scholarly journals The relationship between geographic space and the incidence of scorpion accidents in the context of social vulnerability

2020 ◽  
Vol 12 (12) ◽  
pp. e3950
Author(s):  
Thassiany Sarmento Oliveira De Almeida ◽  
Maria Carolina Accioly Brelaz De Castro ◽  
Sayonara Maria Lia Fook ◽  
Edwirde Luiz Silva Camêlo ◽  
Lidiane Cristina Félix Gomes ◽  
...  
Keyword(s):  
Spatial Data ◽  
Social Vulnerability ◽  
Average Distance ◽  
Vulnerability Index ◽  
Spatial Data Analysis ◽  
Vulnerable Groups ◽  
Geographic Space ◽  
Strongly Connected ◽  
The Relationship ◽  
Geographical Space

Objective: The relationship between the geographical space and the incidence of scorpion accidents in the context of vulnerability was questioned in the present study through the application of geoprocessing techniques. Methods: In order to recognize vulnerable groups, an ecological study was developed using spatial data analysis techniques of area. Results: A total of 631 cases of scorpion accidents occurred in Campina Grande/Paraíba/Brazil, with an incidence of 154.7 accidents/100,000 inhabitants and an average distance of 0.897 hm between the cases; thus, verifying the possible relationship between accidents and the vulnerability index. Conclusion: Social vulnerability was evidenced by the magnitude in scorpion accidents, considering a higher probability (of attacks) in the most vulnerable areas; therefore, it was possible to verify that the occurrence of scorpion accidents is strongly connected to social factors, and that neighborhoods that have a population with low purchasing power, low schooling and no infrastructure were the most affected.

scholarly journals Social vulnerability assessment using spatial multi-criteria analysis (SEVI model) and the Social Vulnerability Index (SoVI model) – a case study for Bucharest, Romania

2013 ◽  
Vol 13 (6) ◽  
pp. 1481-1499 ◽  
Author(s):  
I. Armaș ◽  
A. Gavriș
Keyword(s):  
Spatial Data ◽  
Social Vulnerability ◽  
Critical Issue ◽  
Vulnerability Index ◽  
Capital City ◽  
Spatial Data Analysis ◽  
Limited Attention ◽  
Social Vulnerability Index ◽  
The Social ◽  
Administrative Units

Abstract. In recent decades, the development of vulnerability frameworks has enlarged the research in the natural hazards field. Despite progress in developing the vulnerability studies, there is more to investigate regarding the quantitative approach and clarification of the conceptual explanation of the social component. At the same time, some disaster-prone areas register limited attention. Among these, Romania's capital city, Bucharest, is the most earthquake-prone capital in Europe and the tenth in the world. The location is used to assess two multi-criteria methods for aggregating complex indicators: the social vulnerability index (SoVI model) and the spatial multi-criteria social vulnerability index (SEVI model). Using the data of the 2002 census we reduce the indicators through a factor analytical approach to create the indices and examine if they bear any resemblance to the known vulnerability of Bucharest city through an exploratory spatial data analysis (ESDA). This is a critical issue that may provide better understanding of the social vulnerability in the city and appropriate information for authorities and stakeholders to consider in their decision making. The study emphasizes that social vulnerability is an urban process that increased in a post-communist Bucharest, raising the concern that the population at risk lacks the capacity to cope with disasters. The assessment of the indices indicates a significant and similar clustering pattern of the census administrative units, with an overlap between the clustering areas affected by high social vulnerability. Our proposed SEVI model suggests adjustment sensitivity, useful in the expert-opinion accuracy.

scholarly journals The Relationship Between Social Vulnerability and COVID-19 Incidence Among Louisiana Census Tracts

2021 ◽  
Vol 8 ◽  
Author(s):  
Erin N. Biggs ◽  
Patrick M. Maloney ◽  
Ariane L. Rung ◽  
Edward S. Peters ◽  
William T. Robinson
Keyword(s):  
Population Density ◽  
Social Vulnerability ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Vulnerability Index ◽  
Social Vulnerability Index ◽  
Census Tracts ◽  
Control And Prevention ◽  
Choropleth Maps ◽  
The Relationship

Objective: To examine the association between the Centers for Disease Control and Prevention (CDC)'s Social Vulnerability Index (SVI) and COVID-19 incidence among Louisiana census tracts.Methods: An ecological study comparing the CDC SVI and census tract-level COVID-19 case counts was conducted. Choropleth maps were used to identify census tracts with high levels of both social vulnerability and COVID-19 incidence. Negative binomial regression with random intercepts was used to compare the relationship between overall CDC SVI percentile and its four sub-themes and COVID-19 incidence, adjusting for population density.Results: In a crude stratified analysis, all four CDC SVI sub-themes were significantly associated with COVID-19 incidence. Census tracts with higher levels of social vulnerability were associated with higher COVID-19 incidence after adjusting for population density (adjusted RR: 1.52, 95% CI: 1.41-1.65).Conclusions: The results of this study indicate that increased social vulnerability is linked with COVID-19 incidence. Additional resources should be allocated to areas of increased social disadvantage to reduce the incidence of COVID-19 in vulnerable populations.

