Primary care in the COVID-19 pandemic and beyond
Bibliographic record
Abstract
OBJECTIVE: To understand the role of primary care in the COVID-19 pandemic to provide insight into its functioning and inform potential reforms. COMPOSITION OF THE COMMITTEE: The now dissolved Ontario COVID-19 Science Advisory Table (Science Table) was formed in July 2020 to provide decision makers and the public with a synthesis of rapidly evolving evidence related to COVID-19. The Science Table was based at the Dalla Lana School of Public Health at the University of Toronto, and supported by Public Health Ontario. METHODS: Authors worked with the leadership and secretariat of the Science Table to synthesize evidence and inputs. Authors drew on their expertise in research, policy, and front-line care delivery and coupled this with data analysis and reviews of the literature relevant to the topic areas discussed. Data analysis and literature reviews were done with the support of the Ontario Medical Association, the INSPIRE-Primary Health Care research program, and the Department of Family and Community Medicine at the University of Toronto. Experts conducted a rapid review of the briefs prior to publication, and authors presented the briefs' content at a series of meetings attended by Science Table members for their input. As Science Table briefs were intended to provide rapid-response answers to important health system questions in real time, the intent was not to conduct a systematic review but rather to gather available relevant evidence and present it in a form that could be used by policy-makers. REPORT: This summary describes the work of primary care during the COVID-19 pandemic in Ontario up to September 2022; outlines current challenges in primary care capacity and structure; and makes recommendations for strengthening the sector to better address population needs for current and future public health priorities. While the focus is on Ontario, many of the findings are relevant to other jurisdictions in Canada and elsewhere. CONCLUSION: Universal formal attachment to an accountable interprofessional primary care team supported by adequate infrastructure should be the cornerstone of pandemic recovery planning.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".