Population displacement after earthquakes: benchmarking predictions based on housing damage
DOI:
https://doi.org/10.26443/seismica.v3i2.1374Keywords:
population displacement, earthquake risk, housing damage, scenario modelsAbstract
In the aftermath of an earthquake, the number of residents whose housing was destroyed is often used to approximate the number of people displaced (i.e., rendered homeless) after the event. While this metric can provide rapid situational awareness regarding potential long-term housing needs, more recent research highlights the importance of additional factors beyond housing damage within the scope of household displacement and return (e.g., utility disruption, tenure, place attachment). This study benchmarks population displacement estimates using this simplified conventional approach (i.e., only considering housing destruction) through three scenario models for recent earthquakes in Haiti, Japan, and Nepal. These model predictions are compared with officially reported values and alternate mobile location data-based estimates from the literature. The results highlight the promise of scenario models to realistically estimate population displacement and potential long-term housing needs after earthquakes, but also highlight a large range of uncertainty in the predicted values. Furthermore, purely basing displacement estimates on housing damage offers no view on how the displaced population counts vary with time as compared to more comprehensive models that include other factors influencing population return or alternative approaches, such as using mobile location data.
References
Akkar, S., Sandıkkaya, M. A., & Bommer, J. J. (2014). Empirical ground-motion models for point-and extended-source crustal earthquake scenarios in Europe and the Middle East. Bulletin of Earthquake Engineering, 12, 359–387. DOI: https://doi.org/10.1007/s10518-013-9461-4
Atkinson, G. M., & Boore, D. M. (2003). Empirical ground-motion relations for subduction-zone earthquakes and their application to Cascadia and other regions. Bulletin of the Seismological Society of America, 93(4), 1703–1729. DOI: https://doi.org/10.1785/0120020156
Beguería, S. (2006). Validation and Evaluation of Predictive Models in Hazard Assessment and Risk Management. Natural Hazards, 37(3), 315–329. https://doi.org/10.1007/s11069-005-5182-6 DOI: https://doi.org/10.1007/s11069-005-5182-6
Bengtsson, L., Lu, X., Thorson, A., Garfield, R., & Schreeb, J. von. (2011). Improved Response to Disasters and Outbreaks by Tracking Population Movements with Mobile Phone Network Data: A Post-Earthquake Geospatial Study in Haiti. PLOS Medicine, 8(8), e1001083. https://doi.org/10.1371/journal.pmed.1001083 DOI: https://doi.org/10.1371/journal.pmed.1001083
Bhattacharya, Y., & Kato, T. (2021). Development of an Agent-Based Model on the Decision-Making of Dislocated People After Disasters. In S. C. M. Geertman, C. Pettit, R. Goodspeed, & A. Staffans (Eds.), Urban Informatics and Future Cities (pp. 387–406). Springer International Publishing. https://doi.org/10.1007/978-3-030-76059-5_20 DOI: https://doi.org/10.1007/978-3-030-76059-5_20
Bhattarai, M., Adhikari, L. B., Gautam, U. P., Laurendeau, A., Labonne, C., Hoste-Colomer, R., Sèbe, O., & Hernandez, B. (2015). Overview of the large 25 April 2015 Gorkha, Nepal, earthquake from accelerometric perspectives. Seismological Research Letters, 86(6), 1540–1548. DOI: https://doi.org/10.1785/0220150140
Binder, S. B., Baker, C. K., & Barile, J. P. (2015). Rebuild or Relocate? Resilience and Postdisaster Decision-Making After Hurricane Sandy. American Journal of Community Psychology, 56(1), 180–196. https://doi.org/10.1007/s10464-015-9727-x DOI: https://doi.org/10.1007/s10464-015-9727-x
