International Journal on Advanced Science, Engineering and Information Technology, Vol. 11 (2021) No. 4, pages: 1678-1687, DOI:10.18517/ijaseit.11.4.14845

Collective Action in Communities Exposed to Recurring Hazards: The Camp Fire, Butte County, California, November 8, 2018

L.K. Comfort, K. Soga, M. McElwee, C. Ecosse, B. Zhao


Wildfires constitute an increased risk for California, with the frequency, size, and scale of extreme events and ensuing losses escalating year by year. This article presents a case study of the Camp Fire, Butte County, California, on November 8, 2018. The event exceeded the parameters of prior emergency planning and led to the loss of 85 lives, the deadliest wildfire in California’s history. The study’s objective is to identify gaps in the information flow within and among actors that led to this outcome and to propose more robust strategies that would enable communities to manage wildfire risk sustainably. Data were collected through documentary analysis of existing emergency plans, policies, and protocols; field site visits to the damaged area; attendance at the Paradise Town meeting; and semi-structured interviews with emergency officials who had responsibility for managing the event and residents of the damaged area. A unique combination of highly risky conditions compelled the urgent evacuation of the entire Town of Paradise when emergency personnel was committed to fire suppression in a neighboring community, leaving residents of Paradise to manage their evacuation. Communications failed; regional communities, not alerted, continued standard traffic patterns, creating a massive slowdown in evacuation from Paradise.  Key insights from this study include: 1) the need to model wildfire as a regional event; 2) informed residents of communities at risk act collectively to protect the community as a whole; and 3) interaction of science, technology, and human organizations create an interdisciplinary science for managing wildfire.


Wildfire; evacuation plans; communications technologies; traffic modeling; community resilience.

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