Response time to flood events using a social vulnerability index (ReTSVI)

Abstract. Current methods to estimate evacuation time during a natural disaster do not consider the socioeconomic and demographic characteristics of the population. This article develops the Response Time by Social Vulnerability Index (ReTSVI). ReTSVI combines a series of modules that are pieces of information that interact during an evacuation, such as evacuation rate curves, mobilization, inundation models, and social vulnerability indexes, to create an integrated map of the evacuation rate in a given location. We provide an example of the application of ReTSVI in a potential case of a severe flood event in Huaraz, Peru. The results show that during the first 5 min of the evacuation, the population that lives in neighborhoods with a high social vulnerability evacuates 15 % and 22 % fewer people than the blocks with medium and low social vulnerability. These differences gradually decrease over time after the evacuation warning, and social vulnerability becomes less relevant after 30 min. The results of the application example have no statistical significance, which should be considered in a real case of application. Using a methodology such as ReTSVI could make it possible to combine social and physical vulnerability in a qualitative framework for evacuation, although more research is needed to understand the socioeconomic variables that explain the differences in evacuation rate.

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Response Time to Flood Events using a Social Vulnerability Index (ReTSVI)

10.5194/nhess-2017-395 ◽

2017 ◽

Author(s):

Alvaro Quezada-Hofflinger ◽

Marcelo A. Somos-Valenzuela ◽

Arturo Vallejos-Romero

Keyword(s):

Response Time ◽

Social Vulnerability ◽

Vulnerability Index ◽

Second Step ◽

Demographic Information ◽

Social Vulnerability Index ◽

The Social ◽

Hazard Zone ◽

Severe Flood ◽

Potential Case

Abstract. Current methods used to estimate people's evacuation times during a natural disaster assume that human responses across different social groups are similar. However, individuals respond differently based on their socioeconomic and demographic characteristics and previous knowledge. This article develops the Response Time by Social Vulnerability Index (ReTSVI), which is a methodology to estimate how human response time to evacuation warnings during a natural hazard is affected by considering characteristics related to both physical and social vulnerability. ReTSVI is a three-step methodology: first we calculate a population's evacuation curves considering social vulnerability level, certain demographic information and a model that describes an inundation hazard. Then, we use a mobilization model to generate evacuation maps per level of vulnerability and we also estimate the social vulnerability index for the area of study. In the third step, we combine the results from the second step to generate a map that indicates the percentage of people that could evacuate a hazard zone according to their social vulnerability level. Finally, we provide an example of the application of ReTSVI in a potential case of a severe flood event in Huaraz, Peru. The results show that during the first 5 minutes of the evacuation, the population that lives in neighborhoods with high social vulnerability evacuate 15 % and 22 % fewer people than the neighborhoods with medium and low social vulnerability. These differences gradually decrease over time after the evacuation warning and social vulnerability becomes less relevant after 30 minutes. Using a methodology such as ReTSVI allows first responders to identify areas where the same level of physical vulnerability affects distinct groups differently, providing them with a tool to quantify the differences in time to evacuate and where the resources before and during an evacuation should be preferentially allocated.

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An Assessment of Social and Physical Vulnerability to Hydroclimate Extremes in Appalachia

10.21203/rs.3.rs-469519/v1 ◽

2021 ◽

Author(s):

Leah R. Handwerger ◽

Jennifer R. Runkle ◽

Ronald Leeper ◽

Elizabeth Shay ◽

Kara Dempsey ◽

...

Keyword(s):

Social Vulnerability ◽

Scientific Community ◽

Vulnerability Index ◽

Precipitation Variability ◽

Mitigation Strategies ◽

Climate Projections ◽

Social Vulnerability Index ◽

Physical Vulnerability ◽

Vulnerable Communities ◽

Vulnerability Indicators

Abstract Appalachia is a cultural region in the southern and central Appalachian Mountains that lags behind the nation in several social vulnerability indicators. Climate projections over this region indicate that precipitation variability will increase in both severity and frequency in future decades, suggesting that the occurrence of natural hazards related to hydroclimate extremes will also increase. The objective of this study was to investigate the spatiotemporal patterns of drought and precipitation and determine how trends overlap with vulnerable communities across Appalachia. The study utilized trend analysis through Mann-Kendall calculations and a Social Vulnerability Index, resulting in a bivariate map that displays areas most susceptible to adverse effects from hydroclimate extremes. Results show the southwestern portion of the region as most vulnerable to increased precipitation, and the central-southeast most vulnerable to an increase in drought-precipitation variability. This study is among the first to utilize the boundaries defined by the Appalachian Regional Commission from a climatological perspective, allowing findings to reach audiences outside the scientific community and bring more effective mitigation strategies that span from the local to federal levels.

