Spatiotemporal analysis of regional socio-economic vulnerability change associated with heat risks in Canada

Feeling hot is being hot? Comparing the mapping and the surveying paradigm for urban heat vulnerability in Vienna

With rising global temperatures, cities increasingly need to identify populations or areas that are vulnerable to urban heat waves; however, vulnerability assessments may run into ecological fallacy if data from different scales are misconstrued as equivalent. We assess the heat vulnerability of 1983 residents in Vienna by measuring heat impacts, exposure, sensitivity and adaptive capacity with mirrored indicators in the mapping paradigm (i.e. census tract data referring to the geographic regions where these residents live) and the surveying paradigm (i.e. survey data referring to the residents' individual households). Results obtained in both paradigms diverge substantially: meteorological indicators of hot days and tropical nights are virtually unrelated to self-reported heat strain. Meteorological indicators are explained by mapping indicators (R2 of 15-40 %), but mostly not by surveying indicators. Vice versa, experienced heat stress and subjective heat burden are mostly unassociated with mapping indicators but are partially explained by surveying indicators (R2 of 2-4 %). The results suggest that the two paradigms do not capture the same components of vulnerability; this challenges whether studies conducted in the respective paradigms can complement and cross-validate each other. Policy interventions should first define which heat vulnerability outcome they target and then apply the paradigm that best captures the specific drivers of this outcome.

Micro-spatial flood risk assessment in Nagaon district, Assam (India) using GIS-based multi-criteria decision analysis (MCDA) and analytical hierarchy process (AHP)

Nagaon is one of the highly flood-prone districts of Assam, India that recurrently experiences devastating floods resulting in the loss of lives and property and wreaking havoc on the district's socioeconomic infrastructure. Identification and mapping of spatial patterns of flood hazards, flood vulnerability, and flood risk zones (FRZs) of the district are, therefore, crucial for flood management and mitigation. The present study, therefore, attempts to delineate the FRZs of more than 930 villages in the Nagaon district by integrating the flood hazard and vulnerability layers in the geospatial environment using the multi-criteria decision analysis and analytical hierarchy process techniques. Here, seven flood hazard and vulnerability indicators are considered to derive each layer separately. The results indicate that about 15.14% of the district's total villages are in the very high FRZ, 27.93% in the high, 46.62% in the moderate, and 10.3% in the low FRZ. Further, bivariate correlation analysis is used to evaluate the results with the percentages of the population, cropland, and animals affected by floods at different temporal scales in order to ensure that the revenue circles with a higher percentage of area under high and very high FRZs genuinely have higher percentages of flood-affected cropland, people, and livestock. The significance of this research is evident in its pragmatic findings that could aid the stakeholders in managing and reducing flood risk at micro-spatial scales.

Mapping social vulnerability indicators to understand the health impacts of climate change: a scoping review

The need to assess and measure how social vulnerability influences the health impacts of climate change has resulted in a rapidly growing body of research literature. To date, there has been no overarching, systematic examination of where this evidence is concentrated and what inferences can be made. This scoping review provides an overview of studies published between 2012 and 2022 on social vulnerability to the negative health effects of climate change. Of the 2115 studies identified from four bibliographic databases (Scopus, Web of Science, PubMed, and CAB Direct), 230 that considered indicators of social vulnerability to climate change impacts on health outcomes were selected for review. Frequency and thematic analyses were conducted to establish the scope of the social vulnerability indicators, climate change impacts, and health conditions studied, and the substantive themes and findings of this research. 113 indicators of social vulnerability covering 15 themes were identified, with a small set of indicators receiving most of the research attention, including age, sex, ethnicity, education, income, poverty, unemployment, access to green and blue spaces, access to health services, social isolation, and population density. The results reveal an undertheorisation and few indicators that conceptualise and operationalise social vulnerability beyond individual sociodemographic characteristics by identifying structural and institutional dimensions of vulnerability, and a preponderance of social vulnerability research in high-income countries. This Review highlights the need for future research, data infrastructure, and policy attention to address structural, institutional, and sociopolitical conditions, which will better support climate resilience and adaptation planning.

