Background: Efforts 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.

Methods: Over 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.

Results: Communities 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8324202PMC
http://dx.doi.org/10.9745/GHSP-D-21-00144DOI Listing

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