The impact of the COVID‐19 pandemic on the Ontario Cervical Screening Program, colposcopy and treatment services in Ontario, Canada: a population‐based study
Bibliographic record
Abstract
OBJECTIVE: To describe the immediate impact of the COVID-19 pandemic on cervical screening, colposcopy and treatment volumes in Ontario, Canada. DESIGN: Population-based retrospective observational study. SETTING: Ontario, Canada. POPULATION: People with a cervix age of 21-69 years who completed at least one cervical screening cytology test, colposcopy or treatment procedure for cervical dysplasia between January 2019 and August 2020. METHODS: Administrative databases were used to compare cervical screening cytology, colposcopy and treatment procedure volumes before (historical comparator) and during the first 6 months of the COVID-19 pandemic (March-August 2020). MAIN OUTCOME MEASURES: Changes in cervical screening cytology, colposcopy and treatment volumes; individuals with high-grade cytology awaiting colposcopy. RESULTS: During the first 6 months of the COVID-19 pandemic, the monthly average number of cervical screening cytology tests, colposcopies and treatments decreased by 63.8% (range: -92.3 to -41.0%), 39.7% (range: -75.1 to -14.3%) and 31.1% (range: -43.5 to -23.6%), respectively, when compared with the corresponding months in 2019. Between March and August 2020, on average 292 (-51.0%) fewer high-grade cytological abnormalities were detected through screening each month. As of August 2020, 1159 (29.2%) individuals with high-grade screening cytology were awaiting follow-up colposcopy. CONCLUSIONS: The COVID-19 pandemic has had a substantial impact on key cervical screening and follow-up services in Ontario. As the pandemic continues, ongoing monitoring of service utilisation to inform system response and recovery is required. Future efforts to understand the impact of COVID-19-related disruptions on cervical cancer outcomes will be needed. TWEETABLE ABSTRACT: COVID-19 has had a substantial impact on cervical screening and follow-up services in Ontario, Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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) | 0.002 | 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 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".