Quantifying social vulnerability for flood disasters of insurance company

Social vulnerability assessments are largely ignored when compared with biophysical vulnerability assessments. This is mainly due to the fact that there are more difficulties in quantifying them. Aiming at several pitfalls still existing in the Hoovering approach which is widely accepted, a suitable modified model is provided. In this modified model, the integrated vulnerability is made an analogy to the elasticity coefficient of a spring, and an objective evaluation criterion is established. With the evaluation criterion, the assessment indicators of social vulnerability are filtered and their weight assignments are accomplished. There is an application in the city of Changsha where floods occur often. With the relative data from the PICC Hunan Province Branch, a generalized regression neural network model is established in Matlab 7.0 and used to evaluate a company's flood social vulnerability index (SoVI). The results show that the average flood social vulnerability in Yuhua district is the highest, while Yuelu district is the lowest. It is good for disaster risk management and decision-making of insurance companies.

Measuring Social Vulnerability to Natural Hazards in Beijing-Tianjin-Hebei Region,China

Social vulnerability in this study represents the differences between the capacity to cope with natural hazards and disaster losses suffered within and between places.The assessment of social vulnerability has been recognized as a critical step in understanding natural hazard risks and enhancing effective response capabilities.This article presents an initial study of the social vulnerability of the Beijing-Tianjin-Hebei(B-T-H) Region in China.The goal is to replicate and test the applicability of the United States Social Vulnerability Index(So VI) method in a Chinese cultural context.Thirty-nine variables adapted from the So VI were collected in relation to two aspects:socioeconomic vulnerability and built environment vulnerability.Using factor analysis,seven factors were extracted from the variable set:the structure of social development,the level of economic and government financial strength,social justice and poverty,family structure,the intensity of space development,the status of residential housing and transportation,and building structure.Factor scores were summed to get the final So VI scores and the most and least vulnerable units were identified and mapped.The highest social vulnerability is concentrated in the northwest of the study area.The least socially vulnerable areas are mainly distributed in the Beijing,Tianjin and Shijiazhuang core urban peripheral and central city areas of the prefecture-level cities.The results show that this method is a useful tool for revealing places that have a high level of vulnerability,in other words,areas which are more likely to face significant challenges in coping with a large-scale event.These findings could provide a scientific basis for policy making and the implementation of disaster prevention and mitigation in China.

A Multi-Site Case Study on Social Vulnerability to Climate Change of Select Rain-fed Farming Communities in the Philippines

This study examines social vulnerability by exploring the socio-economic factors, infrastructures, and social networks that can determine how prone and how prepared the rain-fed farming communities are to the adverse impacts of climate change. Increased variability in climatic conditions due to climate change seriously affects the productivity of rain-fed farms. The rain-fed farming communities in the Philippines are located in poor and environmentally fragile rural areas. Their vulnerability is greatly affected by restricted entitlement and access to social and economic capitals. This study is framed on qualitative approach to provide a rich and in-depth understanding on the elements of vulnerability based on the capacities and the practical affairs of life in rain-fed communities. The three subject communities from two agricultural provinces are examined to understand how the context and interactions of people can explicate sociological themes on the social dimension of climate change. The usefulness of multi-site study in probing the unique ways of how people understand and respond to certain environmental issue is part of reflections about the methodology.

Social Vulnerability to Natural Hazards in Brazil

Although social vulnerability has recently gained attention in academic studies, Brazil lacks frameworks and indicators to assess it for the entire country.Social vulnerability highlights differences in the human capacity to prepare for, respond to, and recover from disasters. It varies over space and time, and among and between social groups, largely due to differences in socioeconomic and demographic characteristics. This article provides a social vulnerability index(SoVI~) replication study for Brazil and shows how SoVI~concepts and indicators were adapted to the country. SoVI~Brazil follows the place-based framework adopted in the Social Vulnerability Index initially developed for the United States. Using a principal component analysis(PCA), 45city-level indicators were reduced to 10 factors that explain about 67 % of the variance in the data. Clearly identified spatial patterns showed a concentration of the most socially vulnerable cities in the North and Northeast regions of Brazil, as well as the social vulnerability of metropolitan areas and state capitals in the South and Southeast regions.The least vulnerable cities are mainly concentrated in the inland regions of the Southeast. Although different factors contribute to the social vulnerability in each city, the overall results confirm the social and economic disparities among Brazilian’s regions and reflect a differential vulnerability to natural hazards at local to regional scales.

