Network diffusion model reveals recovery multipliers and heterogeneous spatial effects in post-disaster community recovery
Abstract Community recovery from hazards 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, we created a network diff...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-11-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-46096-x |
| _version_ | 1797636929987018752 |
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| author | Chia-Fu Liu Ali Mostafavi |
| author_facet | Chia-Fu Liu Ali Mostafavi |
| author_sort | Chia-Fu Liu |
| collection | DOAJ |
| description | Abstract Community recovery from hazards 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, we created a network diffusion model to characterize the unfolding of population activity recovery in spatial networks of communities. In particular, this study aims to answer the research question “To what extent can the diffusion model capture the spatial patterns of recovery?” Using population activity recovery data derived from location-based information associated with 2017 Hurricane Harvey in the Houston area, we parameterized the threshold-based network diffusion model using the genetic algorithm and then simulated the recovery diffusion process. The results show that the spatial effects of recovery are rather heterogeneous across different areas; some spatial areas demonstrate a greater spatial effect in their recovery. Also, the results show that low-income and minority areas are community recovery multipliers; with faster recovery in these areas corresponding to accelerated recovery for the entire community. Hence, prioritizing these areas in resource allocation during recovery has the potential to accelerate could expedite the recovery of the entire community’s recovery process while promoting recovery equality and equity. |
| first_indexed | 2024-03-11T12:42:12Z |
| format | Article |
| id | doaj.art-db1d24d7be9f47a8a32cef0b08699180 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-11T12:42:12Z |
| publishDate | 2023-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-db1d24d7be9f47a8a32cef0b086991802023-11-05T12:16:12ZengNature PortfolioScientific Reports2045-23222023-11-0113111310.1038/s41598-023-46096-xNetwork diffusion model reveals recovery multipliers and heterogeneous spatial effects in post-disaster community recoveryChia-Fu Liu0Ali Mostafavi1Zachry Department of Civil and Environmental Engineering, Texas A&M UniversityZachry Department of Civil and Environmental Engineering, Texas A&M UniversityAbstract Community recovery from hazards 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, we created a network diffusion model to characterize the unfolding of population activity recovery in spatial networks of communities. In particular, this study aims to answer the research question “To what extent can the diffusion model capture the spatial patterns of recovery?” Using population activity recovery data derived from location-based information associated with 2017 Hurricane Harvey in the Houston area, we parameterized the threshold-based network diffusion model using the genetic algorithm and then simulated the recovery diffusion process. The results show that the spatial effects of recovery are rather heterogeneous across different areas; some spatial areas demonstrate a greater spatial effect in their recovery. Also, the results show that low-income and minority areas are community recovery multipliers; with faster recovery in these areas corresponding to accelerated recovery for the entire community. Hence, prioritizing these areas in resource allocation during recovery has the potential to accelerate could expedite the recovery of the entire community’s recovery process while promoting recovery equality and equity.https://doi.org/10.1038/s41598-023-46096-x |
| spellingShingle | Chia-Fu Liu Ali Mostafavi Network diffusion model reveals recovery multipliers and heterogeneous spatial effects in post-disaster community recovery Scientific Reports |
| title | Network diffusion model reveals recovery multipliers and heterogeneous spatial effects in post-disaster community recovery |
| title_full | Network diffusion model reveals recovery multipliers and heterogeneous spatial effects in post-disaster community recovery |
| title_fullStr | Network diffusion model reveals recovery multipliers and heterogeneous spatial effects in post-disaster community recovery |
| title_full_unstemmed | Network diffusion model reveals recovery multipliers and heterogeneous spatial effects in post-disaster community recovery |
| title_short | Network diffusion model reveals recovery multipliers and heterogeneous spatial effects in post-disaster community recovery |
| title_sort | network diffusion model reveals recovery multipliers and heterogeneous spatial effects in post disaster community recovery |
| url | https://doi.org/10.1038/s41598-023-46096-x |
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