Analyzing Resilience in Local Labor Market Areas: A Spatial Analysis for the Case of Italy

2019 ◽  
Vol 65 (3) ◽  
pp. 189-208
Author(s):  
Barbara Martini ◽  
Marco Platania
Keyword(s):  
Labor Market ◽  
Spatial Analysis ◽  
Spatial Data ◽  
Spatial Relationship ◽  
Spatial Data Analysis ◽  
Market Area ◽  
Observation Unit ◽  
Local Labor Market ◽  
Market Areas ◽  
The Relationship

Abstract The aim of the paper is to analyse if and in which way specialization, geographical localization and spill-over effects affect resilience. The research is carried out using LLMAs (Local Labor Market Areas) as observational unit and spatial data analysis techniques (Anselin 1999, LeSage & Pace, 2009) in Italy. Resilience literature focalized its attention on regions. Despite this, there is no general agreement regarding the most appropriate observation unit. Our aim is not only to investigate the relationship between specialization and resilience at smaller scale using the LLMAs as observation unit but also to explore the spatial relationship among them. Results highlight a strong spatial correlation among LLMAs. As consequence resilience is not only influenced by specialization but also by geographical localization through spill-over effects. JEL Classifications: R10, R12, C23, C33 Spatial analysis; Resilience; Labor Market Area; Italy

scholarly journals Multilevel analysis concerning the relationship between social vulnerability and the healthy use of leisure time in children and adolescents in Argentina: A national population-based study

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1619
Author(s):  
Daniela Moyano ◽  
Zarina Forclaz ◽  
Raúl M. Chaparro ◽  
Akram Hernández-Vásquez ◽  
Nilda R. Perovic
Keyword(s):  
Health Promotion ◽  
Children And Adolescents ◽  
Social Vulnerability ◽  
Leisure Time ◽  
Multilevel Models ◽  
Household Survey ◽  
Vulnerability Index ◽  
Social Vulnerability Index ◽  
Cross Sectional ◽  
The Relationship

Background: Leisure time is a human right and has to be considered part of any health promotion initiative aimed at children and adolescents. The objective of this study was to analyze the relationship between social vulnerability and the healthy use of leisure time in children and adolescents in urban contexts of Argentina, in 2012. Methods: A cross-sectional and analytical study using data from the Module on Activities of Girls, Boys and Adolescents of the Annual Urban Household Survey was carried out. In this survey, a self-administered instrument was applied to 25,915 individuals aged from 5 to 17. A Social Vulnerability Index (SVI) was developed. Association was estimated by multilevel logistic regression. Results: Children and adolescents use most of their leisure time to carry out school activities (90.1%) with art activities having the lowest percentage (21.8%). In the multilevel models on the relationship between a high SVI and non-performance of socialization activities, the OR was 1.99 (p = 0.002, 95% CI: 1.28-3.12). The association between high SVI and non-use of ICT gave an OR of 14.17 (p ≤ 0.001, 95% CI: 5.13-39.17), and between high SVI and non-use of internet, an OR of 21.89 (p ≤ 0.001, 95% CI: 7.50-63.88). Conclusions: A high SVI negatively impacts on some healthy activities of leisure time for children and adolescents in Argentina. The SVI could be a useful tool to guide health promotion initiatives in this population.

scholarly journals GIS-Based Livelihood Vulnerability Index Mapping of the Socioeconomy of the Pekan Community

2019 ◽  
Vol 11 (24) ◽  
pp. 6935
Author(s):  
Nuriah Abd Majid ◽  
Nurafiqah Muhamad Nazi ◽  
Nor Diana Mohd Idris ◽  
Mohd. Raihan Taha
Keyword(s):  
Spatial Data ◽  
Vulnerability Index ◽  
Geographical Information ◽  
Food Storage ◽  
Gis Mapping ◽  
High Exposure ◽  
Index Mapping ◽  
Index Components ◽  
The Relationship ◽  
Combined Data

