Reaching the “Last Mile”: describing community clinics implemented to increase COVID-19 vaccine uptake in Peel region, Canada
Bibliographic record
Abstract
BACKGROUND: COVID-19 hit Canada hard and exacerbated health inequities, notably among ethnoracially minoritized populations. By August 2021, some areas in Peel region (Ontario, Canada) continued to have high COVID-19 infection rates and low COVID-19 vaccine coverage. To increase first dose uptake, Peel Public Health implemented smaller community-based vaccination clinics in addition to pre-existing mass vaccination (fixed) clinics. This study describes these community clinics and those who received their first dose at a community clinic to determine whether local public health efforts to implement community clinics reached different population groups and whether these community clinics contributed to an increase in uptake of the first dose of COVID-19 vaccines. METHODS: We conducted a descriptive, cross-sectional study using data from the Ontario COVID-19 vaccination registry (COVaxON). We included eligible Peel residents 12 years and older who received a COVID-19 vaccine within community and fixed clinics between September 2021 and August 2022. Clinics were classified based on clinic type (community/fixed), and location. COVID-19 vaccine uptake for smaller geographic areas designated by postal codes was calculated at the beginning and end of the study period. Clinic and attendee characteristics were analyzed using descriptive statistics. RESULTS: There were 177 community and 11 fixed clinic sites that operated during the study period. Community clinics administered 98,965 doses (27%) of COVID-19 vaccine and fixed clinics administered 264,021 doses (73%). A slightly higher proportion of first doses were administered in community clinics (8.1%) compared to fixed clinics (7.9%) and community clinics saw a higher proportion of first dose recipients from low-coverage areas (23% versus 19% in fixed clinics). Clinics in faith-based organizations, schools and shopping areas administered the most doses among community clinic locations. The absolute increase in first dose vaccine uptake was 11% over the study period. CONCLUSIONS: Almost 100,000 doses of COVID-19 vaccine were administered in community clinics, which contributed to increased overall vaccine coverage in Peel region. A slightly higher proportion of first doses were administered in community clinics compared to fixed clinics and a higher proportion of doses to residents of low-coverage areas.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".