Awareness of the Egyptian public about COVID-19: what we do and do not know
Bibliographic record
Abstract
To survey the health-seeking behaviors and perspectives of the Egyptian population toward the COVID-19 pandemic. A descriptive survey was designed and disseminated via social media platforms. The survey consisted of 32 questions addressing respondent's demographics, knowledge, practice, and attitude toward the COVID-19 pandemic. A total of 25,994 Egyptians participated in the survey from the 29 Egyptian governorates. More than 99% of the respondents were aware of the COVID-19 pandemic. Responses showed split opinions regarding whether people should wear gloves or masks to prevent COVID-19 infection (47.7% and 49.5% replied with "False", respectively). Almost one-quarter (23.1%) of the respondents went to crowded places during the last 14 days. Calling the emergency hotline and self-isolation at home were the most frequent practices to deal with COVID-19 symptoms (34.1% and 44.5%, respectively). A total of 85% of respondents reported their confidence in the Egyptian healthcare system to win the battle against COVID-19 despite the challenges. A vast majority of this large population sample reported reasonable knowledge levels and potentially appropriate practices toward COVID-19.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".