Too hot! Preventing, recognizing and managing heat injury in children

Climate change-related extreme heat events leading to public health emergencies are increasing in Canada and expected to affect more regions, more frequently and for longer time periods. Children, city dwellers and marginalized populations are amongst the most vulnerable to morbidity and mortality related to extreme heat. Paediatricians can provide caregivers and families with advice to minimize risks as well as advocate for safer city planning and harm mitigation strategies.

The effect modification of extreme temperatures on mental and behavior disorders by environmental factors and individual-level characteristics in Canada

OBJECTIVE

Ambient extreme temperatures have been associated with mental and behavior disorders (MBDs). However, few studies have assesed whether vulnerability factors such as ambient air pollution, pre-existing mental health conditions and residential environmental factors increase susceptibility. This study aims to evaluate the associations between short-term variations in outdoor ambient extreme temperatures and MBD-related emergency department (ED) visits and how these associations are modified by vulnerability factors.

METHODS

We conducted a case-crossover study of 9,958,759 MBD ED visits in Alberta and Ontario, Canada made between March 1st, 2004 and December 31st, 2020. Daily average temperature was assigned to individual cases with ED visits for MBD using gridded data at a 1 km × 1 km spatial resolution. Conditional logistic regression was used to estimate associations between extreme temperatures (i.e., risk of ED visit at the 2.5th percentile temperature for cold and 97.5th percentile temperature for heat for each health region compared to the minimal temperature risk) and MBD ED visits. Age, sex, pre-existing mental health conditions, ambient air pollution (i.e. PM_2.5, NO₂ and O₃) and residential environmental factors (neighborhood deprivation, residential green space exposure and urbanization) were evaluated as potential effect modifiers.

RESULTS

Cumulative exposure to extreme heat over 0-5 days (odds ratio [OR] = 1.145; 95% CI: 1.121-1.171) was associated with ED visits for any MBD. However, cumulative exposure to extreme cold was associated with lower risk of ED visits for any MBD (OR = 0.981; 95% CI: 0.976-0.987). We also found heat to be associated with ED visits for specific MBDs such as substance use disorders, dementia, neurotic disorders, schizophrenia and personality behavior disorder. Individuals with pre-existing mental health conditions, those exposed to higher daily concentrations of NO₂ and O₃ and those residing in neighborhoods with greater material and social deprivation were at higher risk of heat-related MBD ED visits. Increasing tree canopy coverage appeared to mitigate risks of the effect of heat on MBD ED visits.

CONCLUSIONS

Findings provide evidence that the impacts of heat on MBD ED visits may vary across different vulnerability factors.

Urban heat vulnerability: A dynamic assessment using multi-source data in coastal metropolis of Southeast China

Extreme heat caused by global climate change has become a serious threat to the sustainable development of urban areas. Scientific assessment of the impacts of extreme heat on urban areas and in-depth knowledge of the cross-scale mechanisms of heat vulnerability forming in urban systems are expected to support policymakers and stakeholders in developing effective policies to mitigate the economic, social, and health risks. Based on the perspective of the human-environment system, this study constructed a conceptual framework and index system of "exposure-susceptibility-adaptive capacity" for urban heat vulnerability (UHV) and proposed its assessment methods. Taking Xiamen City, a coastal metropolis, as an example, spatial analysis and Geodetector were used to explore the spatial and temporal changes, spatial characteristics, and patterns of UHV under multiple external disturbances from natural to anthropological factors, and to reveal the main factors influencing UHV forming and spatial differentiation. Results showed that the exposure, susceptibility, adaptive capacity, and UHV in Xiamen City had a spatial structure of "coastal-offshore-inland". On the hot day, both the exposure and UHV showed a temporal pattern of "rising and then falling, peaking at 14:00" and a spatial pattern of "monsoonal-like" movement between coast and inland. Coastal zoning with favorable socioeconomic conditions had less magnitude of changes in UHV, where the stability of the urban system was more likely to be maintained. During the hot months, the high UHV areas were mainly distributed in the inland, while coastal areas showed low UHV levels. Further, coastal UHV was mainly dominated by "heat exposure", offshore by "comprehensive factors", and inland in the northern mountainous areas by "lack of adaptive capacity". Multi-scale urban adaptive capacity was confirmed to alter spatial distribution of exposure and reshape the spatial pattern of UHV. This study promotes the application of multi-scale vulnerability framework to disaster impact assessment, enriches the scientific knowledge of the urban system vulnerability, and provides scientific references for local targeted cooling policy development and extreme heat resilience building programs.

