Understanding post-disaster population recovery patterns
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 mob...
Uloženo v:
| Vydáno v: | Journal of the Royal Society interface Ročník 17; číslo 163; s. 20190532 |
|---|---|
| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
England
01.02.2020
|
| Témata: | |
| ISSN: | 1742-5662, 1742-5662 |
| On-line přístup: | Zjistit podrobnosti o přístupu |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | 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 by a 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. |
|---|---|
| AbstractList | 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 by a 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. 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 by a 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.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 by a 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. |
| Author | Sekimoto, Yoshihide Ukkusuri, Satish V Tsubouchi, Kota Yabe, Takahiro Fujiwara, Naoya |
| Author_xml | – sequence: 1 givenname: Takahiro surname: Yabe fullname: Yabe, Takahiro organization: Lyles School of Civil Engineering, Purdue University, West Lafayette, IN, USA – sequence: 2 givenname: Kota surname: Tsubouchi fullname: Tsubouchi, Kota organization: Yahoo Japan Corporation, Tokyo, Japan – sequence: 3 givenname: Naoya surname: Fujiwara fullname: Fujiwara, Naoya organization: Institute of Industrial Science, University of Tokyo, Tokyo, Japan – sequence: 4 givenname: Yoshihide surname: Sekimoto fullname: Sekimoto, Yoshihide organization: Institute of Industrial Science, University of Tokyo, Tokyo, Japan – sequence: 5 givenname: Satish V surname: Ukkusuri fullname: Ukkusuri, Satish V organization: Lyles School of Civil Engineering, Purdue University, West Lafayette, IN, USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32070218$$D View this record in MEDLINE/PubMed |
| BookMark | eNpNj01LxDAYhIOsuLvVq0fp0Uvrm6Rp0qMsfsGCF_dc0uSNVNq0Jq2w_96KK3iaGWYYeLZk5QePhFxTyClU6i7E1uUMaJWD4OyMbKgsWCbKkq3--TXZxvgBwCUX4oKsOQMJjKoNUQdvMcRJe9v693Qc4pTZNuo4YVjSOHd6agefBjTDF4ZjOuppqXy8JOdOdxGvTpqQw-PD2-45278-vezu95kpqGCZE0JyY6kW0iAYNChtAU5ZaFC6ykigtqlKwxYYaZ1TmhaoLSi3rDlKlpDb398xDJ8zxqnu22iw67THYY4140IJJX9QE3Jzms5Nj7YeQ9vrcKz_aNk353RaEg |
| CitedBy_id | crossref_primary_10_1016_j_ijdrr_2024_104931 crossref_primary_10_1016_j_scs_2022_104213 crossref_primary_10_1038_s41598_023_48130_4 crossref_primary_10_1038_s41598_022_20384_4 crossref_primary_10_3390_w16071066 crossref_primary_10_1007_s41885_025_00175_7 crossref_primary_10_1007_s42001_025_00414_7 crossref_primary_10_1038_s44304_025_00104_4 crossref_primary_10_1145_3449042 crossref_primary_10_1016_j_cities_2022_104104 crossref_primary_10_1140_epjp_s13360_024_05142_x crossref_primary_10_1016_j_compenvurbsys_2024_102160 crossref_primary_10_1038_s41467_024_48624_3 crossref_primary_10_1016_j_scs_2024_105863 crossref_primary_10_1038_s41598_020_75033_5 crossref_primary_10_1177_23998083221090246 crossref_primary_10_1016_j_cie_2022_108283 crossref_primary_10_3390_logistics7030058 crossref_primary_10_1017_dap_2024_94 crossref_primary_10_1016_j_ijdrr_2021_102047 crossref_primary_10_5194_nhess_23_317_2023 crossref_primary_10_3390_ijerph22050733 crossref_primary_10_1016_j_ijdrr_2024_104681 crossref_primary_10_1061_NHREFO_NHENG_1930 crossref_primary_10_1016_j_scs_2024_106023 crossref_primary_10_1145_3512998 crossref_primary_10_1057_s41599_021_00824_8 crossref_primary_10_1177_23998083231167433 crossref_primary_10_1057_s41599_023_02312_7 crossref_primary_10_1016_j_ijdrr_2023_104036 crossref_primary_10_1038_s41598_021_81001_4 crossref_primary_10_20965_jdr_2022_p0541 crossref_primary_10_1016_j_ijdrr_2022_103500 crossref_primary_10_26443_seismica_v3i2_1374 crossref_primary_10_1109_ACCESS_2021_3137651 crossref_primary_10_1016_j_trd_2025_104648 crossref_primary_10_1140_epjds_s13688_025_00540_2 crossref_primary_10_1016_j_pdisas_2024_100396 crossref_primary_10_1073_pnas_2111997119 crossref_primary_10_1016_j_ijdrr_2025_105608 crossref_primary_10_1016_j_compenvurbsys_2022_101777 crossref_primary_10_1177_2399808320980744 crossref_primary_10_1016_j_scs_2021_103237 crossref_primary_10_1016_j_gloenvcha_2023_102743 crossref_primary_10_1016_j_ijdrr_2025_105219 crossref_primary_10_1016_j_ijdrr_2024_104625 crossref_primary_10_1038_s41598_024_59814_w crossref_primary_10_1088_2634_4505_ac7251 crossref_primary_10_1186_s40645_023_00569_9 crossref_primary_10_1016_j_ress_2022_108366 crossref_primary_10_1007_s43621_025_01342_2 crossref_primary_10_3390_rs14051269 crossref_primary_10_1016_j_apgeog_2023_102997 crossref_primary_10_1177_23998083221075634 |
