Assessment of Temporary Community-Based Health Care Facilities During Arbaeenia Mass Gathering at Karbala, Iraq: Cross-Sectional Survey Study
Bibliographic record
Abstract
BACKGROUND: Arbaeenia mass gathering (MG) in Karbala, Iraq, is becoming one of the largest MGs in the world. The health care infrastructure in Iraq is inadequately prepared to serve the health needs of the millions of pilgrims. OBJECTIVE: This study aimed to describe the temporary health care facilities installed and run by the local community to provide health care services to Arbaeenia pilgrims in Karbala, Iraq. METHODS: A survey was conducted in all community-based health care facilities located along part of Najaf to Karbala road within Karbala governorate. A structured questionnaire was answered through an interview with the workers and direct observation. Data were collected on staff profile, type of services provided, use of basic infection control measures, medical equipment, drugs and supplies, and the most commonly encountered medical problems. RESULTS: The total number of health care facilities was 120, staffed by 659 workers. Only 18 (15.0%, 18/120) facilities were licensed, and 44.1% (53/120) of the workers were health professionals. The health care workers provided different services including dispensing drugs (370/1692, 21.87%), measuring blood pressure and blood sugar (350/1692, 20.69%), and caring for wounds and injuries (319/1692, 18.85%). Around 97% (116/120) health facilities provided services for musculoskeletal disorders and only 16.7% (20/120) provided services for injuries. The drugs available in the clinic were analgesics, drugs for gastrointestinal and respiratory diseases, and antibiotics, with an availability range of 13.3% to 100.0%. Infection control practices for individual protection, environmental sanitation, and medical waste disposal were available in a range of 18.1% to 100.0%. CONCLUSIONS: Community-based health care facilities experienced a profound shortage of trained human resources and medical supplies. They can significantly contribute to health services if they are adequately equipped and follow standardized operation procedures.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".