Modeling Religion and Climate Migration: Case Studies in Social Simulation for Development Aid

The intersection of religion and climate change has profound implications for human migration, conflict resolution, and development aid. As the global climate crisis exacerbates humanitarian crises, religious beliefs and social structures often shape how communities respond, adapt, or resist interventions. Social simulation, particularly multi-agent artificial intelligence (MAAI) modeling, offers a powerful tool for understanding and optimizing aid strategies. This presentation explores four case studies in which computational modeling has been used to analyze religious and social dynamics in the context of climate-driven migration and crisis response.

Case Study 1. The Netherlands: Social Cohesion and Religious Identity in Refugee Integration. In the wake of the Syrian refugee crisis, European nations faced unprecedented challenges in integrating displaced populations. The Netherlands, with its robust welfare system and pluralistic society, became a key test case for modeling social cohesion. Our multi-agent simulations examined the interplay between religious identity, economic opportunity, and social acceptance in refugee communities. These models, developed in collaboration with Dutch policymakers and NGOs, demonstrated how perceptions of shared religious values or ideological divides influenced integration success or failure.

Key findings indicated that secular refugee communities integrated faster but faced higher social suspicion than religiously affiliated groups, particularly among communities with strong Christian-Muslim tensions. Economic opportunity alone did not drive integration; perceived cultural threat and religious identity signaling played a dominant role in acceptance or rejection by host populations. Policy simulations showed that faith-based community interventions, rather than secular state-led programs, were more effective at reducing social isolation and increasing trust. This work has informed Dutch refugee integration policies and continues to serve as a predictive framework for assessing the potential impact of future refugee waves—whether driven by war or climate disasters.

Case Study 2. Lesbos: The Syrian Refugee Crisis and Religious Mobilization in Greece. Lesbos, a frontline island in the 2015-2017 Syrian refugee crisis, became a microcosm of Europe’s struggle to balance humanitarianism with border security. Our social simulation models, developed in collaboration with humanitarian organizations, focused on religious mobilization and social solidarity networks in the refugee response.

The models analyzed volunteer-driven aid networks, many of which were faith-based organizations (FBOs) providing frontline assistance. A key insight was that secular NGOs struggled with trust-building, whereas Islamic and Christian aid groups created stronger in-group networks among displaced Syrians. Simulations predicted that perceived religious discrimination in aid distribution could lead to radicalization and resentment, a trend later observed in prolonged refugee encampments with inconsistent aid policies.

By applying agent-based modeling to simulate religious identity as a driving force in humanitarian aid distribution, our work provided critical insights for improving coordination between secular and faith-based relief efforts. The findings have been integrated into Greek and EU humanitarian response frameworks for future climate-driven displacement crises.

Case Study 3. European Union: Climate Mitigation, Religious Ethics, and Policy Resistance. As climate mitigation policies become more urgent, policymakers often underestimate the role of religious ethics and values in shaping resistance or acceptance. Through EU-funded research projects, our team developed multi-agent models to assess how religious worldviews shape climate policy adoption at both community and state levels. Protestant and secular nations in Northern Europe exhibited higher engagement with climate initiatives but struggled with gaining grassroots mobilization compared to religiously inspired movements. Simulations showed that interfaith alliances between Christian, Muslim, and Jewish groups created more effective environmental advocacy than secular campaigns alone. This model has been used to refine EU climate communication strategies, ensuring that mitigation policies align with cultural and religious frameworks rather than being perceived as externally imposed mandates.

Case Study 4. UNDP Program for Assistance to the Palestinian People: Modeling Religious Conflict and Climate-Driven Displacement in Palestine. One of our most complex applications of AI-driven social simulation has been our work with the UNDP on the Palestinian crisis. The intersection of religious identity, conflict, and climate-driven instability has created an urgent need for predictive models to anticipate social unrest and optimize aid distribution.

We developed a social simulation incorporating climate risk factors, such as water scarcity and agricultural collapse, into religious and political tensions in Gaza and the West Bank. The model revealed that perceived religious discrimination in aid allocation—particularly when international NGOs prioritized secular governance approaches over faith-based interventions—increased distrust and conflict likelihood. Climate shocks (such as prolonged droughts) exacerbated existing religious and ethnic divisions, leading to higher risks of radicalization in regions where aid was perceived as politically biased. This simulation has directly influenced UNDP policy recommendations on climate resilience strategies in Palestine and the wider MENA region, ensuring that development aid is culturally and religiously sensitive while remaining politically neutral.

Broader Implications: The Future of AI-Driven Development Aid. Across all four case studies, our work demonstrates that religious dynamics cannot be ignored in climate crisis response. Whether in Europe, the Middle East, or other global contexts, understanding how faith-based narratives shape human behavior is critical for effective intervention design. Multi-agent AI modeling allows policymakers and NGOs to test different intervention strategies before implementing them in real-world crises. Development aid must be culturally attuned—ignoring religious factors increases resistance and unintended negative outcomes. Future AI-driven humanitarian planning should integrate climate science, religious studies, and social simulation for more accurate and ethically responsible policy-making.

In an era where climate change is increasingly driving migration, conflict, and humanitarian crises, the role of religion as a social force must be systematically understood and incorporated into aid strategies. The use of multi-agent modeling, AI-driven simulations, and predictive analytics—as demonstrated in the Netherlands, Lesbos, EU policy studies, and Palestine—offers a path forward for more effective, context-sensitive, and scalable solutions. Through this presentation, we aim to bridge the gap between computational modeling and religious studies, highlighting how AI and social simulation can provide unprecedented insights into the role of faith in shaping climate resilience, migration patterns, and humanitarian response.