An Index-Based Approach to Assess Social Vulnerability for Hamburg, Germany

In this study,we set out to develop a new social vulnerability index(SVI).In doing so,we suggest some conceptual improvements that can be made to existing methodical approaches to assessing social vulnerability.To make the entanglement of socio-spatial inequalities visible,we are conducting a small-scale study on heterogeneous urban development in the city of Hamburg,Germany.This kind of high-resolution analysis was not previously available,but is increasingly requested by political decision makers.We can thus show hot spots of social vulnerability(SV)in Hamburg,considering the effects of social welfare,education,and age.In doing so,we defined SV as a contextual concept that follows the recent shift in discourse in line with the Intergovernmental Panel on Climate Change’s(IPCC)concepts of risk and vulnerability.Our SVI consists of two subcomponents:sensitivity and coping capacity.Populated areas of Hamburg were identified using satellite information and merged with the social data units of the city.Areas with high SVI are distributed over the entire city,notably in the district of Harburg and the Reiherstieg quarter in Wilhelmsburg near the Elbe,as well as in the densely populated inner city areas of Eimsbüttel and St.Pauli.As a map at a detailed scale,our SVI can be a useful tool to identify areas where the population is most vulnerable to climate-related hazards.We conclude that an enhanced understanding of urban social vulnerability is a prerequisite for urban risk management and urban resilience planning.

Place-and Age-Responsive Disaster Risk Reduction for Hong Kong:Collaborative Place Audit and Social Vulnerability Index for Elders

This study reformulates the concept and contents of disaster risk reduction(DRR) in Hong Kong through an explorative study on collaborative place audit(CPA) and social vulnerability index(SVI) for elders.We believe that DRR should be place-and age-responsive.Accordingly,DRR needs to go beyond technical concerns and address vulnerability and risk encountered in the built environment where an individual is located.A place-centered DRR begins with an assessment of person–environment relations from an interdependent perspective.Community becomes a significant scale at which to address vulnerability and risks across a range of environmental,socioeconomic,and institutional factors.A CPA is a ground-level assessment tool that identifies vulnerability and risk in the built and social environment.The audit encourages collaboration in problem solving that uses social capital to effect decisionmaking change in hierarchies and policy networks.Ageresponsive DRR facilitates distinguishing living-alone elders from the general population.This perspective addresses varying degrees of vulnerability due to social and communicational isolation,poverty,disability,being sent to hospital and/or receiving institutional care,as well as lack of access to primary care.Accordingly,SVI,based oncompound indicators,is developed to assess the differentiation of vulnerability across the territory with particular reference to the elders.These two approaches,namely,CPA and SVI,build community capacity to develop a resilient city,as well as to provide evidence-based recommendations that improve government-led disaster preparedness and contingency plans.

Spatiotemporal Pattern of Social Vulnerability in Italy

Evaluation of social vulnerability(SV) against natural hazards remains a big challenge for disaster risk reduction. Spatiotemporal analysis of SV is important for successful implementation of prevision and prevention measures for risk mitigation. This study examined the spatiotemporal pattern of SV in Italy, and also analyzed socioeconomic factors that may influence how the Italian population reacts to catastrophic natural events. We identified 16 indicators that quantify SV and collected data for the census years 1991, 2001, and 2011. We created a social vulnerability index(SVI) for each year by using principal component analysis outputs and an additive method.Exploratory spatial data analysis, including global and local autocorrelations, was used to understand the spatial patterns of social vulnerability across the country. Specifically, univariate local Moran's index was performed for the SVI of each of the three most recent census years in order to detect changes in spatial clustering during the whole study period. The original contribution of this Italy case study was to use a bivariate spatial correlation to describe the spatiotemporal correlation between the threes annual SV indices. The temporal analysis shows that the percentage of municipalities with medium social vulnerability in Italy increased from 1991 to 2011 and those with very high social vulnerability decreased. Spatial analysis provided evidence of clusters that maintained significant high values of social vulnerability throughout the studyperiods. The SVI of many areas in the center and the south of the peninsula remained stable, and the people living there have continued to be potentially vulnerable to natural hazards.

