网络扩散模型揭示了灾后社区恢复中的恢复乘数和异质空间效应
1Zachry Department of Civil and Environmental Engineering, Texas A&M University, 199 Spence St., College Station, TX, 77843-3136, USA. joeyliu0324@tamu.edu.
Scientific reports
|November 4, 2023
概括
社区从灾难中恢复是复杂的. 这项研究表明,优先考虑低收入和少数民族地区可以加速社区的整体复苏,促进公平.
科学领域:
- 灾难恢复科学 灾难恢复科学
- 网络科学 网络科学
- 社会空间网络分析
背景情况:
- 社区从危险中恢复需要在社会和空间网络中进行扩散过程.
- 在社区社会空间网络中关于恢复传播的知识是有限的.
研究的目的:
- 为人口活动恢复开发和验证网络扩散模型.
- 评估模型捕捉空间恢复模式的能力.
- 确定影响社区恢复异质性的因素.
主要方法:
- 开发了一个基于值的网络扩散模型.
- 利用了从哈维风 (休斯顿,2017年) 中恢复人口活动的数据.
- 使用遗传算法进行模型参数化和模拟.
主要成果:
- 恢复扩散表现出显著的空间异质性.
- 低收入和少数群体社区作为复苏乘数,加速更广泛的复苏.
- 这些地区的更快恢复与整个社区的加速恢复有关.
结论:
- 网络扩散模型有效地捕捉空间恢复模式.
- 在资源分配中优先考虑弱势群体 (低收入群体,少数群体) 可以加快整体复苏.
- 有针对性的资源分配可以提高恢复速度和公平性.
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