Disaster Through the Lens of Complex Adaptive Systems: Exploring Emergent Groups Utilizing Agent Based Modeling and Social Networks
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2020
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Abstract
Disasters have become more frequent and intense in the last decades and are a significant challenge to the health and well-being of local communities and regions. As a potential solution to this problem attention has been drawn to community resilience and the building of social networks that support or hinder local response and recovery. Research on disasters and community resilience has shown how the ability to leverage social capital through a community’s social networks is fundamental to the ability of individuals and communities to respond to disaster events, but there is little understanding of how the evolution of social networks can impact disaster response and recovery. A computational framework and agent-based model of disasters can provide a virtual laboratory for testing social network effects and uncover their role, function and underlying mechanisms in community resilience. Agent-based models are suited to test bottom-up dynamics and the interactions of variables that lead to the nonlinear relationships in disasters. To what extent can an agent-based model characterize the social networks that emerge in response to a no-warning disaster event such as a Nuclear Weapon of Mass Destruction impacting Manhattan Island? To explore this question this research reviews theories of disaster, primarily from sociological and anthropological research, and builds a conceptual model of disasters from which to develop an agent-based model. The agent-based model represents social networks relevant in both the normal commuting patterns of New York City and the emergent social networks responding to a Nuclear Weapon of Mass Destruction impacting Manhattan Island. Network representations of social groups along with physical representations of the community shows how individuals adapt and respond to the disaster in the initial response. Integrating agent-based models with social network analysis provides new spaces for scientific inquiry into disasters, the dynamics of social networks in resilient communities, and those areas of complexity most often explored today with qualitative methodologies.