Blumenstock, J., & Eagle, N. (2010). Mobile divides: gender, socioeconomic status, and mobile phone use in Rwanda. Proceedings of the 4th ACM/IEEE International Conference on Information and Communication Technologies and Development, 1–10. https://doi.org/10.1145/2369220.2369225 DOI: https://doi.org/10.1145/2369220.2369225
Burton, H., Kang, H., Miles, S., Nejat, A., & Yi, Z. (2019). A framework and case study for integrating household decision-making into post-earthquake recovery models. International Journal of Disaster Risk Reduction, 37, 101167. DOI: https://doi.org/10.1016/j.ijdrr.2019.101167
CDEMA. (2021). Haiti Earthquake: Final Situation Report #12 [Techreport]. https://www.cdema.org/images/2021/09/FINAL_CDEMA_Situation_Report_12_Haiti_Earthquake_14Sep2021.pdf
Chadha, R. K., Srinagesh, D., Srinivas, D., Suresh, G., Sateesh, A., Singh, S. K., Pérez‐Campos, X., Suresh, G., Koketsu, K., Masuda, T., Domen, K., & Ito, T. (2015). CIGN, A Strong‐Motion Seismic Network in Central Indo‐Gangetic Plains, Foothills of Himalayas: First Results. Seismological Research Letters, 87(1), 37–46. https://doi.org/10.1785/0220150106 DOI: https://doi.org/10.1785/0220150106
Chiou, B. S.-J., & Youngs, R. R. (2014). Update of the Chiou and Youngs NGA model for the average horizontal component of peak ground motion and response spectra. Earthquake Spectra, 30(3), 1117–1153. DOI: https://doi.org/10.1193/072813EQS219M
Cong, Z., Nejat, A., Liang, D., Pei, Y., & Javid, R. J. (2018). Individual relocation decisions after tornadoes: a multi-level analysis. Disasters, 42(2), 233–250. https://doi.org/10.1111/disa.12241 DOI: https://doi.org/10.1111/disa.12241
Costa, R., Haukaas, T., & Chang, S. E. (2022). Predicting population displacements after earthquakes. Sustainable and Resilient Infrastructure, 7(4), 253–271. https://doi.org/10.1080/23789689.2020.1746047 DOI: https://doi.org/10.1080/23789689.2020.1746047
Cremen, G., Galasso, C., & McCloskey, J. (2022). A Simulation‐Based Framework for Earthquake Risk‐Informed and People‐Centered Decision Making on Future Urban Planning. Earth’s Future, 10(1), e2021EF002388. https://doi.org/10.1029/2021EF002388 DOI: https://doi.org/10.1029/2021EF002388
Crowley, H., Silva, V., Kalakonas, P., Martins, L., Weatherill, G., Pitilakis, K., Riga, E., Borzi, B., & Faravelli, M. (2020). Verification of the European seismic risk model (ESRM20). Proceedings of the 17th World Conference on Earthquake Engineering, Sendai, Japan, 27. https://wcee.nicee.org/wcee/article/17WCEE/8b-0045.pdf
DeWaard, J., Johnson, J. E., & Whitaker, S. D. (2020). Out-migration from and return migration to Puerto Rico after Hurricane Maria: evidence from the consumer credit panel. Population and Environment, 42(1), 28–42. https://doi.org/10.1007/s11111-020-00339-5 DOI: https://doi.org/10.1007/s11111-020-00339-5
DeWaard, J., Johnson, J., & Whitaker, S. (2019). Internal migration in the United States: A comprehensive comparative assessment of the Consumer Credit Panel. Demographic Research, 41, 953–1006. https://doi.org/10.4054/DemRes.2019.41.33 DOI: https://doi.org/10.4054/DemRes.2019.41.33
Elliott, J. R., & Pais, J. (2006). Race, class, and Hurricane Katrina: Social differences in human responses to disaster. Social Science Research, 35(2), 295–321. https://doi.org/10.1016/j.ssresearch.2006.02.003 DOI: https://doi.org/10.1016/j.ssresearch.2006.02.003
Engler, D. T., Worden, C. B., Thompson, E. M., & Jaiswal, K. S. (2022). Partitioning Ground Motion Uncertainty When Conditioned on Station Data. Bulletin of the Seismological Society of America, 112(2), 1060–1079. https://doi.org/10.1785/0120210177 DOI: https://doi.org/10.1785/0120210177