Leveraging Hazard,Exposure,and Social Vulnerability Data to Assess Flood Risk to Indigenous Communities in Canada

This study integrates novel data on 100-year flood hazard extents,exposure of residential properties,and place-based social vulnerability to comprehensively assess and compare flood risk between Indigenous communities living on 985 reserve lands and other Canadian communities across 3701 census subdivisions.National-scale exposure of residential properties to fluvial,pluvial,and coastal flooding was estimated at the 100-year return period.A social vulnerability index(SVI)was developed and included 49 variables from the national census that represent demographic,social,economic,cultural,and infrastructure/community indicators of vulnerability.Geographic information system-based bivariate choropleth mapping of the composite SVI scores and of flood exposure of residential properties and population was completed to assess the spatial variation of flood risk.We found that about 81%of the 985 Indigenous land reserves had some flood exposure that impacted either population or residential properties.Our analysis indicates that residential property-level flood exposure is similar between non-Indigenous and Indigenous communities,but socioeconomic vulnerability is higher on reserve lands,which confirms that the overall risk of Indigenous communities is higher.Findings suggest the need for more local verification of flood risk in Indigenous communities to address uncertainty in national scale analysis.

An indicator-based approach to assess village-level social and biophysical vulnerability of agriculture communities in Uttarakhand,India

With the growing recognition to myriad forms of current and future threats in the mountain agriculture systems,there is a pressing need to holistically understand the vulnerability of mountain agriculture communities.The study aims to assess the biophysical and social vulnerability of agriculture communities using an indicator-based approach for the state of Uttarakhand,India.A total of 14 indicators were used to capture biophysical vulnerability and 22 for social vulnerability profiles of15285 villages.Vulnerability analysis was done at village level with weights assigned to each indicator using Analytical Hierarchical Process(AHP).The results of the study highlight the presence of very high biophysical vulnerability(0.82 ± 0.10) and high social vulnerability(0.65 ± 0.15) within the state.Based on the results,it was found that incidences of high biophysical vulnerability coincide with presence of intensified agriculture land and absence of dense forest.Higher social vulnerability scores were found in villages with an absence of local institutions(like Self Helping Groups(SHGs)),negligible infrastructure facilities and higher occupational dependence on agriculture.A contrast was observed in the vulnerability scores of villages present in the three different altitudinal zones in the study area,indicating respective vulnerability generating conditions existing in these three zones.Biophysical vulnerability was recorded to be highest in the villages falling in the lower zone and lowest in the upper zone villages;whereas,social vulnerability was found to be highest in the middle zone villages and lowest in lower zone villages.Our study aids policy makers in identifying areas for intervention to expedite agriculture adaptation planning in the state.Additionally,the adaptation programmes in the region need to be more context-specific to accommodate the differential altitudinal vulnerability profiles.

Spatial Industrial Accident Exposure and Social Vulnerability Assessment of Hazardous Material Sites,Chemical Parks,and Nuclear Power Plants in Germany

Industrial accidents have shown that many people can be affected,such as in Seveso,Italy,in 1976.Industrial accidents in nuclear power plants have also led to fatalities and evacuations.To better guide preparedness against and mitigation of industrial accidents,an assessment is necessary to evaluate hazard exposure and the type of potentially vulnerable social groups that need to be taken into account.This study conducted a spatial assessment of three types of industrial facilities in Germany:facilities registered under the Seveso Directive,chemical parks,and nuclear power plants.The method consisted of a spatial assessment using a Geographic Information System of exposure around hazardous sites registered under the S eveso Directive in Germany and of census data to analyze social vulnerability.Hazards analyzed included industrial accidents and earthquakes.The results revealed that most industrial sites are in urban areas and that population density,the numbers of foreigners,and smaller housing unit sizes are higher in close proximity to these sites.The buffer zones analyzed in circles between 1 and 40 km show a decreasing vulnerability with more distance.This can guide emergency management planners and other stakeholders to better prepare for major accidents and better devise disaster risk reduction strategies specifically for different social groups.

A Novel Approach to Measuring Spatiotemporal Changes in Social Vulnerability at the Local Level in Portugal

Social vulnerability,as one of the risk components,partially explains the magnitude of the impacts observed after a disaster.In this study,a spatiotemporally comparable assessment of social vulnerability and its drivers was conducted in Portugal,at the civil parish level,for three census frames.The first challenging step consisted of the selection of meaningful and consistent variables over time.Data were normalized using the Adjusted Mazziotta-Pareto Index(AMPI)to obtain comparable adimensional-normalized values.A joint principal component analysis(PCA)was applied,resulting in a robust set of variables,interpretable from the point of view of their self-grouping around vulnerability drivers.A separate PCA for each census was also conducted,which proved to be useful in analyzing changes in the composition and type of drivers,although only the joint PCA allows the monitoring of spatiotemporal changes in social vulnerability scores and drivers from 1991 to 2011.A general improvement in social vulnerability was observed for Portugal.The two main drivers are the economic condition(PC1),and aging and depopulation(PC2).The remaining drivers highlighted are uprooting and internal mobility,and daily commuting.Census data proved their value in the territorial,social,and demographic characterization of the country,to support medium-and long-term disaster risk reduction measures.

