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1. An Interactive Dashboard to Study the Impact of Hurricane Florence on Food Bank Operations

   https://doi.org/10.1109/CSCI51800.2020.00219  

   Enyew, Bantwale ; Odubela, Kehinde ; Jiang, Steven ; Davis, Lauren ( December 2020 , 2020 International Conference on Computational Science and Computational Intelligence (CSCI))

   null (Ed.)

   North Carolina is the third most hurricane-prone states in the US. In 2018, Hurricane Florence caused a lot of damages to households in North Carolina. The Food Bank of Central and Eastern North Carolina (FBCENC) serves 34 counties in North Carolina, and 22 of them were affected by Hurricane Florence. This research aims to investigate the impact of Hurricane Florence on the operations of FBCENC. We developed interactive dashboards to visualize food bank operational data and other relevant data and studied the trends and patterns of food distribution in three key stages: preparedness, response, and recovery. These dashboards enable food bank operations managers to explore and interact with the data with ease to explore the operational data at different stages, at different branch level, and on a different time scale (monthly, weekly, or daily). The impact on the operations of affected service areas vs. not affected areas could be investigated as well. The findings of this research will provide insight into how humanitarian relief agencies can better prepare for, respond to, and recover from the disruptions caused by hurricanes. 

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2. Proceedings of the 2018 IISE annual conference

   Islam, M. ; Ivy, J. ( May 2018 , Modeling for Efficient Assignment of Multiple Distribution Centers for the Equitable and Effective Distribution of Donated Food)

   Food insecurity affects more than 41 million people annually in the United States. Within the Feeding America network, approximately 200 food banks are working throughout the US to serve people in need with donated food. Satisfying hunger need of food insecure people with limited supply is a challenge for these food banks. A numerical study is performed on data from Food Bank of Central and Eastern North Carolina (FBCENC) to capture the major attributes controlling its food distribution system. FBCENC seeks to distribute donated food equitably so that each service area (county) receives food proportional to its demand while minimizing the undistributed food donations. In addition to seeking equitable and effective food distribution policies, FBCENC wants to identify distribution branches to maximize the accessibility of the counties to donated food. An assignment and distribution model is developed to minimize the cost of maintaining a user-specified cap on the maximum inequity in food distribution. A sensitivity analysis between the user-specified maximum inequity cap and effectiveness shows the effectiveness of donated food distribution can be improved significantly by sacrificing equitable distribution slightly. 

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3. Demonstrating a systems approach for integrating disparate data streams to inform decisions on children’s environmental health

   https://doi.org/10.1186/s12889-022-12682-3  

   Hubal, Elaine A. Cohen ; DeLuca, Nicole M. ; Mullikin, Ashley ; Slover, Rachel ; Little, John C. ; Reif, David M. ( February 2022 , BMC Public Health)

   The use of systems science methodologies to understand complex environmental and human health relationships is increasing. Requirements for advanced datasets, models, and expertise limit current application of these approaches by many environmental and public health practitioners.

   A conceptual system-of-systems model was applied for children in North Carolina counties that includes example indicators of children’s physical environment (home age, Brownfield sites, Superfund sites), social environment (caregiver’s income, education, insurance), and health (low birthweight, asthma, blood lead levels). The web-based Toxicological Prioritization Index (ToxPi) tool was used to normalize the data, rank the resulting vulnerability index, and visualize impacts from each indicator in a county. Hierarchical clustering was used to sort the 100 North Carolina counties into groups based on similar ToxPi model results. The ToxPi charts for each county were also superimposed over a map of percentage county population under age 5 to visualize spatial distribution of vulnerability clusters across the state.

   Data driven clustering for this systems model suggests 5 groups of counties. One group includes 6 counties with the highest vulnerability scores showing strong influences from all three categories of indicators (social environment, physical environment, and health). A second group contains 15 counties with high vulnerability scores driven by strong influences from home age in the physical environment and poverty in the social environment. A third group is driven by data on Superfund sites in the physical environment.

   This analysis demonstrated how systems science principles can be used to synthesize holistic insights for decision making using publicly available data and computational tools, focusing on a children’s environmental health example. Where more traditional reductionist approaches can elucidate individual relationships between environmental variables and health, the study of collective, system-wide interactions can enable insights into the factors that contribute to regional vulnerabilities and interventions that better address complex real-world conditions.

    

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4. A comparison of raster-based point density calculations to vector-based counterparts as applied to the study of food availability

   https://doi.org/10.1186/s40066-023-00455-z  

   Mulrooney, Timothy ; Akinnusi, Samuel ; McGinn, Christopher ; Okoli, Chima ; Esimaje, Tony ( January 2024 , Agriculture & Food Security)

   Proximity to food sources is one of the quantifiable factors measurable across space impacting diet-related health outcomes. Contemporary research has coined the terms ‘food desert’ and ‘food swamp’, sometimes combined with a poverty component, to highlight disproportionate access to healthy and unhealthy food sources. However, there are various ways to measure this proximity—i.e., food availability in this research. Dollar stores such as Dollar General, Family Dollar, and Dollar Tree are one emerging facet of the food environment that provides healthy and unhealthy food options yet have not fully been studied. With more ways to easily measure food availability within the confines of a GIS, this paper proposes a new raster-based Point Density metric to measure the availability of these Dollar stores. In this study, this raster-based metric was calculated for a 6-county region in central North Carolina and compared to six other availability metrics utilized in food security research. A novel Python-based tool to compute the Jaccard Index between these various availability metrics and a matrix to compare these pairwise Jaccard Index calculations was created for this raster-based metric, which is very easy to derive.

   Using a pairwise Jaccard Index summarized and then averaged in a correlation table, the Point Density measure rated the highest (.65) when compared to 6 other popular vector-based techniques. Our results showed the density metric performed statistically better than Euclidean distance, drive-time, density, and point-in-polygon vector metrics when measuring availability for Dollar stores in Central North Carolina.

   Results reinforce the efficacy of this easy-to-compute metric comparable to vector-based counterparts that require more robust network and/or geoprocessing calculations. Results quantitatively evaluate food availability with an eventual goal of dictating local, regional, and even state-level policy that critically and holistically consider this metric as powerful and convenient metric that can be easily calculated by the lay GIS user and understood by anyone.

    

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5. A Visual Analysis of Food Availability in Davidson County NC

   https://doi.org/10.1109/SoutheastCon44009.2020.9249675  

   Faust, Christina ; Esterline, Albert ( March 2020 , IEEE)

   Community Food Strategies provides guidance and tools to local food networks in North Carolina to empower the creation of equitable policy change at all levels. Their vision is the realization of an equitable food system that improves the quality of life for all. In Davidson County, the recently formed Local Food Network, created under the guidance of Community Food Strategies, is working to create a more equitable and sustainable food system and is evaluating how best to apply their resources toward this end. The county is largely rural, and rural areas tend to have lower food access. Two cities, Lexington and Thomasville, have experienced economic depression over the past three decades with the exodus of furniture manufacturing overseas and as such, both cities have communities that suffer from poverty and food insecurity issues. In this research, we use visual analytics and spatial analysis to build a survey and analysis of local food availability for the county. Visual analytics is increasingly being applied to applications like this to increase understanding of large datasets and improve decision making. This research provides a base analysis for the Local Food Network to present the state of the local food system to potential partners who can help create policies that will increase equity and availability of food to everyone in the county. 

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