Monsoon floods that annually hit the east coast of Malaysia have brought a variety of implications, especially for those who inhabit the most vulnerable areas. This study aims to find the relationship between the socioeconomy of the community living and flood events in the district of Pekan, Pahang. This involved geographic analyses which combined data on vulnerability index components represented by Geographical Information System (GIS) mapping. A field survey was conducted to assess the Livelihood Vulnerability Index (LVI), comprising major and sub-components of vulnerability for ten sub-districts in Pekan. LVI mapping was performed for every major component of the LVI with spatial data on the district. Households in the Gancung sub-district were found to be more vulnerable to flooding impact, with a high exposure index (0.59), but reported a positive vulnerability based on adaptive capacity (0.06). Penyur (0.51) was the most vulnerable and sensitive in terms of food security during the flood season. LVI assessment in the Pekan district could be used as an indicator to change livelihoods, survival food storage practices, and other preventive measures in order to curb damages and injuries when annual flooding strikes in the future.

scholarly journals Incidence of low birth weight in Mexico: A descriptive retrospective study from 2008–2017

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0256518
Author(s):  
Mónica Ancira-Moreno ◽  
Eric Monterrubio-Flores ◽  
Sonia Hernández-Cordero ◽  
Isabel Omaña-Guzmán ◽  
Isidro Soloaga ◽  
...  
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
Spatial Data ◽  
Child Nutrition ◽  
National Level ◽  
Spatial Data Analysis ◽  
Vulnerable Groups ◽  
National State ◽  
Public Health Programs ◽  
Maternal And Child Nutrition

According to the WHO, low birth weight (LBW) affects 15–20% of newborns worldwide. In Mexico, there are no national, state, nor municipal estimates that inform the country’s situation over time. The purpose of this study was to estimate the incidence of LBW at the national, state, and municipal levels from 2008 to 2017, and to estimate the LBW incidence based on maternal sociodemographic characteristics, prenatal care and marginalization indexes at the national level using open national data. We used spatial data analysis to georeferenced LBW incidence at the three levels of geographical disaggregation studied. At the national level, the incidence of LBW increased progressively from 6.2% (2008) to 7.1% (2017), and the country’s capital represented the area with the highest incidence. Southeastern and central states reported the highest LBW regional incidence. At the municipal level, the number of municipalities with an incidence of LBW ≥8% increased in both male and female newborns. The incidence of LBW was higher as the marginalization indexes increases. The results from this study may assist in the identification of vulnerable groups and the development of public health programs and policies with an intersectoral approach that improves maternal and child nutrition.

scholarly journals Assessing the Relationship between Social Vulnerability, Social Capital, and Housing Resilience

2020 ◽  
Vol 12 (18) ◽  
pp. 7718
Author(s):  
Sebastian Rowan ◽  
Kyle Kwiatkowski
Keyword(s):  
Social Capital ◽  
Case Studies ◽  
Social Vulnerability ◽  
Vulnerability Index ◽  
Google Earth ◽  
Social Vulnerability Index ◽  
The Social ◽  
Housing Recovery ◽  
Using Data ◽  
The Relationship

Social vulnerability and social capital have been shown to influence how severely communities are impacted by natural hazards and how quickly they recover. Indices exist to quantify these factors using publicly available data; however, more empirical research is needed to validate these indices and support their use in pre-disaster planning and decision making. Using data from the Federal Emergency Management Agency and data gathered through imagery analysis in Google Earth, this study evaluates the effectiveness of two indices of social vulnerability and social capital to predict housing impacts and rates of recovery in Florida and Puerto Rico following Hurricanes Irma and Maria in 2017. We found the social vulnerability index to be statistically significant in explaining the variation of housing impacts in both case studies, with varying results for the sub-indices of social vulnerability. Results for the social capital index were mixed between the case studies, and we found no statistically significant relationship between any of the indices and rates of housing recovery. Our results show that indices such as these can be useful, with an awareness of limitations, for researchers and emergency practitioners, and additional empirical analysis is needed to more fully support their efficacy for resilience assessment.

scholarly journals Assessment of Social Vulnerability to Floods in the Floodplain of Northern Italy

2017 ◽  
Vol 9 (4) ◽  
pp. 717-737 ◽  
Author(s):  
G. Roder ◽  
G. Sofia ◽  
Z. Wu ◽  
P. Tarolli
Keyword(s):  
Social Vulnerability ◽  
Flood Hazard ◽  
Vulnerability Index ◽  
Northern Italy ◽  
Vulnerable Groups ◽  
Management Approach ◽  
Elevated Concentration ◽  
Social Risk ◽  
Social Vulnerability Index ◽  
Spatial Detection