Social Vulnerability Factors and Reported Post-Disaster Needs in the Aftermath of Hurricane Florence

This research examines the relationship between social vulnerability factors and reported needs following Hurricane Florence.Weighted least squares regression models were used to identify predictor variables for valid registrations that reported needs pertaining to emergencies,food,and shelter.Data consisted of zip codes in North Carolina and South Carolina that received individual assistance for Hurricane Florence(N=406).The results suggest that when controlling for event-specific factors and flood mitigation factors,the proportions of the population that is female,the population over 65,the population aged5 and under,the population older than 5 years not speaking English,and the minority population were all predictors of the per capita reported emergency needs.When controlling for the same variables,the proportions of the population over the age of 25 with a Bachelor’s degree,the female population,the population aged 5 and under,the population above 5 years old that does not speak English,and the minority population were all predictors of the per capita reported food needs.With the same variables controlled for,three variables—the proportions of the population over65,the population aged 5 and under,and the non-Englishspeaking population above 5 years of age—were all predictors of the per capita reported shelter needs.The results suggest that more attention should be given to these vulnerable populations in the pre-disaster planning process.

Disaster Risk Reduction (DRR) Education from Social Disciplinary Theoretical Perspectives

Disaster is a social phenomenon. The occurrence and impacts of disasters including the education sector can be studied through a social problem lens. This paper draws meaning and understanding of DRR education using the sociological disciplinary framework in a detailed qualitative case study of three schools as they responded to the devastating Gorakha earthquake in 2015 and other disasters in Nepal. This paper considers the three sub-disciplines of sociology: the sociology of disaster, the sociology of education and the sociology of education governance in a development context. These sub-disciplines are nested together to analyse social, political and historical factors and their relationships which are helpful to identify risks and vulnerabilities in the education sector in Nepal. These are the major areas to explore the disaster context and needs of context-specific education acts (hereafter DRR education) to minimise the potential risks of disasters. The article concludes that the social disciplinary framework is significantly useful to analyse DRR education provisions and implications of education governance to mobilise school in disaster preparedness, response and recovery.

Estimating long-term K-12 student homelessness after a catastrophic flood disaster

Despite efforts to end homelessness in the United States,student homelessness is gradually growing over the past decade.Homelessness creates physical and psychological disadvantages for students and often disrupts school access.Research suggests that students who experience prolonged dislocation and school disruption after a dis-aster are primarily from low-income households and under-resourced areas.This study develops a framework to predict post-disaster trajectories for kindergarten through high school(K-12)students faced with a major disaster;the framework includes an estimation on the households with children who recover and those who experience long-term homelessness.Using the National Center for Education Statistics school attendance boundaries,resi-dential housing inventory,and U.S.Census data,the framework first identifies students within school boundaries and links schools to students to housing.The framework then estimates dislocation induced by the disaster sce-nario and tracks the stage of post-disaster housing for each dislocated student.The recovery of dislocated students is predicted using a multi-state Markov chain model,which captures the sequences that households transition through the four stages of post-disaster housing(i.e.,emergency shelter,temporary shelter,temporary housing,and permanent housing)based on the social vulnerability of the household.Finally,the framework predicts the number of students experiencing long-term homelessness and maps the students back to their pre-disaster school.The proposed framework is exemplified for the case of Hurricane Matthew-induced flooding in Lumberton,North Carolina.Findings highlight the disparate outcomes households with children face after major disasters and can be used to aid decision-making to reduce future disaster impacts on students.

Extreme Weather Disruptions and Emergency Preparedness Among Older Adults in Ohio: An Eight-County Assessment

The disproportionate risks and impacts of climate change and extreme weather on older adults are increasingly evident. While especially true in disaster-prone areas, human-caused climate change introduces an element of uncertainty even in previously identified “safe” regions such as the Midwestern United States. Using a cumulative disadvantage and vulnerability-informed framework and descriptive statistics from multiple data sources, this article provides an overview of climate impacts, vulnerabilities, and county-level characteristics, focusing on older adults living in Central Ohio. A comparative multiple-case study methodology was used to triangulate regionally representative primary and secondary data sources to examine state and county-level measures of vulnerability, emergency preparedness, and disruptions caused by extreme weather among older adults across eight counties in Central Ohio. Seventy-eight percent of older adults in the sample reported being prepared for emergencies per Federal Emergency Management Agency guidelines. Older adults in Union County reported the highest rates of preparedness, while those in Fayette County reported the lowest. County-level rates of disruption of life activities by extreme weather ranged widely. Among the most rural in the region, Fayette County emerged as uniquely disadvantaged, with the lowest median income, the most vulnerable across multiple social vulnerability dimensions, and the most reported disruptions to life activities from extreme weather. County profiles offer a snapshot of existing vulnerabilities, socioeconomic conditions, special needs, preparedness, and current disruptions among older adults in the region and can inform resource mobilization across community and policy contexts.

