Assessing household underestimation of hurricane food shortages via large language model agent simulation

IF 4.5 1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
Junkang Xu, Chao Fan
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引用次数: 0

Abstract

Food shortages are a significant challenge to public health during natural disasters like hurricanes. Household food shortages during disasters often result from limited access to grocery stores, limited supplies of food, and limited preparation of food at home before a disaster. Existing literature has examined food shortages regarding food supply security and access to food providers. Little is known about how households estimate the duration of food shortages and make decisions about food preparation before disasters. This research proposes a method to quantify the causal impacts of socio-demographics, past experiences, economic status, and trust in community infrastructure on the estimation of food preparation, which also informs effective warning information to enhance the food preparation of households. We adopt a post-Hurricane Harvey household survey conducted in Harris County to apply Generalized Structural Equation Models and find that households with past hurricane experience are more prone to underestimating the impacts than those without such experience. Single-gender households underestimate food shortages more than balanced-gender households, while education is not a significant determinant. Furthermore, we incorporate the decision mechanisms into the Large Language Model and simulate household estimation of food shortages to different types of warning information tailored by economic, infrastructure, and social impacts. Warning information emphasizing infrastructure impacts is found to be effective for most households, while social impact-focused warning significantly improves elderly households’ estimations. Our work offers insights into human perceptions of disaster impacts and customized warning interventions in reducing the underestimation of hurricane-induced food shortages and emphasizes the need for context-specific delivery.
通过大型语言模型代理模拟评估家庭对飓风食物短缺的低估
在飓风等自然灾害期间,粮食短缺是对公共卫生的重大挑战。灾害期间的家庭粮食短缺往往是由于进入杂货店的机会有限、食物供应有限以及灾害前在家中准备的食物有限造成的。现有文献研究了食品供应安全和获得食品供应商的粮食短缺问题。人们对家庭如何估计食物短缺的持续时间以及如何在灾难发生前做出准备食物的决定知之甚少。本研究提出了一种量化社会人口统计、过去经验、经济状况和对社区基础设施信任对食物准备估计的因果影响的方法,这也提供了有效的警告信息,以增强家庭的食物准备。我们采用在哈里斯县进行的哈维飓风后的家庭调查,应用广义结构方程模型,发现过去经历过飓风的家庭比没有经历过飓风的家庭更容易低估飓风的影响。单性别家庭比性别平衡家庭更低估了食物短缺,而教育不是一个重要的决定因素。此外,我们将决策机制纳入大语言模型,并根据经济、基础设施和社会影响量身定制不同类型的警告信息,模拟家庭对粮食短缺的估计。研究发现,强调基础设施影响的预警信息对大多数家庭有效,而以社会影响为重点的预警信息显著提高了老年家庭的估计。我们的工作提供了对人类对灾害影响的认知和定制的预警干预措施的见解,以减少对飓风引起的粮食短缺的低估,并强调了根据具体情况提供服务的必要性。
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来源期刊
International journal of disaster risk reduction
International journal of disaster risk reduction GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
8.70
自引率
18.00%
发文量
688
审稿时长
79 days
期刊介绍: The International Journal of Disaster Risk Reduction (IJDRR) is the journal for researchers, policymakers and practitioners across diverse disciplines: earth sciences and their implications; environmental sciences; engineering; urban studies; geography; and the social sciences. IJDRR publishes fundamental and applied research, critical reviews, policy papers and case studies with a particular focus on multi-disciplinary research that aims to reduce the impact of natural, technological, social and intentional disasters. IJDRR stimulates exchange of ideas and knowledge transfer on disaster research, mitigation, adaptation, prevention and risk reduction at all geographical scales: local, national and international. Key topics:- -multifaceted disaster and cascading disasters -the development of disaster risk reduction strategies and techniques -discussion and development of effective warning and educational systems for risk management at all levels -disasters associated with climate change -vulnerability analysis and vulnerability trends -emerging risks -resilience against disasters. The journal particularly encourages papers that approach risk from a multi-disciplinary perspective.
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