Continuity of routine immunization programs in Canada during the COVID-19 pandemic
Bibliographic record
Abstract
INTRODUCTION: In Canada, the COVID-19 pandemic has interrupted many routine health services, placed additional strain on the health care system, and resulted in many Canadians being either unable or unwilling to attend routine immunization appointments. We sought to capture and synthesize information about changes to routine immunization programs in response to the pandemic and plans to catch-up any missed immunizations. METHODS: Provincial/territorial (P/T) public health leaders were interviewed via teleconference between August-October 2020 to collect information on the following topics: how routine immunization delivery was affected during and after initial lockdown periods, plans to catch-up missed doses, and major challenges and achievements in continuing routine immunization programs. Data were coded and categorized according to common responses and descriptive analysis was performed. RESULTS: Interviews occurred with participants from 11 of 13 P/Ts. School immunization programs were reported to be most negatively affected by the pandemic (n = 9). In the early pandemic period, infant, preschool, and maternal/prenatal programs were prioritized, with most P/Ts continuing these services with adaptations for COVID-19. After the initial lockdown period, all routine programs were continuing with adaptations in most P/Ts. Infant, preschool, and school programs were most often targeted for catch-up through measures such as appointment rebooking and making additional clinics and/or providers available. Major challenges included resource limitations (e.g., staff shortages, PPE shortages, limited infrastructure) (n = 11), public health restrictions (n = 8), and public hesitancy to attend appointments (n = 5). CONCLUSIONS: Canadian routine immunization programs faced some disruptions due to the COVID-19 pandemic, particularly the school, adult, and older adult programs. Further research is needed to determine the measurable impact of the pandemic on routine vaccine coverage levels.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".