| ContentType | Journal Article |
| DBID | NPM 7X8 |
| DOI | 10.1098/rsif.2019.0532 |
| DatabaseName | PubMed MEDLINE - Academic |
| DatabaseTitle | PubMed MEDLINE - Academic |
| DatabaseTitleList | PubMed MEDLINE - Academic |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database |
| DeliveryMethod | no_fulltext_linktorsrc |
| Discipline | Sciences (General) |
| EISSN | 1742-5662 |
| ExternalDocumentID | 32070218 |
| Genre | Research Support, U.S. Gov't, Non-P.H.S Research Support, Non-U.S. Gov't Journal Article |
| GroupedDBID | --- 0R~ 18M 29L 2WC 4.4 53G 5GY 5VS ACGFO ACQIA ACRPL ADBBV ADDVE ADNMO AENEX AFFVI AGPVY AJZGM ALMA_UNASSIGNED_HOLDINGS ALMYZ AOIJS BAWUL BGBPD BTFSW C1A CAG COF CS3 DIK DU5 EBS EJD GX1 H13 HYE HZ~ KQ8 MRS MV1 NPM NSAHA O9- P2P ROL RPM RRY S70 TR2 V1E W8F XSW 7X8 |
| ID | FETCH-LOGICAL-c4152-f5573cd1a57ce0cece7d40f8d0be7f9c701db96c20987dff8a14ead08fe0c3e72 |
| IEDL.DBID | 7X8 |
| ISSN | 1742-5662 |
| IngestDate | Fri Jul 11 09:10:51 EDT 2025 Thu Apr 03 06:58:24 EDT 2025 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 163 |
| Keywords | population recovery human mobility mobile phone data disaster resilience |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c4152-f5573cd1a57ce0cece7d40f8d0be7f9c701db96c20987dff8a14ead08fe0c3e72 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| OpenAccessLink | https://royalsocietypublishing.org/doi/pdf/10.1098/rsif.2019.0532 |
| PMID | 32070218 |
| PQID | 2358587174 |
| PQPubID | 23479 |
| ParticipantIDs | proquest_miscellaneous_2358587174 pubmed_primary_32070218 |
| PublicationCentury | 2000 |
| PublicationDate | 2020-02-01 |
| PublicationDateYYYYMMDD | 2020-02-01 |
| PublicationDate_xml | – month: 02 year: 2020 text: 2020-02-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationPlace | England |
| PublicationPlace_xml | – name: England |
| PublicationTitle | Journal of the Royal Society interface |
| PublicationTitleAlternate | J R Soc Interface |
| PublicationYear | 2020 |
| SSID | ssj0037355 |
| Score | 2.529794 |
| Snippet | Despite the rising importance of enhancing community resilience to disasters, our understandings on when, how and why communities are able to recover from such... |
| SourceID | proquest pubmed |
| SourceType | Aggregation Database Index Database |
| StartPage | 20190532 |
| Title | Understanding post-disaster population recovery patterns |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/32070218 https://www.proquest.com/docview/2358587174 |
| Volume | 17 |
| hasFullText | |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV07T8MwELaAMrAA5VleChIDDKaJ41cmhBAVA1QdKOoWOY4tdUkCLkj8e85uWliQkFgsJYqT6PT5fOezvw-hC1pkxArOMU19I4XGWcwYtpwRLQtATNiM-fIohkM5mWSjdsHNtdsqFz4xOOqy1n6NvO-PdDKI7gW9aV6xV43y1dVWQmMVdVIIZTyqxWRZRUhFGlRPoQ8kXJyTJWmj7EMmHgg8s2svjfB7eBmmmcHWf39wG222AWZ0O0dEF62Yagd12yHsosuWZ_pqF8nxz4MtUVO7GS6nTnnqBLhaCHtFPmcGwH9GTeDirNweGg_un-8ecCukgLWfn7FlTKS6TBQT2sTaaCNKGltZxoURNtMiTsoi45qAZURprVQJBYTF0sLTqRFkH61VdWUOUSRiqgtLEqu0olwRZeAGZxZemFD4Sg-dL6yTA1B99UFVpn53-bd9euhgbuK8mTNq5CkBzwPBxtEfeh-jDeJz3rBz-gR1LAxTc4rW9cds6t7OAgKgHY6evgBmkruu |
| linkProvider | ProQuest |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Understanding+post-disaster+population+recovery+patterns&rft.jtitle=Journal+of+the+Royal+Society+interface&rft.au=Yabe%2C+Takahiro&rft.au=Tsubouchi%2C+Kota&rft.au=Fujiwara%2C+Naoya&rft.au=Sekimoto%2C+Yoshihide&rft.date=2020-02-01&rft.issn=1742-5662&rft.eissn=1742-5662&rft.volume=17&rft.issue=163&rft.spage=20190532&rft_id=info:doi/10.1098%2Frsif.2019.0532&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1742-5662&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1742-5662&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1742-5662&client=summon |