The impact of COVID-19 on community antibiotic use in Canada: an ecological study
Bibliographic record
Abstract
OBJECTIVES: The COVID-19 pandemic has had an effect on the incidence of infectious diseases and medical care. This study aimed to describe the impact of the COVID-19 pandemic on community-level antibiotic use. METHODS: Using national antibiotic dispensing data from IQVIA's CompuScript database, this ecological study investigated antibiotic dispensing through community retail pharmacies in Canada from November 2014 to October 2020. Analyses were stratified by age, sex, prescription origin and approximate indication. RESULTS: Adjusting for seasonality, the national rate of antibiotic dispensing in Canada decreased by 26.5% (50.4 to 37.0 average prescriptions per 1000 inhabitants) during the first 8 months of the Canadian COVID-19 period (March to October 2020), compared with the pre-COVID-19 period. Prescribing rates in children ≤18 years decreased from 43.7 to 12.2 prescriptions per 1000 inhabitants in males (-72%) and from 46.8 to 14.9 prescriptions per 1000 inhabitants in females (-68%) in April 2020. Rates in adults ≥65 decreased from 74.9 to 48.8 prescriptions per 1000 inhabitants in males (-35%) and from 91.7 to 61.3 prescriptions per 1000 inhabitants in females (-33%) in May 2020. Antibiotic prescriptions from family physicians experienced a greater decrease than from surgeons and infectious disease physicians. Prescribing rates for antibiotics for respiratory indications decreased by 56% in May 2020 (29.2 to 12.8 prescriptions per 1000 inhabitants), compared with prescribing rates for urinary tract infections (9.4 to 7.8 prescriptions per 1000 inhabitants; -17%) and skin and soft tissue infections (6.4 to 5.2 prescriptions per 1000 inhabitants; -19%). DISCUSSION: The first 8 months of the COVID-19 pandemic reduced community antibiotic dispensing by 26.5% in Canada, compared with the marginal decrease of 3% in antibiotic consumption between 2015 and 2019. Further research is needed to understand the implications and long-term effects of the observed reductions on antibiotic use on antibiotic resistance in Canada.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".