Health Risk Assessment and Influencing Factors Analysis of High Temperatures on Negative Emotions

The emotional health of urban residents has been seriously threatened by frequent and normalized heat waves. This study constructed the VI-level assessment standard for emotional health risk using data from satellite images, meteorological sites, questionnaire surveys, and statistical yearbooks to assess the effect of high temperatures on negative emotions in Hangzhou. The results showed that the morphological changes of urban high-temperature areas were aggregated from a cross-shape to a large patch shape, then dispersed into cracked patch shapes. Additionally, the health risk of daytime negative emotions peaked at the VI-level from 1984 to 2020, and the influence level of the typical period risk increased by 1–2 levels compared with the daytime. Additionally, driven by urban spatial structure policies, the risk pattern of emotional health expanded outward from a single center into multiple centers. The emotional health risk level rose and then descended in urban centers, and the innovation industries drove the variation tendency of hot spots. Furthermore, high educational background, employment, and couples living together were critical variables that could alleviate the emotional health risk to the middle-aged and elderly population. This study aimed to optimize the urban spatial structure and alleviate residents’ emotional health hazards for healthy urban planning.

Knowledge Domain and Emerging Trends of Social Vulnerability Research: A Bibliometric Analysis (1991–2021)

Carrying out social vulnerability research has become an important way to understand the sustainable development of resources, the environment, populations, and societies. Clarifying the research context and development trend of social vulnerability is of great significance to the follow-up theoretical research on and practical exploration of sustainable social development. With the help of a CiteSpace knowledge map analysis, this study reveals the research hotspots and their evolution in different periods and puts forward the key problems in and future direction of social vulnerability research in the future. This study found that the number of articles on social vulnerability research showed a steady upward trend and that the research experienced roughly three stages: an embryonic stage, a development stage, and a stable stage. The United States, Brazil, the United Kingdom, and China accounted for the majority of the research, but the intensity of cooperation between them is still weak. Vulnerability assessment and risk assessment in the context of policy and environmental change are hot topics in the current research. In the future, it is necessary to focus on the comprehensive research on the integrated and cross-scale research on social vulnerability, research on its occurrence and evolution, and on the dynamic monitoring as well as optimal regulation of social vulnerability under multiple pressures.

Weighting mechanics and the spatial pattern of composite metrics of heat vulnerability in Atlanta, Georgia, USA

This study constructs two biophysical metrics; one based on Land Surface Temperatures (LST) and an integrated spectral index. The latter is an aggregate of Normalized Difference Vegetation Index (NDVI), Normalized Difference Bareness Index (NDBaI), Normalized Difference Water Index (NDWI), and Normalized Difference Built-up Index (NDBI). The goal is to determine how disparate weighting techniques, data transformation approaches, and spatial visualization pathways influence the computation of composite heat metrics. Using composite images made of aggregated images from late May to Early September within Google Earth Engine, we generated four composites by combining biophysical metrics with SoVI using equal and Eigen-based weightings informed by Principal Component Analysis (PCA). We compared equal interval classification, global and local Moran's as pathways for spatial visualization of hotspots. We utilized several data transformation techniques in a Geographic Information System (GIS), including rescaling, reclassification, zonal statistics, and spatial weighting. Mann Kendall and Sen's Slope detected and quantified monotonic trends in each spectral index. The results show that the LST biophysical metric and its composites indicate increased heat susceptibility over time, with disproportionately exposed core metro counties. The integrated spectral index and its proxies showed reduced vulnerability hence not a good proxy for LST. At the same time, the Mann Kendall and Sen's Slope found persistent increases in NDVI and NDWI and decreases in NDBI and NDBaI. However, opposite trends were evident in core city counties. The LST-based composites and spectral indices-based composites varied in the spatial-temporal distribution of hotspots. Disparate weighting mechanics, data transformation techniques, and visualization alternatives influence the magnitude and spatial-temporal distribution of heat hotspots.