Esnard, A.-M., & Sapat, A. (2014). Displaced by Disaster: Recovery and Resilience in a Globalizing World. Routledge. https://doi.org/10.4324/9780203728291 DOI: https://doi.org/10.4324/9780203728291
FlowMinder. (2021). Haiti: Earthquake on 14 August 2021 (Version 1.2) [Techreport]. https://www.flowminder.org/media/dpxfefl4/haitiearthquake_report_27-aug_report-2_eng_v1-2_final.pdf
Frias-Martinez, V., & Virseda, J. (2012). On the relationship between socio-economic factors and cell phone usage. Proceedings of the Fifth International Conference on Information and Communication Technologies and Development, 76–84. https://doi.org/10.1145/2160673.2160684 DOI: https://doi.org/10.1145/2160673.2160684
Greer, A. (2015). Household residential decision-making in the wake of disaster: cases from Hurricane Sandy [Phdthesis, University of Delaware]. https://udspace.udel.edu/handle/19716/31364
Grinberger, A. Y., & Felsenstein, D. (2016). Dynamic agent based simulation of welfare effects of urban disasters. Computers, Environment and Urban Systems, 59, 129–141. https://doi.org/10.1016/j.compenvurbsys.2016.06.005 DOI: https://doi.org/10.1016/j.compenvurbsys.2016.06.005
Groen, J. A., & Polivka, A. E. (2010). Going home after Hurricane Katrina: Determinants of return migration and changes in affected areas. Demography, 47(4), 821–844. DOI: https://doi.org/10.1007/BF03214587
Grünthal, G. (1998). European macroseismic scale 1998 (EMS-98). https://gfzpublic.gfz-potsdam.de/rest/items/item_227033_2/component/file_227032/content
Guadagno, L., & Yonetani, M. (2023). Displacement risk: Unpacking a problematic concept for disaster risk reduction. International Migration, 61(5), 13–28. https://doi.org/10.1111/imig.13004 DOI: https://doi.org/10.1111/imig.13004
Hallegatte, S., Vogt-Schilb, A., Rozenberg, J., Bangalore, M., & Beaudet, C. (2020). From Poverty to Disaster and Back: a Review of the Literature. Economics of Disasters and Climate Change, 4(1), 223–247. https://doi.org/10.1007/s41885-020-00060-5 DOI: https://doi.org/10.1007/s41885-020-00060-5
Hayes, G. P., Briggs, R. W., Barnhart, W. D., Yeck, W. L., McNamara, D. E., Wald, D. J., Nealy, J. L., Benz, H. M., Gold, R. D., & Jaiswal, K. S. (2015). Rapid characterization of the 2015 M w 7.8 Gorkha, Nepal, earthquake sequence and its seismotectonic context. Seismological Research Letters, 86(6), 1557–1567. DOI: https://doi.org/10.1785/0220150145
Heath, D. C., Wald, D. J., Worden, C. B., Thompson, E. M., & Smoczyk, G. M. (2020). A global hybrid VS 30 map with a topographic slope–based default and regional map insets. Earthquake Spectra, 36(3), 1570–1584. DOI: https://doi.org/10.1177/8755293020911137
Hinojosa, J. (2018). Two Sides of the Coin of Puerto Rican Migration: Depopulation in Puerto Rico and the Redefinition of the Diaspora. Centro Journal, 30(3). https://www.academia.edu/download/59765896/J.HINOJOSA_CENTROJOURNAL-FALL2018.pdf
Hinojosa, J., & Meléndez, E. (2018). Puerto Rican Exodus: One Year Since Hurricane Maria (Techreport Centro RB2018-05). Centro Library.
Hough, S. E., Martin, S. S., Gahalaut, V., Joshi, A., Landes, M., & Bossu, R. (2016). A comparison of observed and predicted ground motions from the 2015 MW7.8 Gorkha, Nepal, earthquake. Natural Hazards, 84(3), 1661–1684. https://doi.org/10.1007/s11069-016-2505-8 DOI: https://doi.org/10.1007/s11069-016-2505-8
Hoyos, M. C., & Silva, V. (2022). Exploring benefit cost analysis to support earthquake risk mitigation in Central America. International Journal of Disaster Risk Reduction, 80, 103162. https://doi.org/https://doi.org/10.1016/j.ijdrr.2022.103162 DOI: https://doi.org/10.1016/j.ijdrr.2022.103162
ICIMOD. (2015). Lessons from Nepal’s Gorkha earthquake 2015 [Techreport].
