论文标题
网络扩散模型揭示了恢复乘数和异质空间效应
Network Diffusion Model Reveals Recovery Multipliers and Heterogeneous Spatial Effects in Post-Disaster Community Recovery
论文作者
论文摘要
社区从危害和危机中恢复通过社会和空间网络中的各种扩散过程发生。但是，有关社区社会空间网络中恢复传播的现有知识是相当有限的。为了弥合这一差距，在这项研究中，我们创建了一个网络扩散模型，以表征社区空间网络中人口活动恢复的展开。使用与休斯顿地区2017年哈维飓风中基于位置的数据计算出的人口活动恢复持续时间有关的数据，我们对基于阈值的网络扩散模型进行了参数，并评估了空间效应中同质性的程度。然后，我们与遗传算法一起实现了网络扩散模型，以模拟和识别恢复乘数。结果表明，恢复的空间效应在空间区域之间是异质的。与其他空间区域相比，某些空间区域在恢复中表现出更大的空间效应（空间相互依赖性）。此外，结果表明，低收入区域对其恢复表现出更大的空间效应。低收入地区恢复的空间影响更大，这意味着更多地依赖邻近地区的资源和设施，并解释了在社会脆弱人群居住的地区存在缓慢的恢复热点。此外，结果表明，低收入和少数群体是社区恢复乘数。这些恢复乘数的恢复速度越快；整个社区的恢复越快。因此，优先考虑这些领域的恢复资源分配可以加快整个社区的恢复并促进恢复平等和公平性。
Community recovery from hazards and crises occurs through various diffusion processes within social and spatial networks of communities. Existing knowledge regarding the diffusion of recovery in community socio-spatial networks, however, is rather limited. To bridge this gap, in this study, we created a network diffusion model to characterize the unfolding of population activity recovery in spatial networks of communities. Using data related to population activity recovery durations calculated from location-based data in the context of 2017 Hurricane Harvey in the Houston area, we parameterized the threshold-based network diffusion model and evaluated the extent of homogeneity in spatial effects. Then we implemented the network diffusion model along with the genetic algorithm to simulate and identify recovery multipliers. The results show that the spatial effects of recovery are rather heterogeneous across spatial areas; some spatial areas demonstrate a greater spatial effect (spatial interdependence) in their recovery compared with others. Also, the results show that low-income areas demonstrate a greater spatial effect in their recovery. The greater spatial effects in recovery of low-income areas imply more reliance on resources and facilities of neighboring areas and also explain the existence of slow recovery hotspots in areas where socially vulnerable populations reside. Also, the results show that low-income and minority areas are community recovery multipliers; the faster the recovery of these recovery multipliers; the faster the recovery of the entire community. Hence, prioritizing these areas for recovery resource allocation could expedite the recovery of the overall community and promote recovery equality and equity.
