Unplanned disaster events can greatly disrupt access to essential resources, with calamitous outcomes for already vulnerable households. This is particularly challenging when concurrent extreme events affect both the ability of households to travel and the functioning of traditional transportation networks that supply resources. This paper examines the use of volunteer-based crowdsourced food delivery as a community resilience tactic to improve food accessibility during overlapping disruptions with lasting effects, such as the COVID-19 pandemic and climate disasters. The study uses large-scale spatio-temporal data (n = 28,512) on crowdsourced food deliveries in Houston, TX, spanning from 2020 through 2022, merged with data on community demographics and significant disruptive events occurring in the two-year timespan. Three research lenses are applied to understand the effectiveness of crowdsourced food delivery programs for food access recovery: 1) geographic analysis illustrates hot spots of demand and impacts of disasters on requests for food assistance within the study area; 2) linear spatio-temporal modeling identifies a distinction between shelter-in-place emergencies and evacuation emergencies regarding demand for food assistance; 3) structural equation modeling identifies socially vulnerable identity clusters that impact requests for food assistance. The findings from the study suggest that volunteer-based crowdsourced food delivery adds to the resilience of food insecure communities, supporting its effectiveness in serving its intended populations. The paper contributes to the literature by illustrating how resilience is a function of time and space, and that similarly, there is value in a dynamic representation of community vulnerability. The results point to a new approach to resource recovery following disaster events by shifting the burden of transportation from resource-seekers and traditional transportation systems to home delivery by a crowdsourced volunteer network.

中文翻译：

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提高社区对食物获取中断的复原力：基于志愿者的众包食品配送的实证时空分析


计划外的灾难事件会极大地破坏对基本资源的获取，给本已脆弱的家庭带来灾难性的后果。当同时发生的极端事件同时影响家庭出行能力和提供资源的传统交通网络的运作时，这一点尤其具有挑战性。本文研究了使用基于志愿者的众包食品配送作为社区弹性策略，以在具有持久影响的重叠中断（例如 COVID-19 大流行和气候灾难）期间改善食品可及性。该研究使用了 2020 年至 2022 年德克萨斯州休斯顿众包食品配送的大规模时空数据 （n = 28,512），并结合了社区人口统计数据和两年时间跨度内发生的重大破坏性事件的数据。应用三个研究镜头来了解众包食品配送计划对食品获取恢复的有效性：1） 地理分析说明了需求热点和灾害对研究区域内食品援助请求的影响;2） 线性时空模型确定了就地避难紧急情况和疏散紧急情况在食品援助需求方面的区别;3） 结构方程建模识别影响食品援助请求的社会弱势身份集群。研究结果表明，基于志愿者的众包食品配送增加了粮食不安全社区的复原力，支持其为目标人群服务的有效性。本文通过说明弹性如何成为时间和空间的函数，以及同样，动态表示社区脆弱性也有价值，从而为文献做出了贡献。 结果指出了一种在灾难事件后恢复资源的新方法，方法是将交通负担从寻求资源的人和传统的交通系统转移到众包志愿者网络送货上门。