Heat Adaptive Capacity: What Causes the Differences Between Residents of Xiamen Island and Other Areas?

Extreme heat events caused by climate change have serious adverse effects on residents' health in many coastal metropolises in southeast China. Adaptive capacity (AC) is crucial to reduce heat vulnerability in the human-environment system. However, it is unclear whether changes in individual characteristics and socioeconomic conditions likely amplify or attenuate the impacts of residents' heat adaptive capacity (HAC) changes. Moreover, which public policies can be implemented by the authorities to improve the HAC of vulnerable groups remains unknown. We conducted a questionnaire survey of 630 residents of Xiamen, a typical coastal metropolis, in 2018. The effects of individual and household characteristics, and government actions on the residents' HAC were examined by using ordinal logistic regression analysis. Results show that the majority (48.10%) of Xiamen residents had a "medium" HAC level, followed by a "high" level (37.14%). On Xiamen Island, residents who settled locally for one-three years and spent less than one hour outdoors might report weaker HAC, and their HAC would not improve with increased air conditioning units in household. In other areas of Xiamen, residents with more rooms in their households, no educational experience, and building areas <50 m2 might report better HAC. Further, vulnerable groups, such as local residents and outdoor workers on Xiamen Island, people lacking educational experience and renters in other areas of Xiamen, showed better AC to hot weather than those in previous studies. Low-income groups should be given more attention by local governments and community groups as monthly household income played a positive role in improving Xiamen residents' HAC. Rational green spaces planning and cooling services, such as street sprinkling operations, provided by municipal departments can effectively bring benefits to Xiamen residents. Identification of basic conditions of AC has significant implications for practical promoting targeted measures or policies to reduce health damages and livelihood losses of urban residents during extreme heat events.

Spatiotemporal Evolution and Trend Prediction of Tourism Economic Vulnerability in China’s Major Tourist Cities

The evaluation and trend prediction of tourism economic vulnerability (TEV) in major tourist cities are necessary for formulating tourism economic strategies scientifically and promoting the sustainable development of regional tourism. In this study, 58 major tourist cities in China were taken as the research object, and an evaluation index system of TEV was constructed from two aspects of sensitivity and adaptive capacity. On the basis of the entropy weight method, TOPSIS model, obstacle diagnosis model, and BP neural network model, this study analyzed the spatiotemporal patterns, obstacle factors, and future trends of TEV in major tourist cities in China from 2004 to 2019. The results show three key findings: (1) In terms of spatiotemporal patterns, the TEV index of most of China’s tourist cities has been on the rise from 2004 to 2019. Cities throughout the coast of China’s Yangtze River Delta and the Pearl River Delta urban agglomeration show high vulnerability, whereas low vulnerability has a scattered distribution in China’s northeast, central, and western regions. (2) The proportion of international tourists out of total tourists, tourism output density, urban industrial sulfur dioxide emissions per unit area, urban industrial smoke and dust emission per unit area, and discharge of urban industrial wastewater per unit area are the five major obstacles affecting the vulnerability degree of the tourism economy. (3) According to the prediction results of TEV from 2021 to 2030, although the TEV of many tourist cities in China is increasing year by year, cities with low TEV levels occupy the dominant position. Research results can provide reference for tourist cities to prevent tourism crises from occurring and to reasonably improve the resilience of the tourism economic system.

