TY - JOUR
T1 - Exploring the worldwide impact of COVID-19 on conflict risk under climate change
AU - Xie, Xiaolan
AU - Hao, Mengmeng
AU - Ding, Fangyu
AU - Ide, Tobias
AU - Helman, David
AU - Scheffran, Jürgen
AU - Wang, Qian
AU - Qian, Yushu
AU - Chen, Shuai
AU - Wu, Jiajie
AU - Ma, Tian
AU - Ge, Quansheng
AU - Jiang, Dong
N1 - Publisher Copyright:
© 2023 The Authors
PY - 2023/6
Y1 - 2023/6
N2 - 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.
AB - 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.
KW - Boosted regression trees
KW - COVID-19
KW - Causal link
KW - Conflict risk
KW - Structural equation model
UR - http://www.scopus.com/inward/record.url?scp=85161943333&partnerID=8YFLogxK
U2 - 10.1016/j.heliyon.2023.e17182
DO - 10.1016/j.heliyon.2023.e17182
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C2 - 37332947
AN - SCOPUS:85161943333
SN - 2405-8440
VL - 9
JO - Heliyon
JF - Heliyon
IS - 6
M1 - e17182
ER -
