Evidence map›Paper›PMID 36345472›Full record

ReviewGeoenvironmental disasters2022

A state-of-the-art examination of disaster management in Sierra Leone: the implementation drawbacks, research gaps, advances, and prospects.

Bashiru Turay, Sheku Gbetuwa

Abstract readReview
In one paragraph

Review in Geoenvironmental disasters, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Bashiru TurayDepartment of Geography, University of Bonn, Bonn, Germany.ORCID 0000-0002-2128-9881
Sheku GbetuwaInstitute of Geography and Development Studies, School of Environmental Sciences, Njala University, Moyamba, Sierra Leone.ORCID 0000-0003-2515-7322

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unfolding events have shown that Sierra Leone is enduring various disasters at a worrying rate. While progress is being made in disaster management, activities that degrade the fragile ecosystem, exacerbated by climate change, poverty, and bad governance, remain growing concerns. Amid these concerns, there is inadequate information to take appropriate actions. The authors wish to provide a solution by examining 35 publications from various scholarly and grey literature and raw data sources, following a critical review process designed to expose the implementation drawbacks, research gaps, advances, and prospects in disaster management in Sierra Leone. The study results show that lapses in data management, fewer professionals, and inefficiencies in communication are the most pressing considerations for improving disaster management in the country. Inadequate funds to implement management plans remain pervasive. Following these findings, we recommend that all first responders be routinely exposed to international tabletop exercises and simulated disaster response training to help them build their capacities and learn from other countries. Students in the relevant disciplines should be encouraged to participate in these exercises to facilitate early learning. Also, management initiatives should consider gender equity, the situations of the disabled, and other vulnerable groups at all levels of planning and implementation of activities. Future studies should assess the influence of social media on disaster management research and practice in the country.

Indexed as

Climate changeDisaster managementGovernmentHazardsRisksSierra Leone

Identifiers

PMID36345472
PMCPMC9631602

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.