ReviewInternational journal of disaster risk reduction : IJDRR2020
Instructions for planning emergency shelters and open spaces in China: Lessons from global experiences and expertise.
Review in International journal of disaster risk reduction : IJDRR, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Epidemic and Pandemic Preparedness and Response in a Multi-Hazard Context: COVID-19 Pandemic as a Point of Reference.International journal of environmental research and public health · 2024Pooled it
- Challenges and opportunities in designing innovative emergency-evacuation equipment for bed-dependent hospital patients: a scoping review with a focus on evacuation mattresses and stretchers.BMC emergency medicine · 2026Article
- The initial response of a local hospital in the earthquake zone during the February 6, 2023 Kahramanmaraş earthquakes: Injuries and challenges.Acta orthopaedica et traumatologica turcica · 2023Article
- How have governments supported citizens stranded abroad due to COVID-19 travel restrictions? A comparative analysis of the financial and health support in eleven countries.BMC infectious diseases · 2022Article
- Measuring spatial accessibility to refuge green space after earthquakes: A case study of Nanjing, China.PloS one · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Emergency shelters and open spaces play dual roles in providing locations for temporary accommodation and rescue activities during disaster situations. Over time, research has attempted to optimize site selection and design for emergency shelters and open spaces, though they rarely offered lessons to guide actual projects. In this regard, it is paramount to design emergency shelters or open spaces in a forward-looking and dynamic manner, especially when the country faces challenges due to extreme events (e.g. earthquake and floods) and large populations. The aim of this paper is to analyze the issues of this field in China while summarizing instructions for future construction based on the experience and expertise of other countries. Specific suggestions include: (1) combining the designs and plans of emergency shelters/open spaces into the construction of a resilient urban system; (2) embedding routine preparedness into disaster risk reduction approaches; (3) optimizing issues in site-selection using spatiotemporal patterns in refuge demand while designing the shelter system into a hierarchical structure; (4) shifting from a top-down approach to a bottom-up approach, which includes the participation of multiple aspects of shelter construction; and (5) designing and establishing emergency shelters/open spaces to fight against different types of disasters.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.