ArticleBMC emergency medicine2022
Perspectives on deployment of humanitarian workers through operational partnerships during the acute emergency health response to the Rohingya refugee crisis in Cox's Bazar.
Article in BMC emergency medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Evolution of the humanitarian roster system for sexual and reproductive health.Sexual and reproductive health matters · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundThe unprecedented influx of Rohingya refugees into Cox's Bazar, Bangladesh, in 2017 led to a humanitarian emergency requiring large numbers of humanitarian workers to be deployed to the region. The World Health Organization (WHO) contributed to this effort through well-established deployment mechanisms: the Global Outbreak Alert and Response Network (GOARN) and the Standby Partnerships (SBP). The study captures the views and experiences of those humanitarian workers deployed by WHO through operational partnerships between December 2017 and February 2019 with the purpose of identifying challenges and good practice during the deployment process, and steps to their improvement.
methodsA mixed methods design was used. A desktop review was conducted to describe the demographics of the humanitarian workers deployed to Cox's Bazar and the work that was undertaken. Interviews were conducted with a subset of the respondents to elicit their views relating to their experiences of working as part of the humanitarian response. Thematic analysis was used to identify key themes.
resultsWe identified sixty-five deployments during the study period. Respondents' previous experience ranged between 3 and 28 years (mean 9.7 years). The duration of deployment ranged from 8 to 278 days (mean 67 days) and there was a higher representation of workers from Western Pacific and European regions. Forty-one interviews were conducted with people who experienced differing aspects of the deployment process. Key themes elicited from interviews related to staffing, the deployment process, the office environment and capacity building. Various issues raised have since been addressed, including the establishment of a sub-office structure, introduction of online training prior to deployment, and a staff wellbeing committee.
conclusionsThis study identified successes and areas for improvement for deployments during emergencies. The themes and subthemes elicited can be used to inform policy and practice changes, as well as the development of performance indicators. Common findings between this study and previous literature indicate the pivotal role of staff deployments through partnership agreements during health emergency response operations and a need for continuous improvements of processes to ensure maximum effectiveness.
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.