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Building community resilience is vital due to climate change and more frequent extreme weather events, which often force people to choose between evacuating or sheltering in place. The prevalence of stay-at-home orders and quarantine practices emerging from the COVID-19 pandemic highlights the need to understand how households access resources when mobility is restricted. This research investigates peer-to-peer resource-exchanging behavior during a shelterin- place response to a flooding event amid the pandemic through an online stated response survey (n=600). Latent class analysis reveals six distinct segments based on respondents’ resource sharing and accepting behaviors. Several household and social context variables help explain these behavioral clusters. Younger individuals and individuals with lower household income are generally more reluctant to accept resources from neighbors, while larger households are more inclined to share essential items. Additionally, social resources, trust in neighbors, and preparedness level can significantly influence individuals’ resource-exchanging behaviors. The findings highlight gaps for governmental agencies and nonprofit organizations to help address, emphasizing the need to ensure sufficient allocation of resources, especially for private items such as backup power sources, communication devices, and shelter, which respondents are least willing to share. This research offers valuable insights for future disaster preparedness programs and resource allocation strategies, aiming to improve community resilience and minimize negative impacts during shelter-in-place responses. 

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 volunteerbased 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.