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MAPPING TSUNAMI VULNERABILITY FOR MATARAM CITY IN LOMBOK ISLAND – INDONESIA: A PHYSICAL AND SOCIOECONOMIC ASSESSMENT

Jurnal Pengembangan Kota ◽

10.14710/jpk.3.1.60-79 ◽

2015 ◽

Vol 3 (1) ◽

pp. 60

Author(s):

Andhi Pratama Putra

Keyword(s):

Social Vulnerability ◽

Composite Index ◽

Vulnerability Index ◽

Social Vulnerability Index ◽

Physical Vulnerability ◽

Economic Vulnerability ◽

Physical Vulnerability Index ◽

Lombok Island

Letak kedekatan lokasi geografis dengan lempeng tektonik Eurasian dan Indo-Australian membawa konsekuensi logis terhadap tingginya resiko kebencanaan, terutama gempa dan tsunami, bagi Indonesia. Kota Mataram yang merupakan ibukota Provinsi Nusa Tenggara Barat merupakan salah satu wilayah yang perlu mendapatkan perhatian khusus terhadap resiko bencana tsunami. Sebagai langkah awal, identifikasi lokasi yang paling rentan terhadap resiko bencana tsunami perlu dilakukan dengan memadukan aspek-aspek fisik, sosial dan ekonomi. Penelitian ini bertujuan mengidentifikasikan lokasi paling rentan terhadap resiko bencana tsunami di Kota Mataram dengan menggunakan analisa sistem informasi geografis (GIS). Penilaian dilakukan dengan mengembangkan Indeks Gabungan (Composite Index) berupa Total Vulnerability Index (TVI) yang merupakan kombinasi Indeks Kerentanan Fisik/ Physical Vulnerability Index (PVI), Indeks Kerentanan Sosial/ Social Vulnerability Index (SVI) dan Indeks Kerentanan Ekonomi/ Economic Vulnerability Index (EVI). Hasil analisis berhasil menemukenali bahwa Kota Tua Ampenan merupakan wilayah di Kota Mataram dengan nilai indeks gabungan tertinggi yang mencerminkan tingkat kerentanan yang paling tinggi.

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The constituent components and local indicator variables of social vulnerability index

Natural Hazards ◽

10.1007/s11069-021-04938-9 ◽

2021 ◽

Author(s):

Gainbi Park ◽

Zengwang Xu

Keyword(s):

Social Vulnerability ◽

Vulnerability Index ◽

Social Vulnerability Index ◽

Indicator Variables

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Social Vulnerability across the Great Lakes Basin: A County-Level Comparative and Spatial Analysis

Sustainability ◽

10.3390/su13137274 ◽

2021 ◽

Vol 13 (13) ◽

pp. 7274

Author(s):

Joshua T. Fergen ◽

Ryan D. Bergstrom

Keyword(s):

Great Lakes ◽

Spatial Patterns ◽

Social Vulnerability ◽

Vulnerability Index ◽

Social Vulnerability Index ◽

Great Lakes Basin ◽

Empirical Examination ◽

Regional Patterns ◽

Urban Rural ◽

Social Vulnerabilities

Social vulnerability refers to how social positions affect the ability to access resources during a disaster or disturbance, but there is limited empirical examination of its spatial patterns in the Great Lakes Basin (GLB) region of North America. In this study, we map four themes of social vulnerability for the GLB by using the Center for Disease Control’s Social Vulnerability Index (CDC SVI) for every county in the basin and compare mean scores for each sub-basin to assess inter-basin differences. Additionally, we map LISA results to identify clusters of high and low social vulnerability along with the outliers across the region. Results show the spatial patterns depend on the social vulnerability theme selected, with some overlapping clusters of high vulnerability existing in Northern and Central Michigan, and clusters of low vulnerability in Eastern Wisconsin along with outliers across the basins. Differences in these patterns also indicate the existence of an urban–rural dimension to the variance in social vulnerabilities measured in this study. Understanding regional patterns of social vulnerability help identify the most vulnerable people, and this paper presents a framework for policymakers and researchers to address the unique social vulnerabilities across heterogeneous regions.

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Applying the Social Vulnerability Index as a Leading Indicator to Protect Fire-Based Emergency Medical Service Responders’ Health

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18158049 ◽

2021 ◽

Vol 18 (15) ◽

pp. 8049

Author(s):

Emily J. Haas ◽

Alexa Furek ◽

Megan Casey ◽

Katherine N. Yoon ◽

Susan M. Moore

Keyword(s):

Emergency Response ◽

Social Vulnerability ◽

Vulnerability Index ◽

Fire Service ◽

Household Composition ◽

Fire Departments ◽

Social Vulnerability Index ◽

Response Planning ◽

Leading Indicator ◽

Increased Risk

During emergencies, areas with higher social vulnerability experience an increased risk for negative health outcomes. However, research has not extrapolated this concept to understand how the workers who respond to these areas may be affected. Researchers from the National Institute for Occupational Safety and Health (NIOSH) merged approximately 160,000 emergency response calls received from three fire departments during the COVID-19 pandemic with the CDC’s publicly available Social Vulnerability Index (SVI) to examine the utility of SVI as a leading indicator of occupational health and safety risks. Multiple regressions, binomial logit models, and relative weights analyses were used to answer the research questions. Researchers found that higher social vulnerability on household composition, minority/language, and housing/transportation increase the risk of first responders’ exposure to SARS-CoV-2. Higher socioeconomic, household, and minority vulnerability were significantly associated with response calls that required emergency treatment and transport in comparison to fire-related or other calls that are also managed by fire departments. These results have implications for more strategic emergency response planning during the COVID-19 pandemic, as well as improving Total Worker Health® and future of work initiatives at the worker and workplace levels within the fire service industry.

