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Leveraging epidemic network models towards wildfire resilience

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Wildfires have increased in frequency and intensity due to climate change and have had severe impacts on the built environment worldwide. Moving forward, models should take inspiration from epidemic network modeling to predict damage to individual buildings and understand the impact of different mitigations on the community vulnerability in a network setting.

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Fig. 1: Treatment of community wildfire as a computational network flow problem.

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Acknowledgements

The work was made possible by the generous funding from the Gordon and Betty Moore Foundation under award no. 11994. The content expressed in this paper is the views of the author and does not necessarily represent the opinions or views of the Gordon and Betty Moore Foundation. H.M. developed the concept and wrote the paper.

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Authors and Affiliations

  1. Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO, USA

    Hussam Mahmoud

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  1. Hussam Mahmoud
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Correspondence to Hussam Mahmoud.

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Nature Computational Science thanks Jiafu Mao and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Kaitlin McCardle, in collaboration with the Nature Computational Science team.

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Mahmoud, H. Leveraging epidemic network models towards wildfire resilience. Nat Comput Sci 4, 253–256 (2024). https://doi.org/10.1038/s43588-024-00619-2

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