Assessment of the Socioeconomic Vulnerability to Seismic Hazards in the National Capital Region of India Using Factor Analysis

The seismicity of the National Capital Region (NCR) of India increased significantly over the last decade. Communities in the NCR face significant exposure to damaging seismic events, and the seismic risk arises not only from the region’s proximity to the Himalayan mountains, but also from the socioeconomic vulnerabilities in its communities and the current capacities of different localities to respond to and recover from any unforeseen large seismic event. GIS-based spatial distribution of exposure to seismic hazards (SH) can help decision-makers and authorities identify locations with populations at high seismic risk, and to prepare risk-mitigation plans. Socioeconomic vulnerability (SeV) studies serve as a basis for quantifying qualitative measures. For this purpose, in the present study, the hazard of place (HoP) model is used to assess SeV to seismic hazards in the NCR. Social indicators like age, gender, literacy, family size, built environment, etc., comprising a total of 36 variables, are used to assess a socioeconomic vulnerability index (SeVI) based on factor and principal component (PCA) analyses. Based on PCA, 20 variables were retained and grouped into four factors: socioeconomic status, employment status, building typology, and family size. Ground-motion parameters, estimated from probabilistic seismic hazard assessment, are integrated with the socioeconomic vulnerability index to quantify exposure to seismic hazards. The spatial distributions in the produced socioeconomic-vulnerability index and seismic–hazard–exposure maps highlight the critical areas. The results reveal that areas of low literacy, high unemployment, and poor housing condition show moderate-to-high vulnerability. The south-eastern region of the study area is assessed as a high-risk zone by an integrated SeV–SH risk matrix. The results of this study emphasize the importance of the socioeconomic vulnerability component of disaster risk–reduction programs, from a holistic perspective, for the areas with high seismicity.

A human-centred assessment framework to prioritise heat mitigation efforts for active travel at city scale

Hot weather not only impacts upon human physical comfort and health, but also impacts the way that people access and experience active travel options such as walking and cycling. By evaluating the street thermal environment of a city alongside an assessment of those communities that are the most vulnerable to the effects of heat, we can prioritise areas in which heat mitigation interventions are most needed. In this paper, we propose a new approach for policy makers to determine where to delegate limited resources for heat mitigation with most effective outcomes for the communities. We use eye-level street panorama images and community profiles to provide a bottom-up, human-centred perspective of the city scale assessment, highlighting the situation of urban tree shade provision throughout the streets in comparison with environmental and social-economic status. The approach leverages multiple sources of spatial data including satellite thermal images, Google street view (GSV) images, land use and demographic census data. A deep learning model was developed to automate the classification of streetscape types and percentages at the street- and eye-view level. The methodology is metrics based and scalable which provides a data driven assessment of heat-related vulnerability. The findings of this study first contribute to sustainable development by developing a method to identify geographical areas or neighbourhoods that require heat mitigation; and enforce policies improving tree shade on routes, as a heat adaptation strategy, which will lead to increasing active travel and produce significant health benefits for residents. The approach can be also used to guide post COVID-19 city planning and design.

Human health outcomes at the neighbourhood scale implications: Elderly's heat-related cardiorespiratory mortality and its influencing factors

The excessively warm weather, especially in cities, can lead to several adverse impacts, including heat-related mortality, becoming an increasingly important public health issue. Previous studies on heat-related mortality have assessed risk factors at the municipal scale, missing the intra-urban variability in heat risk and vulnerability. The knowledge of the spatial intra-variability can help to design spatially targeted measures to better protect citizens' health. Through hot spot analysis, we identified the neighbourhood-scale spatial pattern of heat-related cardiorespiratory mortality in the elderly, during the yearly warmest five months of a three years period. Potential associations between spatial variability in heat-related mortality and several independent factors in each neighbourhood were investigated and their predictions. Two approaches were adopted: one is eminently statistical, using Generalized Linear Models (GLM) and another using Geographically Weighted Regression (GWR). This new recent regression technique is increasing in international attention on spatial modelling. The spatial model explains about 60% of the spatial variations in elderly's heat-related cardiorespiratory mortality. The two-analyses produced an overlapping set of predictor variables, with emphasis on the elderly, vegetation cover and employment. The results also show that the areas where heat-related mortality is high, are also the areas where the number of deaths is higher than expected. These neighbourhoods should be considered as the most vulnerable to heat-related mortality. We concluded that studying human health outcomes at neighbourhood-scale is relevant for public health heat-related plans. Essential suggestions are provided to decision-making support and city planners designing strategies to reduce heat-related mortality.

