Evidence map›Paper›PMID 34234025›Full record

ArticleGlobal health, science and practice2021

New Mixed Methods Approach for Monitoring Community Perceptions of Ebola and Response Efforts in the Democratic Republic of the Congo.

Giulia Earle-Richardson, Eva Erlach, Vivienne Walz, Ombretta Baggio, Molly Kurnit, Cheick Abdoulaye Camara, Christina Craig, Lucia Robles Dios, Daiva Yee, Gnakub Norbert Soke and 2 more

Open access · diamondAbstract read
In one paragraph

Article in Global health, science and practice, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.7field-weighted citation impact, top 27% 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

8 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. 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

12 authors at 2 institutions in 2 countries.

Giulia Earle-RichardsonCenters for Disease Control and Prevention, Atlanta, GA, USA. evy8@cdc.gov.
Eva ErlachInternational Federation of the Red Cross and Red Crescent Societies, Geneva, Switzerland.
Vivienne WalzCenters for Disease Control and Prevention, Atlanta, GA, USA.
Ombretta BaggioInternational Federation of the Red Cross and Red Crescent Societies, Geneva, Switzerland.
Molly KurnitCenters for Disease Control and Prevention, Atlanta, GA, USA.
Cheick Abdoulaye CamaraInternational Federation of the Red Cross and Red Crescent Societies, Geneva, Switzerland.
Christina CraigCenters for Disease Control and Prevention, Atlanta, GA, USA.
Lucia Robles DiosInternational Federation of the Red Cross and Red Crescent Societies, Geneva, Switzerland.
Daiva YeeCenters for Disease Control and Prevention, Atlanta, GA, USA.
Gnakub Norbert SokeCenters for Disease Control and Prevention, Atlanta, GA, USA.
Ialijaona VoaharyInternational Federation of the Red Cross and Red Crescent Societies, Geneva, Switzerland.
Christine E PrueCenters for Disease Control and Prevention, Atlanta, GA, USA.
Centers for Disease Control and Prevention · USInternational Federation of Red Cross and Red Crescent Societies · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEfforts to contain the spread of Ebola in the eastern Democratic Republic of the Congo (DRC) during the 2018-2020 epidemic faced challenges in gaining community trust and participation. This affected implementation of community alerts, early isolation, contact tracing, vaccination, and safe and dignified burials. To quickly understand community perspectives and improve community engagement, collaborators from the DRC Red Cross, the International Federation of the Red Cross, and the U.S. Centers for Disease Control and Prevention explored a new method of collecting, coding, and quickly analyzing community feedback.

methodsOver 800 DRC Red Cross local volunteers recorded unstructured, free-text questions and comments from community members during community Ebola awareness activities. Comments were coded and analyzed using a text-coding system developed by the collaborators. Coded comments were then aggregated and qualitatively grouped into major themes, and time trends were examined.

resultsCommunities reported a lack of information about the outbreak and the response, as well as concerns about the Ebola vaccination program and health care quality. Some doubted that Ebola was real. The response used the feedback to revise some community engagement approaches. For example, 2 procedural changes that were followed by drops in negative community responses were: using transparent body bags, which allayed fears that bodies or organs were being stolen, and widening the eligibility criteria for Ebola vaccination, which addressed concerns that selectively vaccinating individuals within Ebola-affected communities was unfair. DISCUSSION: This system is unique in that unstructured feedback collected by local volunteers in the course of their work was rapidly coded, analyzed, and given to health authorities for use in making course corrections throughout the response. It provides a platform for local voices to be heard throughout an emergency response and provides a mechanism for assessing the effects of program adjustments on community sentiments.

Indexed as

EpidemicsHemorrhagic Fever, EbolaDemocratic Republic of the CongoDisease OutbreaksHumansPerception

Identifiers

PMID34234025
PMCPMC8324202
OpenAlexW3180504426

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.