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Anamaria Bukvic

Virginia Tech

Breakout Room 1.


Integration; decision sciences; multi-hazard; security

How can the human dimensions of disaster impacts be more accurately captured and represented in the analysis, modeling and simulation of disasters?

The human dimensions of contemporary emerging problems are difficult to measure due to their complexity and ever-changing nature in response to internal and external stimuli and stressors. However; several new methodological approaches may allow us to capture some of those vital determinants before; during; and after the disaster. Namely; mixed-method approaches that combine primary; bottom-up qualitative and quantitative data from focus groups; interviews; and surveys; which can be integrated with other secondary data in vulnerability assessments; geospatial analysis; Agent-Based Modeling; and Machine Learning/Artificial Intelligence models to scale up granular information or identify trends that would otherwise be less evident. Another promising strategy involves real-time data acquisition and rapid data processing with decision-makers and stakeholders directly involved in interpreting and identifying policy-relevant results. Other emerging approaches; such as citizen science or crowdsourcing and participatory GIS mapping using technology; can foster engagement of diverse populations with difficult issues; ensuring that actors who would otherwise be excluded from disaster resilience planning get a voice in this discourse. Finding interdisciplinary data science approaches that will effectively integrate social science primary and secondary data to validate and refine computational models and allow for forward-looking exploration of future risks will be central to this success. Further; the ability to advance methods of forecasting population growth and estimating future changes in the cultural; socioeconomic; and political landscape of places to allow for spatiotemporal alignment with models of sea level rise and disaster risk will be vital to support forward-looking disaster planning.

What type of data and supporting research infrastructure would be necessary to enable novel, transdisciplinary approaches to answering these and other human-centered disaster questions?

Developing culturally and socially sensitive data collection modalities will be critical; as well as improving a real-time data collection of a more inclusive range of social indicators. Establishing collaborations and human-data collection protections with local partners and developing a framework that will allow for consistent data collection of disaster-related human behaviors and choices would allow for more meaningful data sharing and cross pollination across various spatio-temporal scales. Longitudinal studies and those designed to be transferable to other geographic locations are prevalently lacking. Funding opportunities that would support a more comprehensive and consistent human-subject data collection over time and allow for some non-conventional experimentation may be able to capture behavioral signals that would otherwise be indiscernible. Identifying the most critical disaster resilience indicators for different locations and settings (e.g.; rural and urban) and aligning data sources with the local context would be vital to produce data that could be integrated into data science approaches. A financially and institutionally supported framework would provide continued expertise; guidance; and technical assistance to facilitate the integration of human data into novel computing and other approaches and knowledge.  Cross pollination between the U.S. and Japan would help sharing methodologies; transferable models; and lessons learned between these two countries. Data access and open-source sharing would allow comparative analysis between disaster responses in different locations to identify most effective contributing factors to disaster resilience.

In what ways can US-Japan collaborations advance these questions in new and important ways?

Emerging issues are becoming increasingly complex and volatile both in the U.S. and Japan. Human dimensions of disaster resilience are shaped by many local to global factors that must be considered in the discourse on long-term disaster preparedness. One fundamental way human-centered disaster risk reduction research would be advanced is by developing more holistic research approaches designed to capture and manage social complexities; cascading events; and compound stressors. For example; such strategies would consider disaster impacts and probe how they intersect with various security issues and other sources of instability across scales. Considering the anticipated acceleration of disaster risk in both the U.S. and Japan and a growing awareness that cookie-cutter solutions often do not yield desired results; a novel approach is needed that builds off the inherent resilience and empowers communities to be active participants in preparedness actions through their behaviors; choices; and actions. The US-Japan collaboration should focus on multi-hazard scenarios coupled with external national security threats or sudden permanent shifts in climate conditions to assess the risk of low probability; high-impact events. This can be achieved by developing collaborative scenario planning exercises to dissect potential impacts across national and transboundary systems. The collaboration should explore the role of cultural competence in handling disasters and how other social changes; such as the use of technology; changes in family structure; mental and physical health; and willingness to participate in collective action; affect disaster resilience.

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