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

BMJ Glob Health. 2022 Feb;7(2):e005971. doi: 10.1136/bmjgh-2021-005971.

Abstract

Introduction: The 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.

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

Methods: Qualitative 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.

Findings: The 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.

Conclusion: CF 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.

Keywords: epidemiology; health policy; qualitative study; viral haemorrhagic fevers.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Democratic Republic of the Congo / epidemiology
  • Epidemics*
  • Feedback
  • Hemorrhagic Fever, Ebola* / epidemiology
  • Humans