Climate change and child health: a scoping review and an expanded conceptual framework

Climate change can have detrimental effects on child health and wellbeing. Despite the imperative for a fuller understanding of how climate change affects child health and wellbeing, a systematic approach and focus solely on children (aged <18 years) has been lacking. In this Scoping Review, we did a literature search on the impacts of climate change on child health from January, 2000, to June, 2019. The included studies explicitly linked an alteration of an exposure to a risk factor for child health to climate change or climate variability. In total, 2970 original articles, reviews, and other documents were identified, of which 371 were analysed. Employing an expanded framework, our analysis showed that the effects of climate change on child health act through direct and indirect pathways, with implications for determinants of child health as well as morbidity and mortality from a range of diseases. This understanding can be further enhanced by using a broader range of research methods, studying overlooked populations and geographical regions, investigating the costs and benefits of mitigation and adaptation for child health, and considering the position of climate change and child health within the UN Sustainable Development Goals. Present and future generations of children bear and will continue to bear an unacceptably high disease burden from climate change.

Health Risks Due To Climate Change: Inequity In Causes And Consequences

Climate change has altered global to local weather patterns and increased sea levels, and it will continue to do so. Average temperatures, precipitation amounts, and other variables such as humidity levels are all rising. In addition, weather variability is increasing, causing, for example, a greater number of heat waves, many of which are more intense and last longer, and more floods and droughts. These changes are collectively increasing the number of injuries, illnesses, and deaths from a wide range of climate-sensitive health outcomes. Future health risks will be determined not just by the hazards created by a changing climate but also by the sensitivity of individuals and communities exposed to these hazards and the capacity of health systems to prepare for and effectively manage the attendant risks. These risks include deaths and injuries from extreme events (for example, heat waves, storms, and floods), infectious diseases (including food-, water-, and vectorborne illnesses), and food and water insecurity. These risks are unevenly distributed and both create new inequities and exacerbate those that already exist. Most of these risks are projected to increase with each additional unit of warming. Using an equity lens to move beyond incremental to transformational resilience would reduce vulnerability and improve sustainability for all, but substantial additional funding is required for proactive and effective actions by the health system.

Intraurban social risk and mortality patterns during extreme heat events: A case study of Moscow, 2010-2017

There is currently an increase in the number of heat waves occurring worldwide. Moscow experienced the effects of an extreme heat wave in 2010, which resulted in more than 10,000 extra deaths and significant economic damage. This study conducted a comprehensive assessment of the social risks existing during the occurrence of heat waves and allowed us to identify the spatial heterogeneity of the city in terms of thermal risk and the consequences for public health. Using a detailed simulation of the meteorological regime based on the COSMO-CLM regional climate model and the physiologically equivalent temperature (PET), a spatial assessment of thermal stress in the summer of 2010 was carried out. Based on statistical data, the components of social risk (vulnerabilities and adaptive capacity of the population) were calculated and mapped. We also performed an analysis of their changes in 2010-2017. A significant differentiation of the territory of Moscow has been revealed in terms of the thermal stress and vulnerability of the population to heat waves. The spatial pattern of thermal stress agrees quite well with the excess deaths observed during the period from July to August 2010. The identified negative trend of increasing vulnerability of the population has grown in most districts of Moscow. The adaptive capacity has been reduced in most of Moscow. The growth of adaptive capacity mainly affects the most prosperous areas of the city.