IDMC. (n.d.). Global Internal Displacement Database. Retrieved April 27, 2023, from https://www.internal-displacement.org/database
IDMC. (2018). GRID Methodological Annex [Techreport]. https://www.internal-displacement.org/global-report/grid2018/downloads/report/2018-GRID-methodological-annex.pdf
IDMC. (2019). Disaster Displacement - A global review, 2008-2018 [Techreport]. https://www.internal-displacement.org/publications/disaster-displacement-a-global-review
IDMC. (2020). GRID Methodology [Techreport]. https://www.internal-displacement.org/global-report/grid2020/downloads/2020-IDMC-GRID-methodology.pdf
IDMC. (2022a). Urban case study: Ba Town, Fiji [Techreport]. https://www.internal-displacement.org/publications/pacific-response-to-disaster-displacement-urban-case-study-ba-town-fiji/
IDMC. (2022b). Urban case study: Port Vila, Vanuatu [Techreport]. https://www.internal-displacement.org/publications/pacific-response-to-disaster-displacement-urban-case-study-port-vila-vanuatu/
JCO. (2017). Disaster Report for 2016 Kumamoto earthquake [Techreport]. https://www.bousai.go.jp/updates/h280414jishin/pdf/h280414jishin_39.pdf
Kalakonas, P., Silva, V., Mouyiannou, A., & Rao, A. (2020). Exploring the impact of epistemic uncertainty on a regional probabilistic seismic risk assessment model. Natural Hazards, 104(1), 997–1020. https://doi.org/https://doi.org/10.1007/s11069-020-04201-7 DOI: https://doi.org/10.1007/s11069-020-04201-7
Kolbe, A. R., Hutson, R. A., Shannon, H., Trzcinski, E., Miles, B., Levitz, N., Puccio, M., James, L., Noel, J. R., & Muggah, R. (2010). Mortality, crime and access to basic needs before and after the Haiti earthquake: a random survey of Port-au-Prince households. Medicine, Conflict and Survival, 26(4), 281–297. https://doi.org/10.1080/13623699.2010.535279 DOI: https://doi.org/10.1080/13623699.2010.535279
Lee, C.-C., Chou, C., & Mostafavi, A. (2022). Specifying Evacuation Return and Home-switch Stability During Short-term Disaster Recovery Using Location-based Data. Scientific Reports, 12(1), 15987. https://doi.org/10.1038/s41598-022-20384-4 DOI: https://doi.org/10.1038/s41598-022-20384-4
Lee, Y.-J., Sugiura, H., & Gečienė, I. (2017). Stay or Relocate: The Roles of Networks After the Great East Japan Earthquake. In E. C. Jones & A. J. Faas (Eds.), Social Network Analysis of Disaster Response, Recovery, and Adaptation (pp. 223–238). Butterworth-Heinemann. https://doi.org/10.1016/B978-0-12-805196-2.00015-7 DOI: https://doi.org/10.1016/B978-0-12-805196-2.00015-7
Liel, A. B., & Deierlein, G. G. (2013). Cost-Benefit Evaluation of Seismic Risk Mitigation Alternatives for Older Concrete Frame Buildings. Earthquake Spectra, 29(4), 1391–1411. https://doi.org/10.1193/030911EQS040M DOI: https://doi.org/10.1193/030911EQS040M
Lin, Y.-S. (2009). Development of algorithms to estimate post-disaster population dislocation—a research-based approach. Texas A&M University.
