Comparison of the Seasonal Influenza Vaccination amidst the 2020 COVID-19 Pandemic within Six Regional Community Pharmacies of a Large Pharmacy Chain
Bibliographic record
Abstract
Background: The CDC has issued interim guidance on administering influenza vaccines amidst the COVID-19 pandemic including providing specific appointment times. A large chain pharmacy has adopted this guidance and is encouraging patients to make appointments rather than a walk-in visit for the influenza vaccination to help avoid large crowds. Objective(s): This study aims to determine the impact of the COVID-19 pandemic on influenza vaccination rates (2019 versus 2020 season) and patient appointments versus walk-in visits. The second goal of this study is to evaluate patient satisfaction with the influenza vaccination process. Methods: Influenza vaccine data was collected from the chain pharmacy online database from the first week in September to the last week in December during 2019 to 2020 and from 2020 to 2021. The second part of this study included a voluntary survey to be completed by the patient regarding satisfaction and thoughts about the 2020-2021 influenza vaccination process. Results: The six stores identified showed an overall 7.6% increase in influenza vaccination rates from the 2019-2020 season to the 2020-2021 season (p-value= 0.73). There were a total of 15 survey respondents amongst the stores of which 100% of the patients were at least slightly comfortable with the vaccination process and very satisfied overall. Conclusion: The six pharmacy locations within a large chain revealed that COVID-19 had a positive impact on influenza vaccination rates. Although these results were not statistically significant, this study sets the framework for future vaccination studies.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".