Mapping Heat-Related Risks in Northern Jiangxi Province of China Based on Two Spatial Assessment Frameworks Approaches

Heat-health risk is a growing concern in many regions of China due to the more frequent occurrence of extremely hot weather. Spatial indexes based on various heat assessment frameworks can be used for the assessment of heat risks. In this study, we adopted two approaches—Crichton’s risk triangle and heat vulnerability index (HVI) to identify heat-health risks in the Northern Jiangxi Province of China, by using remote sensing and socio-economic data. The Geographical Information System (GIS) overlay and principal component analysis (PCA) were separately used in two frameworks to integrate parameters. The results show that the most densely populated community in the suburbs, instead of city centers, are exposed to the highest heat risk. A comparison of two heat assessment mapping indicates that the distribution of HVI highlights the vulnerability differences between census tracts. In contrast, the heat risk index of Crichton’s risk triangle has a prominent representation for regions with high risks. The stepwise multiple linear regression zero-order correlation coefficient between HVI and outdoor workers is 0.715, highlighting the vulnerability of this particular group. Spearman’s rho nonparametric correlation and the mean test reveals that heat risk index is strongly correlated with HVI in most of the main urban regions in the study area, with a significantly lower value than the latter. The analysis of variance shows that the distribution of HVI exhibits greater variety across urban regions than that of heat risk index. Our research provides new insight into heat risk assessment for further study of heat health risk in developing countries.

Impact of climate change on disaster events in metropolitan cities -trend of disasters reported by Taiwan national medical response and preparedness system

BACKGROUND

Taiwan is geographically located in a zone that is vulnerable to earthquakes, typhoons, floods, and landslide hazards and has experienced various disasters. Six Regional Emergency Medical Operation Centers (REMOCs) are integrated and administered by the Ministry of Health and Welfare (MOHW) to be responsible for emergency situations during disastrous events, such as the emission of chemical toxicants, traffic accidents, industrial materials containment, and typhoons.

OBJECTIVE

To analyze events reported by the six REMOCs during the 2014 to 2018 for the government policy reference.

METHODS

Data were collected from injured and death toll reports provided by local designated hospitals in the emergency medical reporting system. Disaster events were categorized into three categories: natural disaster (NDs), disasters associated with technology (DTs), and disasters associated with security/violence/others (DSVOs). The three categories were further subdivided into sub-categories. Variables considered for trend analyses included the number of wounded and deaths, event characteristics, date/time, and triage. The frequency of disaster events among the six REMOCs was compared using the chi-square test. We used the global information system (GIS) to describe the distribution of events in Taiwan metropolitan cities. The α-level was set at 0.05.

RESULTS

Of 580 events during the study period, the distribution of disaster characteristics in the jurisdictions of the six REMOCs were different. The majority of disaster events were DTs (64.5%), followed by NDs (24.5%) and DSVOs (11.0%). Events for the three disaster categories in the six REMOCs were different (χ²-test, p < 0.001). Furthermore, for the Taipei branch (Northern Taiwan), other NDs, especially heatwaves and cold spells, were most reported in New Taipei City (92.2%) and showed an increasing annual trend; for the Kaohsiung branch (Southern Taiwan), DT events were the most reported, especially in Kaohsiung City; and for the Taichung branch (Central Taiwan), DSVOs were the most reported, especially in Taichung City.

CONCLUSION

Our data revealed that extreme weather precautions reported in the Taipei branch were increasing. Disaster characteristics were different in each metropolitan city. Upgrading the ability to respond to natural disasters is ineluctable.

The Role of Individual and Small-Area Social and Environmental Factors on Heat Vulnerability to Mortality Within and Outside of the Home in Boston, MA

Climate change is resulting in heatwaves that are more frequent, severe, and longer lasting, which is projected to double-to-triple the heat-related mortality in Boston, MA if adequate climate change mitigation and adaptation strategies are not implemented. A case-only analysis was used to examine subject and small-area neighborhood characteristics that modified the association between hot days and mortality. Deaths of Boston, Massachusetts residents that occurred from 2000–2015 were analyzed in relation to the daily temperature and heat index during the warm season as part of the case-only analysis. The modification by small-area (census tract, CT) social, and environmental (natural and built) factors was assessed. At-home mortality on hot days was driven by both social and environmental factors, differentially across the City of Boston census tracts, with a greater proportion of low-to-no income individuals or those with limited English proficiency being more highly represented among those who died during the study period; but small-area built environment features, like street trees and enhanced energy efficiency, were able to reduce the relative odds of death within and outside the home. At temperatures below current local thresholds used for heat warnings and advisories, there was increased relative odds of death from substance abuse and assault-related altercations. Geographic weighted regression analyses were used to examine these relationships spatially within a subset of at-home deaths with high-resolution temperature and humidity data. This revealed spatially heterogeneous associations between at-home mortality and social and environmental vulnerability factors.