Lines, R., Faure Walker, J. P., & Yore, R. (2022). Progression through emergency and temporary shelter, transitional housing and permanent housing: A longitudinal case study from the 2018 Lombok earthquake, Indonesia. International Journal of Disaster Risk Reduction, 75, 102959. https://doi.org/10.1016/j.ijdrr.2022.102959 DOI: https://doi.org/10.1016/j.ijdrr.2022.102959
Loos, S., Lallemant, D., Baker, J., McCaughey, J., Yun, S.-H., Budhathoki, N., Khan, F., & Singh, R. (2020). G-DIF: A geospatial data integration framework to rapidly estimate post-earthquake damage. Earthquake Spectra, 36(4), 1695–1718. https://doi.org/10.1177/8755293020926190 DOI: https://doi.org/10.1177/8755293020926190
Loos, S., Lallemant, D., Khan, F., McCaughey, J. W., Banick, R., Budhathoki, N., & Baker, J. W. (2023). A data-driven approach to rapidly estimate recovery potential to go beyond building damage after disasters. Communications Earth & Environment, 4(1), 1–12. https://doi.org/10.1038/s43247-023-00699-4 DOI: https://doi.org/10.1038/s43247-023-00699-4
Love, T. (2011). Population movement after natural disasters: a literature review and assessment of Christchurch data (p. 26) [Techreport]. Sapere Research Group.
Lu, X., Bengtsson, L., & Holme, P. (2012). Predictability of population displacement after the 2010 Haiti earthquake. Proceedings of the National Academy of Sciences, 109(29), 11576–11581. https://doi.org/10.1073/pnas.1203882109 DOI: https://doi.org/10.1073/pnas.1203882109
Martins, L., & Silva, V. (2021). Development of a fragility and vulnerability model for global seismic risk analyses. Bulletin of Earthquake Engineering, 19(15), 6719–6745. https://doi.org/10.1007/s10518-020-00885-1 DOI: https://doi.org/10.1007/s10518-020-00885-1
Mayer, J., Moradi, S., Nejat, A., Ghosh, S., Cong, Z., & Liang, D. (2020). Drivers of post-disaster relocations: The case of Moore and Hattiesburg tornados. International Journal of Disaster Risk Reduction, 49, 101643. https://doi.org/10.1016/j.ijdrr.2020.101643 DOI: https://doi.org/10.1016/j.ijdrr.2020.101643
McAdam, J. (2022). Evacuations: a form of disaster displacement? Forced Migration Review, 69, 56–57. https://www.proquest.com/docview/2647725690/abstract/DB0755D2F79B4311PQ/1
Milusheva, S., Bjorkegren, D., & Viotti, L. (2021). Assessing Bias in Smartphone Mobility Estimates in Low Income Countries. ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS), 364–378. https://doi.org/10.1145/3460112.3471968 DOI: https://doi.org/10.1145/3460112.3471968
Nawrotzki, R. J., Brenkert-Smith, H., Hunter, L. M., & Champ, P. A. (2014). Wildfire-Migration Dynamics: Lessons from Colorado’s Fourmile Canyon Fire. Society & Natural Resources, 27(2), 215–225. https://doi.org/10.1080/08941920.2013.842275 DOI: https://doi.org/10.1080/08941920.2013.842275
Nejat, A., & Ghosh, S. (2016). LASSO Model of Postdisaster Housing Recovery: Case Study of Hurricane Sandy. Natural Hazards Review, 17(3), 4016007. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000223 DOI: https://doi.org/10.1061/(ASCE)NH.1527-6996.0000223
Newell, J., Beaven, S., & Johnston, D. M. (2012). Population movements following the 2010-2011 Canterbury Earthquakes: Summary of research workshops November 2011 and current evidence [Techreport].
Newzoo. (2017). Global Mobile Market Report 2017 [Techreport]. https://newzoo.com/resources/trend-reports/global-mobile-market-report-light-2017
Paul, N., Galasso, C., & Baker, J. (2024). Household Displacement and Return in Disasters: A Review. Natural Hazards Review, 25(1), 3123006. https://doi.org/10.1061/NHREFO.NHENG-1930 DOI: https://doi.org/10.1061/NHREFO.NHENG-1930
Plyer, A., Bonaguro, J., & Hodges, K. (2010). Using administrative data to estimate population displacement and resettlement following a catastrophic U.S. disaster. Population and Environment, 31(1), 150–175. https://doi.org/10.1007/s11111-009-0091-3 DOI: https://doi.org/10.1007/s11111-009-0091-3
Price, D. (2011). Population and household trends in Christchurch post February 22 earthquake. Population and Employment Effects of the Christchurch Earthquakes Workshop.
