Exploring the worldwide impact of COVID-19 on conflict risk under climate change

Xiaolan Xie, Mengmeng Hao, Fangyu Ding*, Tobias Ide, David Helman, Jürgen Scheffran, Qian Wang, Yushu Qian, Shuai Chen, Jiajie Wu, Tian Ma, Quansheng Ge*, Dong Jiang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Objectives: Understand whether and how the COVID-19 pandemic affects the risk of different types of conflict worldwide in the context of climate change. Methodology: Based on the database of armed conflict, COVID-19, detailed climate, and non-climate data covering the period 2020–2021, we applied Structural Equation Modeling specifically to reorganize the links between climate, COVID-19, and conflict risk. Moreover, we used the Boosted Regression Tree method to simulate conflict risk under the influence of multiple factors. Findings: The transmission risk of COVID-19 seems to decrease as the temperature rises. Additionally, COVID-19 has a substantial worldwide impact on conflict risk, albeit regional and conflict risk variations exist. Moreover, when testing a one-month lagged effect, we find consistency across regions, indicating a positive influence of COVID-19 on demonstrations (protests and riots) and a negative relationship with non-state and violent conflict risk. Conclusion: COVID-19 has a complex effect on conflict risk worldwide under climate change. Implications: Laying the theoretical foundation of how COVID-19 affects conflict risk and providing some inspiration for the implementation of relevant policies.

Original languageAmerican English
Article numbere17182
JournalHeliyon
Volume9
Issue number6
DOIs
StatePublished - Jun 2023

Bibliographical note

Publisher Copyright:
© 2023 The Authors

Keywords

  • Boosted regression trees
  • COVID-19
  • Causal link
  • Conflict risk
  • Structural equation model

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