Abstract Practices for reducing the impacts of floods are becoming more and more advanced, centered on communities and reaching out to vulnerable populations. Vulnerable individuals are characterized by social and economic attributes and by societal dynamics rooted in each community. These indicators can magnify the negative impacts of disasters together with the capacity of each individual to cope with these events. The Social Vulnerability Index (SoVI) provides an empirical basis to compare social differences in various spatial scenarios and for specific environmental hazards. This research shows the application of the SoVI to the floodplain of northern Italy, based on the use of 15 census variables. The chosen study area is of particular interest for the high occurrence of flood events coupled with a high level of human activity, landscape transformations, and an elevated concentration of assets and people. The analysis identified a positive spatial autocorrelation across the floodplain that translates into the spatial detection of vulnerable groups, those that are likely to suffer the most from floods. In a second stage, the output of the index was superimposed on the flood hazard map of the study area to analyze the resulting risk. The Piemonte and Veneto regions contain the main areas prone to flood “social” risk, highlighting the need for a cohesive management approach at all levels to recognize local capacities and increase communication, awareness, and preparedness to mitigate the undesirable effects of such events.

scholarly journals KERENTANAN SOSIAL TERHADAP BANJIR DI BANTARAN SUNGAI BENGAWAN SOLO PASCA RELOKASI MANDIRI

2017 ◽  
Vol 19 (2) ◽  
pp. 105
Author(s):  
Agustina Setyaningrum ◽  
Dyah Rahmawati H ◽  
Muh. Aris Marfai
Keyword(s):  
Data Analysis ◽  
Spatial Data ◽  
Social Vulnerability ◽  
Random Sampling ◽  
Secondary Data ◽  
Sampling Technique ◽  
Simple Random Sampling ◽  
Spatial Data Analysis ◽  
Primary Data ◽  
Multi Criteria Evaluation

<p class="judulabstrakindoCxSpFirst"><strong>ABSTRAK</strong></p><p class="abstrak">Banjir besar pada akhir tahun 2007 mengharuskan Pemerintah Kota Surakarta untuk melaksanakan program relokasi paska terjadinya banjir. Masyarakat pindah dan menempati lokasi relokasi namun tidak jauh dari bantaran Sungai Bengawan Solo. Penelitian ini bertujuan untuk menilai tingkat kerentanan sosial masyarakat terhadap banjir pasca relokasi yang bertempat tinggal di sempadan Sungai Bengawan Solo. Data yang digunakan dalam penelitian ini meliputi data primer dan data sekunder. Teknik pengambilan sampel yaitu <em>s</em><em>imple random sampling. </em>Analisis data keruangan dilakukan dengan metode <em>Spatial Multi Criteria Evaluation (SMCE)</em><em>. </em>Penilaian kerentanan dengan menggunakan dua skenario yaitu skenario lingkungan dan skenario ekonomi. Hasil proses SMCE menunjukkan bahwa di lokasi relokasi, terdapat wilayah-wilayah yang masuk dalam kerentanan sosial tinggi dan sedang. Berdasarkan skenario lingkungan, menunjukkan bahwa seluruh kelurahan/desa lokasi relokasi memiliki kerentanan tinggi kecuali Kelurahan Mojosongo yang memiliki kerentanan sedang. Berdasarkan skenario ekonomi, menunjukan lokasi relokasi yang termasuk dalam kerentanan tinggi adalah Kelurahan Semanggi, Jebres, dan Desa Gadingan. Sedangkan lokasi relokasi yang termasuk dalam kerentanan sedang dalam skenario ekonomi adalah Kelurahan Mojosongo, Desa Laban, dan Desa Plumbon.</p><p><strong>Kata k</strong><strong>unci</strong>: kerentanan, banjir, relokasi</p><p class="judulabstrakingCxSpMiddle"><strong>ABSTRACT</strong></p><p class="Abstrakeng">        Great flood at the end of 2007 requires Government of Surakarta to implement the relocation program after the flood. The community moved and occupied the relocation site but not far from the banks of Bengawan Solo River. The aims of the study are to assess the level of social vulnerability after relocation. The data used in this study consist of primary data and secondary data. The sampling technique used in this study was simple random sampling. Spatial data analysis was conducted using Spatial Multi Criteria Evaluation (SMCE). The vulnerability assessment using two scenarios, the environmental scenario and economic scenario. Results of the SMCE showed that in relocation sites there are areas that fall into high and medium social vulnerability. Based on the environmental scenarios, the relocation areas have high vulnerability except for Mojosongo which have moderate vulnerability. Based on the economic scenarios, the relocation area that included in high vulnerability are Semanggi, Jebres, and Gadingan.While the relocation area that included in moderate vulnerability using economic scenario are Mojosongo, Laban, and Plumbon.</p><p><strong><em>Keywords</em></strong><em>: </em><em>vulnerability, flood, relocation </em></p>

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