Water supply emergency preparedness and response in health care facilities: A systematic review on international evidence
Bibliographic record
Abstract
Introduction: Enabling health care facilities to deal with impairments or outages of water supply and sewage systems is essential and particularly important in the face of growing risk levels due to climate change and natural hazards. Yet, comprehensive assessments of the existing preparedness and response measures, both in theory and practice, are lacking. The objective of this review is to assess water supply and wastewater management in health care facilities in emergency settings and low-resource contexts. It thereby is a first step toward knowledge transfer across different world regions and/or contexts. Method: A systematic review was performed to identify published articles on the subject using online MEDLINE and Web of Science. The initial searches yielded a total of 1,845 records. Two independent reviewers screened identified records using selection criteria. A total of 39 relevant studies were identified. Descriptive analyses were used to summarize evidence of included studies. Results: back-up water storage tanks previously installed as part of disaster preparedness measures, and tanker trucks to complete were most used. Questions on how to improve existing technologies, their uptake, but also the supplementation by alternative measures remain unanswered. Only few guidelines and tools on emergency preparedness were identified, while multiple studies formulated theoretical recommendations to guide preparedness. Recovery planning was rarely discussed, despite many studies mentioning the importance of the reconstruction and restoration phases. Literature focus on recovery is mostly on technical aspects, while organizational ones are largely absent. Despite their key role for preparedness and response, citizens and patients' perspectives are hugely underrepresented. This fits into the bigger picture as communication, awareness raising and actor cooperation in general is addressed comparatively little. Discussion: Combining organizational and technical aspects, and intersecting theory and practice will be necessary to address existing gaps. Improving both, preparedness and response, is key to maintaining public health and providing primary care.
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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 | 0.012 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.018 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".