Evaluating COVID-19’s impacts on Puerto Rican’s travel behaviors

The COVID-19 pandemic has completely disrupted and possibly permanently changed the way humans travel.In Puerto Rico,major travel restrictions to the island have persisted at different levels since March 2020,which heavily influenced residents’travel behaviors.However,it remains unclear about how big the impact is and how inequitable it might be.The goal of this study is to evaluate COVID-19’s impacts on Puerto Rican’s travel behaviors by analyzing travel flows from Puerto Rico to the contiguous US with a modified gravity model.The roles of socioeconomic factors regarding the Puerto Rican travelers and COVID-19 factors regarding the destination US states have been assessed.COVID-19 was a strong deterring factor of travel at the beginning of the pandemic and also in the winter of 2020,but it did not keep Puerto Ricans from traveling during the summer 2020 when most travel restrictions were lifted.We found that the elderly population of Puerto Rico,despite being more vulnerable to COVID-19,were much more likely to travel during the pandemic.We also found that,during the holiday season in 2020,some socioeconomically disadvantaged populations were more likely to be traveling,a direct contradiction to their travel flows the year prior.These findings shed light on about how disproportionately affected populations behavior changed from pre-pandemic to after the pandemic started.With the continuance of the pandemic,this information is extremely valuable for future planning with respect to emergency management,travel regulation,and social benefit.

Risk of Flash Floods in Urban and Rural Municipalities Triggered by Intense Precipitation in Wielkopolska of Poland

This research analyzed interventions of State Fire Service(SFS)units in the Wielkopolska region of Poland that were triggered by extreme precipitation for the period 2010-2021.Our results demonstrated that the most populated and urbanized towns in the Wielkopolska(Greater Poland,west of Warsaw)region are at the most risk in the event of extreme precipitation occurrence as measured by the total number of interventions made by the SFS.The number of SFS unit interventions in towns,standardized to 10,000 inhabitants,indicates that the highest proportional volume of interventions also occurred in smaller towns.In the rural municipalities the number of SFS unit interventions increases along with higher population density and proportion of infrastructure areas.As analyzed in this study,the 12 years from 2010 to 2021 were characterized by a higher number of days with heavy precipitation,for example,20,30,40,and 50 mm,in comparison to the previous periods 1961-2010 and 1981-2010.Intervention databases collected by emergency services are a valuable source of information for hazard mapping.Based on those and other available data,a statistical model was created and factors influencing the local and regional occurrence of interventions were determined.Increasing suburbanization,the rising proportion of impermeable surfaces,and the impact of climate change are of considerable importance in urban flood risk.It is necessary to help municipalities develop abilities to absorb larger amounts of rainwater.

Typhoon disaster risk zoning for China’s coastal area

Previous studies on typhoon disaster risk zoning in China have focused on individual provinces or small-scale areas and lack county-level results.In this study,typhoon disaster risk zoning is conducted for China’s coastal area,based on data at the county level.Using precipitation and wind data for China and typhoon disaster and social data at the county level for China’s coastal area from 2004 to 2013,first we analyze the characteristics of typhoon disasters in China’s coastal area and then develop an intensity index of factors causing typhoon disasters and a comprehensive social vulnerability index.Finally,by combining the two indices,we obtain a comprehensive risk index for typhoon disasters and conduct risk zoning.The results show that the maximum intensity areas are mainly the most coastal areas of both Zhejiang and Guangdong,and parts of Hainan Island,which is similar to the distribution of typhoon disasters.The maximum values of vulnerability in the northwest of Guangxi,parts of Fujian coastal areas and parts of the Shandong Peninsula.The comprehensive risk index generally decreases from coastal areas to inland areas.The high-risk areas are mainly distributed over Hainan Island,south-western Guangdong,most coastal Zhejiang,the coastal areas between Zhejiang and Fujian and parts of the Shandong Peninsula.