ArticleScientific reports2017
A generalized simulation development approach for predicting refugee destinations.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed, 123 citations in OpenAlex.
- Article
- Article
- Forecasting asylum-related migration flows with machine learning and data at scale.Scientific reports · 2022Article
- The potential of Facebook advertising data for understanding flows of people from Ukraine to the European Union.EPJ data science · 2022Article
- What we do know (and could know) about estimating population sizes of internally displaced people.Journal of migration and health · 2022Article
- Reconstructing subdistrict-level population denominators in Yemen after six years of armed conflict and forced displacement.Journal of migration and health · 2022Article
- How Armed Conflict Influences Migration.Population and development review · 2021Article
- A route pruning algorithm for an automated geographic location graph construction.Scientific reports · 2021Article
- Sensitivity-driven simulation development: a case study in forced migration.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2021Article
- VECMAtk: a scalable verification, validation and uncertainty quantification toolkit for scientific simulations.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2021Article
- When we can trust computers (and when we can't).Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2021Article
- From digital hype to analogue reality: Universal simulation beyond the quantum and exascale eras.Journal of computational science · 2020Article
- A data-driven computational model on the effects of immigration policies.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, global forced displacement has reached record levels, with 22.5 million refugees worldwide. Forecasting refugee movements is important, as accurate predictions can help save refugee lives by allowing governments and NGOs to conduct a better informed allocation of humanitarian resources. Here, we propose a generalized simulation development approach to predict the destinations of refugee movements in conflict regions. In this approach, we synthesize data from UNHCR, ACLED and Bing Maps to construct agent-based simulations of refugee movements. We apply our approach to develop, run and validate refugee movement simulations set in three major African conflicts, estimating the distribution of incoming refugees across destination camps, given the expected total number of refugees in the conflict. Our simulations consistently predict more than 75% of the refugee destinations correctly after the first 12 days, and consistently outperform alternative naive forecasting techniques. Using our approach, we are also able to reproduce key trends in refugee arrival rates found in the UNHCR data.
Indexed as
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.