Assessment of Preparedness for the COVID-19 Pandemic in Schools in Al-Rusafa District, Baghdad, Iraq, 2021
Bibliographic record
Abstract
Background Following the international spread of the novel coronavirus (SARS-CoV-2) or COVID-19 pandemic, the Iraqi government took several steps to prevent community transmission, including the indefinite closure of schools as a measure to safeguard schoolchildren from COVID-19. The key rationale behind these decisions was the insufficient preparedness level within schools to prevent infection and the lack of appropriate vaccines for children. Objective Researchers assessed COVID-19 preparedness levels in schools in Al-Rusafa district, Baghdad, to prepare schools for reopening. Methods An observational study design was conducted to assess the schools. Stratified sampling was performed to make the sample more representative; we stratified the schools into 3 categories based on sex, level (primary or secondary), and administration (public or private). The study population comprised all students and teachers in the selected sample. The assessment was carried out retrospectively for 3 months, from May 31, 2021. Data were collected through face-to-face interviews and analyzed using Microsoft Excel. Tables and pie charts were used to display the results. Results The assessment was completed in 40 schools—20 (50%) primary schools, 10 (25%) high schools, 6 (15%) intermediate schools, and 4 (10%) secondary schools. Overall, the assessment covered 1162 teachers and 16,776 students. The highest infection rate, according to school category, was among primary school staff (6.14%). Moreover, 92% (n=39) of the schools did not have a contact number for a nearby ambulance, and early detection system was weak in 60% (n=24) of the schools, which reflected low levels of school participation in preparing against the COVID-19 pandemic. Referral system for any sick person to an appropriate health facility was not present or was disabled in 63% (n=25) of the schools. Conclusions The assessment concluded that none of the schools had a robust screening system to record students infected with COVID-19. The study discusses several actions and requirements that should be reviewed and addressed to prevent the spread of COVID-19 in the schools and the community.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".