Protection, health seeking, or a laissez-passer: Participants’ decision-making in an EVD vaccine trial in the eastern Democratic Republic of the Congo
Bibliographic record
Abstract
During the 10th Ebola virus disease (EVD) epidemic in the eastern Democratic Republic of the Congo (DRC) (2018-2020), two experimental EVD vaccines were deployed in North Kivu. This province has been at the centre of conflict in the region for the last 25 years. Amidst ambivalence towards protracted foreign intervention and controversy about introducing two experimental vaccines, the existing literature has focused on mistrust and 'resistance' towards the Ebola response and vaccines. In this article, we examine why people in the eastern DRC did decide to volunteer for a trial of a second EVD vaccine in North Kivu, despite the controversy. Drawing on ethnographic observation, interviews, and focus groups with trial participants conducted between September 2020 and April 2021, we analyse three motivations for participating: protection, health seeking, and expectations surrounding travel requirements. We make three points. First, participation in vaccine trials may be understood locally to have advantages which have not been considered by the trial, because they go beyond medical considerations and are specific to a particular social setting. Second, despite much of the literature focusing on a causal relationship between rumours and 'vaccine hesitancy', some rumours may in fact encourage participation. Third, material objects associated with trial participation - such as participant vaccine cards - can hold social and political meaning beyond the confines of the vaccine clinic, and influence decisions surrounding participation. Empirical investigation of how medical interventions become entangled in political economies is essential to understanding the perceived functions of participation, and thus the reasons why people volunteer in clinical trials. Participants' narratives about their decision-making provide an insight into how international bioethical debates interact with, but may also stand apart from, the situated social and economic realities driving decision-making around clinical trials on the ground. This highlights the need for ethical approaches that foreground the political, social, and economic context.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".