The spreading process identification and influential factors analyze of the American opioid crisis based on big data

Jiaying Kong, Zhaoyang Ye, Yiyang Zhou, Ying Jiang
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引用次数: 0

Abstract

The spread of opioid crisis has posed many negative impacts on the society of the United State and attracts the attention of the US government and many relevant organizations to mitigate the increasing of drug abuse. This passage mainly describe the spreading trend of opioid crisis between five states/counties and analyze the important social and economic data of America to identify some important influential factors. In this way, an optimized spreading model based on cellular automata with the combination of life-cycle graph of the four stages in spreading process can be achieved and the exact starting point of each state can be known. With the factor analyze of socio-economic information extracted from the U.S. Census Bureau,the characteristics and idiosyncrasy of people who commonly get drug abusing problems can be identified And with more factors taken into consideration the spreading model can be optimized with multi-layer factors so that more strategies can be made to help restricting the drug abuse.
基于大数据的美国阿片类药物危机蔓延过程识别及影响因素分析
阿片类药物危机的蔓延给美国社会带来了许多负面影响,引起了美国政府和许多相关组织的关注,以缓解日益严重的药物滥用问题。这篇文章主要描述了阿片类药物危机在五个州/县之间的蔓延趋势,并分析了美国重要的社会经济数据,找出一些重要的影响因素。这样就可以得到一个基于元胞自动机的优化传播模型,并结合传播过程的四个阶段的生命周期图,并且可以知道每个状态的确切起点。通过对美国人口普查局提取的社会经济信息进行因子分析,可以识别出常见药物滥用问题人群的特征和特质,考虑到更多的因素,可以通过多层因素优化传播模型,从而制定更多的策略来帮助限制药物滥用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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