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 disaster impacts take shape in various ways including but not limited to decisions made in response to disruptions; interactions between people and infrastructure; and intangible losses of disasters (e.g.; health and psychological impact). To more accurately capture and represent them in disaster models and analyses; there is a need to develop new theories and models that capture the dynamics of the human dimensions in disaster models. For example; significant emphasis has been placed on improving our understanding of critical infrastructure interdependencies. However; there is an additional layer of interdependencies between humans and infrastructure that further amplifies these complex interactions. A lack of understanding of social and organizational interdependencies can result in unintended consequences that harm communities during disasters. As such; modeling network interdependencies must be expanded to include human-infrastructure interactions which requires new modeling approaches that account for the dynamic and uncertain nature of these interdependencies. Another example is in the quantification of disaster losses. While most models developed have focused on the direct and tangible losses (e.g.; structural damage; economic impact); little attention is paid to intangible costs when planning for mitigation and adaptation strategies to climate change. These intangible costs often include health; environmental; and social impacts. Disaster loss models that account for both tangible and intangible costs will more accurately capture human dimensions of disaster impacts.
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?
To enable advances towards transdisciplinary approaches in human-centered disaster research; it is important to understand how people plan for and respond to disasters; what and how decisions are made before; during; and after disruptive events; and how such information should be integrated with disaster models and analyses. In addition; understanding human risk perception is critical to anticipate how communities react to changes and how stakeholders prioritize resource allocation across multiple hazards; infrastructure sectors; and populations. Depending the type of the data that supports such important information (e.g.; decisions; movement during disasters; risk perception); the data can be collected using crowdsourcing approaches; surveys; interviews; or estimated using proxies from other dimensions of disaster impacts. A challenge lies in the ability to integrate the data in comprehensive and holistic approaches that cross over multiple dimensions of disasters (i.e.; the built environment; hazards; and human) which results in varying levels of data size; completeness; and reliability. In addition; the data on the human dimension would also vary in the levels of fidelity; accuracy; and uncertainty depending on whether it's crowd sourced or collected with surveys and interviews. As such; there is a need for novel models; data integration methods; and computation capacities that address data heterogeneity to enable its usability in the disaster context.
In what ways can US-Japan collaborations advance these questions in new and important ways?
There are various ways US-Japan collaborations can help advance transdisciplinary research to achieve human-centered disaster management. First; the exchange of ideas; models; and methods can enrich both communities to explore new ways of applying existing methods or identify research directions to overcome their limitations. Second; the diversity in the hazard and disaster data collected across communities will help determine lessons to be learned to improve the research and practice of disaster management. Overall; both communities are experienced in different types of communities; hazard scenarios; and climate archetypes; and they have each made significant scientific advances in disaster models; analysis; and simulation. As such; these collaborations would benefit the broader research community by addressing critical questions to achieve a human-centered disaster management.