TY - JOUR
T1 - Understanding post-disaster population recovery patterns
AU - Yabe, Takahiro
AU - Tsubouchi, Kota
AU - Fujiwara, Naoya
AU - Sekimoto, Yoshihide
AU - Ukkusuri, Satish V.
N1 - Funding Information:
The work of T.Y. and S.V.U. is partly funded by NSF grant no. 1638311 CRISP Type 2/Collaborative Research: Critical Transitions in the Resilience and Recovery of Interdependent Social and Physical Networks. N.F. was supported by JSPS KAKENHI grant number JP17H01742.
Publisher Copyright:
© 2020 The Author(s) Published by the Royal Society. All rights reserved.
PY - 2020/2/1
Y1 - 2020/2/1
N2 - Despite the rising importance of enhancing community resilience to disasters, our understandings on when, how and why communities are able to recover from such extreme events are limited. Here, we study the macroscopic population recovery patterns in disaster affected regions, by observing human mobility trajectories of over 1.9 million mobile phone users across three countries before, during and after five major disasters. We find that, despite the diversity in socio-economic characteristics among the affected regions and the types of hazards, population recovery trends after significant displacement resemble similar patterns after all five disasters. Moreover, the heterogeneity in initial and long-term displacement rates across communities in the three countries were explained bya set of key common factors, including the community's median income level, population, housing damage rates and the connectedness to other cities. Such insights discovered from large-scale empirical data could assist policymaking in various disciplines for developing community resilience to disasters.
AB - Despite the rising importance of enhancing community resilience to disasters, our understandings on when, how and why communities are able to recover from such extreme events are limited. Here, we study the macroscopic population recovery patterns in disaster affected regions, by observing human mobility trajectories of over 1.9 million mobile phone users across three countries before, during and after five major disasters. We find that, despite the diversity in socio-economic characteristics among the affected regions and the types of hazards, population recovery trends after significant displacement resemble similar patterns after all five disasters. Moreover, the heterogeneity in initial and long-term displacement rates across communities in the three countries were explained bya set of key common factors, including the community's median income level, population, housing damage rates and the connectedness to other cities. Such insights discovered from large-scale empirical data could assist policymaking in various disciplines for developing community resilience to disasters.
KW - Disaster resilience
KW - Human mobility
KW - Mobile phone data
KW - Population recovery
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U2 - 10.1098/rsif.2019.0532
DO - 10.1098/rsif.2019.0532
M3 - Article
C2 - 32070218
AN - SCOPUS:85079684315
VL - 17
JO - Journal of the Royal Society Interface
JF - Journal of the Royal Society Interface
SN - 1742-5689
IS - 163
M1 - 0532
ER -