Evidence map›Paper›PMID 35197250›Full record

ArticleBMJ global health2022

The response is like a big ship': community feedback as a case study of evidence uptake and use in the 2018-2020 Ebola epidemic in the Democratic Republic of the Congo.

Gillian McKay, Ombretta Baggio, Cheick Abdoulaye Camara, Eva Erlach, Lucia Robles Dios, Francesco Checchi, Hana Rohan

Open access · goldAbstract read
In one paragraph

Article in BMJ global health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 24% of its field
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

5 citing papers in PubMed, 10 citations in OpenAlex.

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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

7 authors at 2 institutions in 2 countries.

Gillian McKayDepartment of Global Health and Development, The London School of Hygiene and Tropical Medicine, London, UK gillian.mckay@lshtm.ac.uk.
Ombretta BaggioThe International Federation of Red Cross and Red Crescent Societies, Geneva, Switzerland.
Cheick Abdoulaye CamaraInternational Federation of Red Cross and Red Crescent Societies, Conakry, Guinea.
Eva ErlachThe International Federation of Red Cross and Red Crescent Societies, Geneva, Switzerland.
Lucia Robles DiosThe International Federation of the Red Cross and Red Crescent Societies, Goma, Democratic Republic of the Congo.
Francesco ChecchiDepartment of Infectious Disease Epidemiology, The London School of Hygiene and Tropical Medicine, London, UK.
Hana RohanUK Public Health Rapid Support Team, The London School of Hygiene and Tropical Medicine, London, UK.
International Federation of Red Cross and Red Crescent Societies · CHLondon School of Hygiene & Tropical Medicine · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

introductionThe 2018-2020 Ebola outbreak in the Democratic Republic of the Congo (DRC) took place in the highly complex protracted crisis regions of North Kivu and Ituri. The Red Cross developed a community feedback (CF) data collection process through the work of hundreds of Red Cross personnel, who gathered unprompted feedback in order to inform the response coordination mechanism and decision-making.

aimTo understand how a new CF system was used to make operational and strategic decisions by Ebola response leadership.

methodsQualitative data collection in November 2019 in Goma and Beni (DRC), including document review, observation of meetings and CF activities, key informant interviews and focus group discussions.

findingsThe credibility and use of different evidence types was affected by the experiential and academic backgrounds of the consumers of that evidence. Ebola response decision-makers were often medics or epidemiologists who tended to view quantitative evidence as having more rigour than qualitative evidence. The process of taking in and using evidence in the Ebola response was affected by decision-makers' bandwidth to parse large volumes of data coming from a range of different sources. The operationalisation of those data into decisions was hampered by the size of the response and an associated reduction in agility to new evidence.

conclusionCF data collection has both instrumental and intrinsic value for outbreak response and should be normalised as a critical data stream; however, a failure to act on those data can further frustrate communities.

Indexed as

EpidemicsHemorrhagic Fever, EbolaDemocratic Republic of the CongoFeedbackHumansepidemiologyhealth policyqualitative studyviral haemorrhagic fevers

Identifiers

PMID35197250
PMCPMC8867249
OpenAlexW4213266688

What OpenQuestion holds

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LicenceCC BY-NC
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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.