Quarantelli, E. L. (1982). General and particular observations on sheltering and housing in American disasters. Disasters, 6(4), 277–281. https://doi.org/10.1111/j.1467-7717.1982.tb00550.x DOI: https://doi.org/10.1111/j.1467-7717.1982.tb00550.x
Quarantelli, E. L. (1995). Patterns of sheltering and housing in US disasters. Disaster Prevention and Management: An International Journal, 4(3), 43–53. https://doi.org/10.1108/09653569510088069 DOI: https://doi.org/10.1108/09653569510088069
Rajaure, S., Asimaki, D., Thompson, E. M., Hough, S., Martin, S., Ampuero, J. P., Dhital, M. R., Inbal, A., Takai, N., Shigefuji, M., Bijukchhen, S., Ichiyanagi, M., Sasatani, T., & Paudel, L. (2017). Characterizing the Kathmandu Valley sediment response through strong motion recordings of the 2015 Gorkha earthquake sequence. Tectonophysics, 714–715, 146–157. https://doi.org/10.1016/j.tecto.2016.09.030 DOI: https://doi.org/10.1016/j.tecto.2016.09.030
Sharygin, E. (2021). Estimating Migration Impacts of Wildfire: California’s 2017 North Bay Fires. In D. Karácsonyi, A. Taylor, & D. Bird (Eds.), The Demography of Disasters: Impacts for Population and Place (pp. 49–70). Springer International Publishing. https://doi.org/10.1007/978-3-030-49920-4_3 DOI: https://doi.org/10.1007/978-3-030-49920-4_3
Silva, V. (2016). Critical Issues in Earthquake Scenario Loss Modeling. Journal of Earthquake Engineering, 20(8), 1322–1341. https://doi.org/10.1080/13632469.2016.1138172 DOI: https://doi.org/10.1080/13632469.2016.1138172
Silva, V. (2018). Critical Issues on Probabilistic Earthquake Loss Assessment. Journal of Earthquake Engineering, 22(9), 1683–1709. https://doi.org/10.1080/13632469.2017.1297264 DOI: https://doi.org/10.1080/13632469.2017.1297264
Silva, V., Amo-Oduro, D., Calderon, A., Costa, C., Dabbeek, J., Despotaki, V., Martins, L., Pagani, M., Rao, A., & Simionato, M. (2020). Development of a global seismic risk model. Earthquake Spectra, 36(1_suppl), 372–394. DOI: https://doi.org/10.1177/8755293019899953
Silva, V., Crowley, H., Pagani, M., Monelli, D., & Pinho, R. (2014). Development of the OpenQuake engine, the Global Earthquake Model’s open-source software for seismic risk assessment. Natural Hazards, 72, 1409–1427. DOI: https://doi.org/10.1007/s11069-013-0618-x
Silva, V., & Horspool, N. (2019). Combining USGS ShakeMaps and the OpenQuake-engine for damage and loss assessment. Earthquake Engineering & Structural Dynamics, 48(6), 634–652. https://doi.org/10.1002/eqe.3154 DOI: https://doi.org/10.1002/eqe.3154
The Asia Foundation. (2019). Independent Impacts and Recovery Monitoring Phase Five [Techreport]. The Asia Foundation. https://asiafoundation.org/wp-content/uploads/2021/03/IRM-Nepal_Aid-and-Recovery-in-Post-Earthquake-Nepal-Qualititative-Field-MonitoringNovember-2019_EN.pdf
Van De Lindt, J. W., Peacock, W. G., Mitrani-Reiser, J., Rosenheim, N., Deniz, D., Dillard, M., Tomiczek, T., Koliou, M., Graettinger, A., Crawford, P. S., Harrison, K., Barbosa, A., Tobin, J., Helgeson, J., Peek, L., Memari, M., Sutley, E. J., Hamideh, S., Gu, D., … Fung, J. (2020). Community Resilience-Focused Technical Investigation of the 2016 Lumberton, North Carolina, Flood: An Interdisciplinary Approach. Natural Hazards Review, 21(3), 4020029. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000387 DOI: https://doi.org/10.1061/(ASCE)NH.1527-6996.0000387