Spatially Explicit Assessment of Social Vulnerability in Coastal China

Social vulnerability assessment has been recognized as a reliable and effective measure for informing coastal hazard management. Although significant advances have been made in the study of social vulnerability for over two decades, China’s social vulnerability profiles are mainly based on administrative unit. Consequently, no detailed distribution is provided, and the capability to diagnose human risks is hindered. In this study, we established a social vulnerability index (SoVI) in 2000 and 2010 at a spatial resolution of 250 m for China’s coastal zone by combining the potential exposure index (PEI) and social resilience index (SRI). The PEI with a 250 m resolution was obtained by fitting the census data and multisource remote sensing data in random forest model. The county-level SRI was evaluated through principal component analysis based on 33 socioeconomic variables. For identifying the spatiotemporal change, we used global and local Moran’s I to map clusters of SoVI and its percent change in the decade. The results suggest the following: (1) Counties in the Yangtze River Delta, Pearl River Delta, and eastern Guangzhou, except several small hot spots, exhibited the most vulnerability, especially in urban areas, whereas those in Hainan and southern Liaoning presented the least vulnerability. (2) Notable increases were emphasized in Tianjin, Yangtze River Delta, and Pearl River Delta. The spatiotemporal variation and heterogeneity in social vulnerability obtained through this analysis will provide a scientific basis to decision-makers to focus risk mitigation effort.

Assessing the Intensity of the Population Affected by a Complex Natural Disaster Using Social Media Data

Complex natural disasters often cause people to suffer hardships, and they can cause a large number of casualties. A population that has been affected by a natural disaster is at high risk and desperately in need of help. Even with the timely assessment and knowledge of the degree that natural disasters affect populations, challenges arise during emergency response in the aftermath of a natural disaster. This paper proposes an approach to assessing the near-real-time intensity of the affected population using social media data. Because of its fatal impact on the Philippines, Typhoon Haiyan was selected as a case study. The results show that the normalized affected population index (NAPI) has a significant ability to indicate the affected population intensity. With the geographic information of disasters, more accurate and relevant disaster relief information can be extracted from social media data. The method proposed in this paper will benefit disaster relief operations and decision-making, which can be executed in a timely manner.

A Raster-Based Subdividing Indicator to Map Urban Heat Vulnerability: A Case Study in Sydney, Australia

Assessing and mapping urban heat vulnerability has developed significantly over the past decade. Many studies have mapped urban heat vulnerability with a census unit-based general indicator (CGI). However, this kind of indicator has many problems, such as inaccurate assessment results and lacking comparability among different studies. This paper seeks to address this research gap and proposes a raster-based subdividing indicator to map urban heat vulnerability. We created a raster-based subdividing indicator (RSI) to map urban heat vulnerability from 3 aspects: exposure, sensitivity and adaptive capacity. We applied and compared it with a raster-based general indicator (RGI) and a census unit-based general indicator (CGI) in Sydney, Australia. Spatial statistics and analysis were used to investigate the performance among those three indicators. The results indicate that: (1) compared with the RSI framework, 67.54% of very high heat vulnerability pixels were ignored in the RGI framework; and up to 83.63% of very high heat vulnerability pixels were ignored in the CGI framework; (2) Compared with the previous CGI framework, a RSI framework has many advantages. These include more accurate results, more flexible model structure, and higher comparability among different studies. This study recommends using a RSI framework to map urban heat vulnerability in the future.