causes of compound flood when the city coastal protection is vulnerable, while in the city with robust coastal protection, precipitation serves as a main disaster-causing factor. Taking the inundation under scenario S1 as an example, when the seawall elevation is 2 m, the composite flooding causes significant inundation in the riparian area (the total inundation area is 15.29 km2), whereas when the seawall elevation is raised to 2.5 m, the inundation area in the riparian area caused by the compound flood decreases significantly (the total inundation area is 0.03 km2). This study is expected to provide scientific references on disaster prevention planning, compound disaster risk management and urban resilience construction along the coastline, as well as have a significant impact on modern economic growth, social stability, and the security in coastal cities.

Understanding spatiotemporal variation of social vulnerabilities from longitudinal hurricane-pandemic data: A multilevel model of the Covid-19 pandemic during hurricane Sally in Florida

An important question in the context of compound disasters is the degree to which geophysical disasters amplify the transmission of infectious diseases during pandemics and how this relationship is influenced by the social vulnerability of affected populations. This article proposes a spatiotemporal modeling approach to understand spatially varying social, demographic and health drivers of vulnerability during pandemics co-occurring with geophysical hazards. A multilevel mixed-effects model is developed to investigate the dynamic association between census tract-level Covid-19 case count trajectories co-occurring with a hurricane and demographic, socioeconomic and health factors. A state-level analysis is conducted to identify the distinct geographical regions in which significant changes are seen in the infection count trends due to the hurricane. A subsequent region-level analysis is performed to describe, at a higher spatial resolution, the impact of social vulnerability on the infection count trajectories at a community level. The method provides an approach to systematically study the effects of compound hazards and distinct patterns of infectious disease spread during hurricanes by quantifying (1) dynamic associations between infection counts and social factors and (2) spatial heterogeneities of these associations between communities. A case study for modeling the spatiotemporal variation of social vulnerability with data from Covid-19 pandemic and Hurricane Sally in Florida is presented to illustrate the application of the approach.

Anticipating older populations’ health risk exacerbated by compound disasters based on mortality caused by heart diseases and strokes

The health of older populations in the Southeastern U.S. receives threats from recurrent tropical cyclones and extreme heat, which may exacerbate the mortality caused by heart diseases and strokes. Such threats can escalate when these extremes form compound disasters, which may be more frequent under climate change. However, a paucity of empirical evidence exists concerning the health threats of compound disasters, and anticipations regarding the health risks of older populations under future compound disaster scenarios are lacking. Focusing on Florida, which has 67 counties and the second-largest proportion of older populations among U.S. states, we calibrate Poisson regression models to explore older populations’ mortality caused by heart diseases and strokes under single and compound disasters. The models are utilized to estimate the mortality across future disaster scenarios, the changing climate, and the growing population. We identify that under multiple hurricanes or heat, current-month hurricanes or heat can affect mortality more heavily than previous-month hurricanes or heat. Under future scenarios, co-occurring hurricanes and extreme heat can exacerbate the mortality more severely than other disaster scenarios. The same types of compound disasters can coincide with an average of 20.5% higher mortality under RCP8.5-SSP5 than under RCP4.5-SSP2. We assess older populations’ future health risks, alerting health agencies to enhance preparedness for future “worst-case” scenarios of compound disasters and proactively adapt to climate change.