Characterization of community-based donation of personal protective equipment to an academic health center during the COVID-19 pandemic
Bibliographic record
Abstract
Objective: The novel coronavirus 2019 (COVID-19) pandemic led to a shortage of personal protective equipment (PPE) early in the pandemic. Healthcare systems asked for public donations of PPE and established community drop-off sites. Herein, we aim to profile community PPE donors at one large academic medical center including evaluation of donor industry, public messaging, and psychosocial aspects of donation.Methods: A survey was created and distributed to donors at two urban PPE drop-off sites between March and April 2020. Targeted donors and drop-off sites were located in the Twin Cities metropolitan area (approximate population of 3.5 million people).Results: A total of 486 surveys were completed. Nearly half (47.3%) of PPE donated was initially intended for personal use. Donors primarily learned of PPE collection efforts through word of mouth (23.2%) and social media (22.7%). The most frequently reported barrier to donation included distance between donors and drop off sites or location (27.8%). Donors rated the severity of the PPE shortage in the state as a 7.8 ± 1.7 out of 10. There was a slight correlation between donors assessment of COVID-19 severity and feeling that their donation was a meaningful contribution against COVID-19 (r = 0.21, p = .00).Conclusions: Future community collection campaigns during widespread disasters should prioritize mobilizing privately held goods from individuals rather than small businesses. Public messaging around donation should utilize simple narratives that are easily shareable via social media and evoke donation as a means of building community.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".