ArticlePLoS currents2016
Rapid and Near Real-Time Assessments of Population Displacement Using Mobile Phone Data Following Disasters: The 2015 Nepal Earthquake.
Article in PLoS currents, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
43 citing papers in PubMed.
- Access to Essential Services: A Critical Factor for Predicting Recovery and Quantifying Resilience.Risk analysis : an official publication of the Society for Risk Analysis · 2026Article
- Health among sexual and gender minority people affected by armed conflict and forced displacement: Call for a biocultural and minority stress framework.Social science & medicine (1982) · 2026Review
- Dynamic Population Distribution and Perceived Impact Area of the Tibet DingriSensors (Basel, Switzerland) · 2026Article
- Should I stay or should I go? Leveraging data-driven approaches to explore the effect of various disaster policies on postearthquake household relocation decision-making.Risk analysis : an official publication of the Society for Risk Analysis · 2025Article
- Mixing individual and collective behaviors to predict out-of-routine mobility.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Mapping seasonal human mobility across Africa using mobile phone location history and geospatial data.Research square · 2025Article
- Analysis of disaster-affected population mobility through grid-aggregated mobile location data: The 2017 Jiuzhaigou earthquake, China.PloS one · 2025Article
- Crowd-based spatial risk assessment of urban flooding: Results from a municipal flood hotline in Detroit, MI.Journal of flood risk management · 2024Article
- Using mobile phone data to map evacuation and displacement: a case study of the central Italy earthquake.Scientific reports · 2023Article
- Projecting 1 km-grid population distributions from 2020 to 2100 globally under shared socioeconomic pathways.Scientific data · 2022Article
- Application of Mobile Signaling Data in Determining the Seismic Influence Field: A Case Study of the 2017 Mw 6.5 Jiuzhaigou Earthquake, China.International journal of environmental research and public health · 2022Article
- Toward data-driven, dynamical complex systems approaches to disaster resilience.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- An Evaluation of Geo-located Twitter Data for Measuring Human Migration.International journal of geographical information science : IJGIS · 2022Article
- Multi-scale governance and data for sustainable development.Frontiers in big data · 2022Article
- The potential of Facebook advertising data for understanding flows of people from Ukraine to the European Union.EPJ data science · 2022Article
- Food insecurity and compound environmental shocks in Nepal: Implications for a changing climate.World development · 2021Article
- Using big data for evaluating development outcomes: A systematic map.Campbell systematic reviews · 2021Article
- Review
- Perception and Use of Primary Healthcare Services Among People With Cardiometabolic Diseases in Two Resource-Limited Areas in Nepal: A Mixed Methods Study.Frontiers in public health · 2021Article
- A framework for the prediction of earthquake using federated learning.PeerJ. Computer science · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
Abstract
introductionSudden impact disasters often result in the displacement of large numbers of people. These movements can occur prior to events, due to early warning messages, or take place post-event due to damages to shelters and livelihoods as well as a result of long-term reconstruction efforts. Displaced populations are especially vulnerable and often in need of support. However, timely and accurate data on the numbers and destinations of displaced populations are extremely challenging to collect across temporal and spatial scales, especially in the aftermath of disasters. Mobile phone call detail records were shown to be a valid data source for estimates of population movements after the 2010 Haiti earthquake, but their potential to provide near real-time ongoing measurements of population displacements immediately after a natural disaster has not been demonstrated.
methodsA computational architecture and analytical capacity were rapidly deployed within nine days of the Nepal earthquake of 25th April 2015, to provide spatiotemporally detailed estimates of population displacements from call detail records based on movements of 12 million de-identified mobile phones users.
resultsAnalysis shows the evolution of population mobility patterns after the earthquake and the patterns of return to affected areas, at a high level of detail. Particularly notable is the movement of an estimated 390,000 people above normal from the Kathmandu valley after the earthquake, with most people moving to surrounding areas and the highly-populated areas in the central southern area of Nepal. DISCUSSION: This analysis provides an unprecedented level of information about human movement after a natural disaster, provided within a very short timeframe after the earthquake occurred. The patterns revealed using this method are almost impossible to find through other methods, and are of great interest to humanitarian agencies.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.