Ward, P. J., Blauhut, V., Bloemendaal, N., Daniell, J. E., de Ruiter, M. C., Duncan, M. J., Emberson, R., Jenkins, S. F., Kirschbaum, D., Kunz, M., Mohr, S., Muis, S., Riddell, G. A., Schäfer, A., Stanley, T., Veldkamp, T. I. E., & Winsemius, H. C. (2020). Review article: Natural hazard risk assessments at the global scale. Natural Hazards and Earth System Sciences, 20(4), 1069–1096. https://doi.org/10.5194/nhess-20-1069-2020 DOI: https://doi.org/10.5194/nhess-20-1069-2020
Wesolowski, A., Eagle, N., Noor, A. M., Snow, R. W., & Buckee, C. O. (2012). Heterogeneous Mobile Phone Ownership and Usage Patterns in Kenya. PLoS ONE, 7(4), e35319. https://doi.org/10.1371/journal.pone.0035319 DOI: https://doi.org/10.1371/journal.pone.0035319
Wesolowski, A., Eagle, N., Noor, A. M., Snow, R. W., & Buckee, C. O. (2013). The impact of biases in mobile phone ownership on estimates of human mobility. Journal of The Royal Society Interface, 10(81), 20120986. https://doi.org/10.1098/rsif.2012.0986 DOI: https://doi.org/10.1098/rsif.2012.0986
Wilson, R., zu Erbach-Schoenberg, E., Albert, M., Power, D., Tudge, S., Gonzalez, M., Guthrie, S., Chamberlain, H., Brooks, C., Hughes, C., Pitonakova, L., Buckee, C., Lu, X., Wetter, E., Tatem, A., & Bengtsson, L. (2016). Rapid and Near Real-Time Assessments of Population Displacement Using Mobile Phone Data Following Disasters: The 2015 Nepal Earthquake. PLoS Currents, 8, ecurrents.dis.d073fbece328e4c39087bc086d694b5c. https://doi.org/10.1371/currents.dis.d073fbece328e4c39087bc086d694b5c DOI: https://doi.org/10.1371/currents.dis.d073fbece328e4c39087bc086d694b5c
World Bank Group. (2021). Mobile cellular subscriptions (per 100 people). World Bank Open Data. https://data.worldbank.org
Yabe, T., Jones, N. K. W., Lozano-Gracia, N., Khan, M. F., Ukkusuri, S. V., Fraiberger, S., & Montfort, A. (2021). Location Data Reveals Disproportionate Disaster Impact Amongst the Poor: A Case Study of the 2017 Puebla Earthquake Using Mobilkit. arXiv. https://doi.org/10.48550/arXiv.2107.13590
Yabe, T., Jones, N. K. W., Rao, P. S. C., Gonzalez, M. C., & Ukkusuri, S. V. (2022). Mobile phone location data for disasters: A review from natural hazards and epidemics. Computers, Environment and Urban Systems, 94, 101777. https://doi.org/10.1016/j.compenvurbsys.2022.101777 DOI: https://doi.org/10.1016/j.compenvurbsys.2022.101777
Yabe, T., Sekimoto, Y., Tsubouchi, K., & Ikemoto, S. (2019). Cross-comparative analysis of evacuation behavior after earthquakes using mobile phone data. PLOS ONE, 14(2), e0211375. https://doi.org/10.1371/journal.pone.0211375 DOI: https://doi.org/10.1371/journal.pone.0211375
Yabe, T., Tsubouchi, K., Fujiwara, N., Sekimoto, Y., & Ukkusuri, S. V. (2020). Understanding post-disaster population recovery patterns. Journal of The Royal Society Interface, 17(163), 20190532. https://doi.org/10.1098/rsif.2019.0532 DOI: https://doi.org/10.1098/rsif.2019.0532
Yepes-Estrada, C., Calderon, A., Costa, C., Crowley, H., Dabbeek, J., Hoyos, M. C., Martins, L., Paul, N., Rao, A., & Silva, V. (2023). Global building exposure model for earthquake risk assessment. Earthquake Spectra, 39(4), 2212–2235. https://doi.org/10.1177/87552930231194048 DOI: https://doi.org/10.1177/87552930231194048
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Copyright (c) 2024 Nicole Paul, Carmine Galasso, Vitor Silva, Jack Baker
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