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Effectiveness of mass treatment of Schistosoma mansoni infection in socially vulnerable areas of a state in northeastern Brazil, 2011–2014

Archives of Public Health ◽

10.1186/s13690-021-00549-9 ◽

2021 ◽

Vol 79 (1) ◽

Author(s):

Flávia Silvestre Outtes Wanderley ◽

Ulisses Montarroyos ◽

Cristine Bonfim ◽

Carolina Cunha-Correia

Keyword(s):

Schistosoma Mansoni ◽

Correspondence Analysis ◽

Social Vulnerability ◽

Multiple Correspondence Analysis ◽

Vulnerability Index ◽

Two Dimensions ◽

Northeastern Brazil ◽

Mass Treatment ◽

Social Vulnerability Index ◽

Treatment Information

Abstract Background To assess the effectiveness of mass treatment of Schistosoma mansoni infection in socially vulnerable endemic areas in northeastern Brazil. Method An ecological study was conducted, in which 118 localities in 30 municipalities in the state of Pernambuco were screened before 2011 and in 2014 (after mass treatment). Information on the endemic baseline index, mass treatment coverage, socio-environmental conditions and social vulnerability index were used in the multiple correspondence analysis. One hundred fourteen thousand nine hundred eighty-seven people in 118 locations were examined. Results The first two dimensions of the multiple correspondence analysis represented 55.3% of the variability between locations. The human capital component of the social vulnerability index showed an association with the baseline endemicity index. There was a significant reduction in positivity for schistosomes. For two rounds, for every extra 1% of initial endemicity index, the fixed effect of 13.62% increased by 0.0003%, achieving at most 15.94%. Conclusions The mass treatment intervention helped to reduce transmission of schistosomiasis in areas of high endemicity. Thus, it can be recommended that application of mass treatment should be accompanied by other control actions, such as basic sanitation, monitoring of intermediate vectors and case surveillance.

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Exploratory Testing of an Artificial Neural Network Classification for Enhancement of the Social Vulnerability Index

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi4041774 ◽

2015 ◽

Vol 4 (4) ◽

pp. 1774-1790 ◽

Cited By ~ 6

Author(s):

Ryan Hile ◽

Thomas Cova

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Social Vulnerability ◽

Vulnerability Index ◽

Social Vulnerability Index ◽

Neural Network Classification ◽

Exploratory Testing ◽

The Social ◽

Artificial Neural

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Impact of Social Vulnerability on Access to Educational Programming Designed to Enhance Living Donation

Progress in Transplantation ◽

10.1177/15269248211046014 ◽

2021 ◽

pp. 152692482110460

Author(s):

Alexis J. Carter ◽

Rhiannon D. Reed ◽

A. Cozette Kale ◽

Haiyan Qu ◽

Vineeta Kumar ◽

...

Keyword(s):

Health Care ◽

Social Vulnerability ◽

Living Donor ◽

Research Question ◽

College Education ◽

Vulnerability Index ◽

Social Vulnerability Index ◽

Chi Square ◽

Control And Prevention ◽

Transplant Candidate

Introduction Transplant candidate participation in the Living Donor Navigator Program is associated with an increased likelihood of achieving living donor kidney transplantation; yet not every transplant candidate participates in navigator programming. Research Question We sought to assess interest and ability to participate in the Living Donor Navigator Program by the degree of social vulnerability. Design Eighty-two adult kidney-only candidates initiating evaluation at our center provided Likert-scaled responses to survey questions on interest and ability to participate in the Living Donor Navigator Program. Surveys were linked at the participant-level to the Centers for Disease Control and Prevention Social Vulnerability Index and county health rankings and overall social vulnerability and subthemes, individual barriers, telehealth capabilities/ knowledge, interest, and ability to participate were assessed utilizing nonparametric Wilcoxon ranks sums tests, chi-square, and Fisher's exact tests. Results Participants indicating distance as a barrier to participation in navigator programming lived approximately 82 miles farther from our center. Disinterested participants lived in areas with the highest social vulnerability, higher physical inactivity rates, lower college education rates, and higher uninsurance (lack of insurance) and unemployment rates. Similarly, participants without a computer, who never heard of telehealth, and who were not encouraged to participate in telehealth resided in areas of highest social vulnerability. Conclusion These data suggest geography combined with being from under-resourced areas with high social vulnerability was negatively associated with health care engagement. Geography and poverty may be surrogates for lower health literacy and fewer health care interactions.

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