Modelling forced migration: A framework for conflict-induced forced migration modelling according to an agent-based approach

Searle, Christa; Vuuren, Jan H. van

doi:10.1016/j.compenvurbsys.2020.101568

Cited by 12 publications

(4 citation statements)

References 12 publications

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“…There are already several examples of ABM providing insight into potential migration pathways (Hébert et al., 2018; Suleimenova et al., 2017; Speelman et al., 2021). The use of autonomous agents within the simulation allows the incorporation of different demographics, influences and drivers, all of which can combine to provide a more reflective image of the potential post‐disaster response (Searle et al., 2021). By allowing a heterogeneous mix of agents to act and interact autonomously, it is also more likely that any emergent properties of the system will be observed.…”

Section: Modelling the Ccm Nexusmentioning

confidence: 99%

The climate change, conflict and migration nexus: A holistic view

2023

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Current discourse relating to climate change, conflict, migration (CCM), and the causal links thereof, is polarized. It is widely acknowledged that climate change will have a detrimental effect on quality of life, and that this impact will not be homogeneous across the globe. However, proposed causal links among CCM remain contentious. This paper argues that to better grasp the implications of climate change on global society and security, it is vital to develop a more systemic understanding of the interplay among CCM. Although this nexus is already recognized, studies to date have tended to be qualitative and statistical evidence of multivariate causality has been lacking, where quantitative analysis is present, it has typically been limited to two components at a time; few studies have addressed the nexus holistically, making research conclusions sometimes difficult to reconcile. Hence, by reviewing literature from a broad range of sources, this paper suggests a suite of systemic and quantitative approaches with which to address the CCM nexus. This review critically assesses the existing research approaches employed across a range of examples and suggests how leveraging the power of 'big data' and modelling the nexus as a complex system encapsulating both human and environmental drivers could offer new insights, especially for those looking to explore the increasing number of 'what if' scenarios relating to climate and human dynamics.

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Section: Modelling the Ccm Nexusmentioning

confidence: 99%

The climate change, conflict and migration nexus: A holistic view

2023

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“…In fact, it has been increasingly used in forecasting numbers of people who may want to move along with their potential destination, as has been conducted in a World Bank report exploring potential future climate migration (Rigaud et al, 2018). Finally, the literature has identified how agent-based modelling approaches in combination with machine learning are promising to provide predictions based on indicators or decisions to migrate at the individual or household level (corresponding to micro-level theories of migration; Searle & van Vuuren, 2021). These agent-based models are often used to explain migration, rather than predict (Klabunde & Willekens, 2016).…”

Section: Best Suited Model(s)mentioning

confidence: 99%

The Role of Emerging Predictive IT Tools in Effective Migration Governance

Casagran

Boland

Sánchez-Montijano

et al. 2021

PaG

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Predicting mass migration is one of the main challenges for policymakers and NGOs working with migrants worldwide. Recently there has been a considerable increase in the use of computational techniques to predict migration flows, and advances have allowed for application of improved algorithms in the field. However, given the rapid pace of technological development facilitating these new predictive tools and methods for migration, it is important to address the extent to which such instruments and techniques engage with and impact migration governance. This study provides an in-depth examination of selected existing predictive tools in the migration field and their impact on the governance of migratory flows. It focuses on a comparative qualitative examination of these tools’ scope, as well as how these characteristics link to their respective underlying migration theory, research question, or objective. It overviews how several organisations have developed tools to predict short- or longer-term migration patterns, or to assess and estimate migration uncertainties. At the same time, it demonstrates how and why these instruments continue to face limitations that in turn affect migration management, especially as it relates to increasing EU institutional and stakeholder efforts to forecast or predict mixed migration. The main predictive migration tools in use today cover different scopes and uses, and as such are equally valid in shaping the requirements for a future, fully comprehensive predictive migration tool. This article provides clarity on the requirements and features for such a tool and draws conclusions as to the risks and opportunities any such tool could present for the future of EU migration governance.

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“…And, if we take a step back, we realize that prior to understanding the choice of destination, we need to understand which individuals among the population in the affected region undergo forced migration. Moreover, these studies are country-specific (Asgary, Solis et al 2016;Davis, Bhattachan et al 2018;Searle and van Vuuren 2021;Smith 2014). To the best of our knowledge, there is no existing work that attempts to explain conflictinduced migration outflows from a social-theoretic standpoint.…”

Section: Introductionmentioning

confidence: 99%

A Generalizable Theory-Driven Agent-Based Framework to Study Conflict-Induced Forced Migration

Mehrab,

Stundal,

Venkatramanan

et al. 2024

AAAI

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Large-scale population displacements arising from conflict-induced forced migration generate uncertainty and introduce several policy challenges. Addressing these concerns requires an interdisciplinary approach that integrates knowledge from both computational modeling and social sciences. We propose a generalized computational agent-based modeling framework grounded by Theory of Planned Behavior to model conflict-induced migration outflows within Ukraine during the start of that conflict in 2022. Existing migration modeling frameworks that attempt to address policy implications primarily focus on destination while leaving absent a generalized computational framework grounded by social theory focused on the conflict-induced region. We propose an agent-based framework utilizing a spatiotemporal gravity model and a Bi-threshold model over a Graph Dynamical System to update migration status of agents in conflict-induced regions at fine temporal and spatial granularity. This approach significantly outperforms previous work when examining the case of Russian invasion in Ukraine. Policy implications of the proposed framework are demonstrated by modeling the migration behavior of Ukrainian civilians attempting to flee from regions encircled by Russian forces. We also showcase the generalizability of the model by simulating a past conflict in Burundi, an alternative conflict setting. Results demonstrate the utility of the framework for assessing conflict-induced migration in varied settings as well as identifying vulnerable civilian populations.

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Modelling forced migration: A framework for conflict-induced forced migration modelling according to an agent-based approach

Cited by 12 publications

References 12 publications

The climate change, conflict and migration nexus: A holistic view

The climate change, conflict and migration nexus: A holistic view

The Role of Emerging Predictive IT Tools in Effective Migration Governance

A Generalizable Theory-Driven Agent-Based Framework to Study Conflict-Induced Forced Migration

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