Exploring geological and socio-demographic factors associated with under-five mortality in the Wenchuan earthquake using neural network model.

On 12 May 2008, a devastating earthquake occurred in Sichuan Province, China, taking tens of thousands of lives and destroying the homes of millions of people. Among the large number of dead or missing were children, particularly children aged less than five years old, a fact which drew significant...

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Publicado en:International Journal of Environmental Health Research Vol. 22; no. 2; pp. 184 - 197
Autores principales: Hu, Yi, Wang, Jinfeng, Li, Xiaohong, Ren, Dan, Driskell, Luke, Zhu, Jun
Formato: pictorial research tables/charts Journal Article
Publicado: Taylor & Francis Ltd Apr2012
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Exploring geological and socio-demographic factors associated with under-five mortality in the Wenchuan earthquake using neural network model.
      aug:
        au:
          Hu, Yi
          Wang, Jinfeng
          Li, Xiaohong
          Ren, Dan
          Driskell, Luke
          Zhu, Jun
        affil: School of Earth & Mineral Resources, China University of Geosciences, Beijing; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing
      sug:
        subj:
          Neural Networks (Computer)
          Child Mortality Risk Factors
          Natural Disasters
          Human
          China
          Geographic Factors
          Socioeconomic Factors
          Child, Preschool
          Descriptive Statistics
          Income
          Conceptual Framework
          Data Analysis Software
          Funding Source
          Child, Preschool: 2-5 years
      ab: On 12 May 2008, a devastating earthquake occurred in Sichuan Province, China, taking tens of thousands of lives and destroying the homes of millions of people. Among the large number of dead or missing were children, particularly children aged less than five years old, a fact which drew significant media attention. To obtain relevant information specifically to aid further studies and future preventative measures, a neural network model was proposed to explore some geological and socio-demographic factors associated with earthquake-related child mortality. Sensitivity analysis showed that topographic slope (mean 35.76%), geomorphology (mean 24.18%), earthquake intensity (mean 13.68%), and average income (mean 11%) had great contributions to child mortality. These findings could provide some clues to researchers for further studies and to policy makers in deciding how and where preventive measures and corresponding policies should be implemented in the reconstruction of communities.
      pubtype: Academic Journal
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        research
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    language: English
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