Social resistance drives persistent transmission of Ebola virus disease in Eastern Democratic Republic of Congo: A mixed-methods study
Bibliographic record
Abstract
BACKGROUND: The second largest Ebola virus disease (EVD) epidemic in history is currently raging in Eastern Democratic Republic of Congo (DRC). Stubbornly persistent EVD transmission has been associated with social resistance, ranging from passive non-compliance to overt acts of aggression toward EVD reponse teams. METHODS: We explored community resistance using focus group discussions and assessed the prevalence of resistant views using standardized questionnaires. RESULTS: Despite being generally cooperative and appreciative of the EVD response (led by the government of DRC with support from the international community), focus group participants provided eyewitness accounts of aggressive resistance to control efforts, consistent with recent media reports. Mistrust of EVD response teams was fueled by perceived inadequacies of the response effort ("herd medicine"), suspicion of mercenary motives, and violation of cultural burial mores ("makeshift plastic morgue"). Survey questionnaires found that the majority of respondents had compliant attitudes with respect to EVD control. Nonetheless, 78/630 (12%) respondents believed that EVD was fabricated and did not exist in the area, 482/630 (72%) were dissatisfied with or mistrustful of the EVD response, and 60/630 (9%) sympathized with perpetrators of overt hostility. Furthermore, 102/630 (15%) expressed non-compliant intentions in the case of EVD illness or death in a family member, including hiding from the health authorities, touching the body, or refusing to welcome an official burial team. Denial of the biomedical discourse and dissatisfaction/mistrust of the EVD response were statistically significantly associated with indicators of social resistance. CONCLUSIONS: We concluded that social resistance to EVD control efforts was prevalent among focus group and survey participants. Mistrust, with deep political and historical roots in this area besieged by chronic violence and neglected by the outside world, may fuel social resistance. Resistant attitudes may be refractory to short-lived community engagement efforts targeting the epidemic but not the broader humanitarian crisis in Eastern DRC.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".