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

2015 ◽  
Vol 4 (4) ◽  
pp. 1774-1790 ◽  
Author(s):  
Ryan Hile ◽  
Thomas Cova
2020 ◽  
Author(s):  
Mark Allen Thornton ◽  
Milena Rmus ◽  
Diana Tamir

People’s thoughts and feelings ebb and flow in predictable ways: surprise arises quickly, anticipation ramps up slowly, regret follows anger, love begets happiness, and so forth. Predicting these transitions between mental states can help people successfully navigate the social world. We hypothesize that the goal of predicting state dynamics shapes people’ mental state concepts. Across seven studies, when people observed more frequent transitions between a pair of novel mental states, they judged those states to be more conceptually similar to each other. In an eighth study, an artificial neural network trained to predict real human mental state dynamics spontaneously learned the same conceptual dimensions that people use to understand these states: the 3d Mind Model. Together these results suggest that mental state dynamics explain the origins of mental state concepts.


Author(s):  
S. V. Shiva Prasad Sharma ◽  
P. S. Roy ◽  
V. Chakravarthi

<p><strong>Abstract.</strong> In the present study, an attempt is made to understand the impact on Social Vulnerability of the Kopili basin due to various severities of flood hazard. The flood hazard is generated using multi-temporal historical satellite based analysis and integration of annual flood inundation layers. The census of India data of 2001 and 2011 is spatially joined with village database to study the impact at village level. Using 5 Census variables from both Census 2001 &amp;amp; 2011 as vulnerability indicators, the Social Vulnerability Index (SVI) is derived and classified into various vulnerable zones namely Low, Moderate and High Vulnerable zones. The findings of the study show that the number of villages falling in Low and High Vulnerable zones had decreased during Census 2011 when compared to 2001 and a rise of 6% in villages falling in moderate vulnerable zones during 2011 is observed. The spatial database generated is useful to understand the impact of floods on the Social Vulnerability status of the basin and can be a useful input to further study the Physical, Economic and Environmental Vulnerabilities of the basin.</p>


Author(s):  
Jennifer J. LeRose ◽  
Courtney Merlo ◽  
Phong Duong ◽  
Kelsi Harden ◽  
Rebecca Rush ◽  
...  

Abstract The Social Vulnerability Index (SVI) is used to stratify community need for support during disasters. We evaluated relationships between the SVI and personal protective equipment shortages, COVID-19 caseload, and mortality rates in skilled nursing facilities (SNFs). In SVI quartile 4, personal protective equipment shortages were 2.3 times those in SNFs in quartile 1; COVID-19 case loads were 1.6 times those of SNFs in quartile 1; and mortality rates in were 1.9 times those of SNFs in SVI quartile 1.


2019 ◽  
Vol 67 (6) ◽  
pp. 1305-1306 ◽  
Author(s):  
Camille Ouvrard ◽  
José Alberto Avila-Funes ◽  
Jean-François Dartigues ◽  
Hélène Amieva ◽  
Maturin Tabue-Teguo

Author(s):  
Tu Nguyen ◽  
Patrice Ngangue ◽  
Tarek Bouhali ◽  
Bridget Ryan ◽  
Moira Stewart ◽  
...  

Background: Social aspects play an important role in individual health and should be taken into consideration in the long-term care for people with multimorbidity. Purposes: To describe social vulnerability, to examine its correlation with the number of chronic conditions, and to investigate which chronic conditions were significantly associated with the most socially vulnerable state in patients with multimorbidity. Methods: Cross-sectional analysis from the baseline data of the Patient-Centred Innovations for Persons with Multimorbidity (PACEinMM) Study. Participants were patients attending primary healthcare settings in Quebec, Canada. A social vulnerability index was applied to identify social vulnerability level. The index value ranges from 0 to 1 (1 as the most vulnerable). Spearman’s rank correlation coefficient was calculated for the correlation between the social vulnerability index and the number of chronic conditions. Logistic regression was applied to investigate which chronic conditions were independently associated with the most socially vulnerable state. Results: There were 301 participants, mean age 61.0 ± 10.5, 53.2% female. The mean number of chronic health conditions was 5.01 ± 1.82, with the most common being hyperlipidemia (78.1%), hypertension (69.4%), and obesity (54.2%). The social vulnerability index had a median value of 0.13 (range 0.00–0.78). There was a positive correlation between the social vulnerability index and the number of chronic conditions (r = 0.24, p < 0.001). Obesity, depression/anxiety, and cardiovascular diseases were significantly associated with the most socially vulnerable patients with multimorbidity. Conclusions: There was a significant correlation between social vulnerability and the total number of chronic conditions, with depression/anxiety, obesity, and cardiovascular diseases being the most related to social vulnerability.


Geriatrics ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 24
Author(s):  
Natalia Sánchez-Garrido ◽  
Sara G. Aguilar-Navarro ◽  
José Alberto Ávila-Funes ◽  
Olga Theou ◽  
Melissa Andrew ◽  
...  

The social vulnerability index (SVI) independently predicts mortality and others adverse outcomes across different populations. There is no evidence that the SVI can predict adverse outcomes in individuals living in countries with high social vulnerability such as Latin America. The aim of this study was to analyze the association of the SVI with mortality and disability in Mexican middle-aged and older adults. This is a longitudinal study with a follow-up of 47 months, the Mexican Health and Aging Study, including people over the age of 40 years. A SVI was calculated using 42 items stratified in three categories low (<0.36), medium (0.36–0.47), and high (>0.47) vulnerability. We examined the association of SVI with three-year mortality and incident disability. Cox and logistic regression models were fitted to test these associations. We included 14,217 participants (58.4% women) with a mean age of 63.9 years (±SD 10.1). The mean SVI was of 0.42 (±SD 0.12). Mortality rate at three years was 6% (n = 809) and incident disability was 13.2% (n = 1367). SVI was independently associated with mortality, with a HR of 1.4 (95% CI 1.1–1.8, p < 0.001) for the highest category of the SVI compared to the lowest. Regarding disability, the OR was 1.3 (95% CI 1.1–1.5, p = 0.026) when comparing the highest and the lowest levels of the SVI. The SVI was independently associated with mortality and disability. Our findings support previous evidence on the SVI and builds on how this association persists even in those individuals with underlying contextual social vulnerability.


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