How infectious disease outbreaks affect community-based primary care physicians: comparing the SARS and H1N1 epidemics.
Bibliographic record
Abstract
OBJECTIVE: To compare how the infectious disease outbreaks H1N1 and severe acute respiratory syndrome (SARS) affected community-based GPs and FPs. DESIGN: A mailed survey sent after the H1N1 outbreak compared with the results of similar survey completed after the SARS outbreak. SETTING: Greater Toronto area in Ontario. PARTICIPANTS: A total of 183 randomly selected GPs and FPs who provided office-based care. MAIN OUTCOME MEASURES: The perceptions of GPs and FPs on how serious infectious disease outbreaks affected their clinical work and personal lives; their preparedness for a serious infectious disease outbreak; and the types of information they want to receive and the sources they wanted to receive information from during a serious infectious disease outbreak. The responses from this survey were compared with the responses of GPs and FPs in the greater Toronto area who completed a similar survey in 2003 after the SARS outbreak. RESULTS: After the H1N1 outbreak, GPs and FPs still had substantial concerns about the effects of serious infectious disease outbreaks on the health of their family members. Physicians made changes to various office practices in order to manage and deal with patients with serious infectious diseases. They expressed concerns about the effects of an infectious disease on the provision of health care services. Also, physicians wanted to quickly receive accurate information from the provincial government and their medical associations. CONCLUSION: Serious community-based infectious diseases are a personal concern for GPs and FPs, and have considerable effects on their clinical practice. Further work examining the timely flow of relevant information through different health care sectors and government agencies still needs to be undertaken.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".