Assessment of Water, Sanitation and Hygiene (WASH) within Healthcare Facilities in Selected Eastern Mediterranean Countries
Bibliographic record
Abstract
Background: Inadequate drinking water, sanitation, and hygiene (WASH) in health care facilities impacts the health, particularly in low and middle-income countries. There is limited knowledge on the status of WASH in such settings. Objective: The primary objective of this study was to assess WASH conditions in health care facilities in four EM countries; Jordan, Morocco, Lebanon, and Pakistan. Methods: This study was based on secondary data analysis of the regional study on WASH services in health facilities. Separate samples of health care facilities were selected from Jordan (19 hospitals), Morocco (8 hospitals), Lebanon (14 hospitals), and Pakistan (8 hospitals) and were assessed using the WHO/CEHA tool WSH in the health facilities assessment tool. The assessment tool consisted of items to assess the WSH services availability, adequacy, and functionality. Results: All health care facilities (100%) in Jordan and Morocco, 71.4% of hospitals in Lebanon and none of the hospitals in Pakistan had a safe water source. Overall, all hospitals in Jordan, Morocco, and Lebanon and 71.4 % of hospitals in Pakistan had improved and gender separated toilets in inpatients settings (One per 20 users). About 84.2% of hospitals in Jordan, none in Morocco, 28.6% in Lebanon, and all hospitals in Pakistan had sufficient improved and gender separated toilets in outpatients setting. Overall, 84.2% of hospitals had sufficient and functioning handwashing basins with soap and water and 79.0% of hospitals had sufficient showers. The majority of hospitals in the selected countries have a policy for the safe management of healthcare waste but inadequate training program on healthcare waste. Conclusions: WASH services are not well implemented in health care facilities of the selected countries. The countries have to develop and implement a monitoring system for WASH services or at least support inclusion of WASH services in routine monitoring of health care services.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".