Enhancing Food Security for Families Vulnerable to COVID-19

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Abstract

The COVID-19 pandemic has exposed some of the underlying inequities in our society. Vulnerable and low-income communities who have typically struggled with food insecurity have been further impacted by the COVID-19 pandemic. To make matters worse, transit dependent households in the City of Detroit that rely on SNAP benefits from the government have a 54% probability of not having internet access, reducing the possibility of online food delivery. Thus, the motivation for the Detroit Food Delivery Pilot Program, a prepared meal delivery service for food insecure households during the COVID-19 pandemic. Through this program, the City had aided 350 households; over 1,000 unique individuals and has served over 90,000 meals. This had all been made possible through the engagement of 575 volunteers, volunteering over 6,850 delivery miles. Our team helped to identify the magnitude and the needs of the City’s food insecure population; then partnered with the City of Detroit to modify existing food programs to address the crisis, and finally, assessed the impact of the program on the target population. Our analysis revealed that approximately 20,800 households will be classified as food insecure in Detroit and only a fraction of this population is benefitting from the food delivery pilot program. However, on average, the concerns about food sufficiency have abated appreciably from the surveys analyzed. Responses from the beneficiaries of the food delivery pilot program were positive though concerns about the travel behavior of individuals, particularly those from COVID-19 positive households remain.

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  1. SciScore for 10.1101/2021.02.04.21251181: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.