Understanding knowledge, attitudes and practices on Ebola Virus Disease: a multi-site mixed methods survey on preparedness in Rwanda
Bibliographic record
Abstract
BACKGROUND: The overall goal of this survey was to understand the knowledge, attitudes, and practices related to the Ebola Virus Disease (EVD) in Rwanda. METHODS: This mixed-method cross-sectional survey was conducted in five selected districts of Rwanda. Quantitative data were collected from 1,010 participants using Kobo Collect Software and the analysis was performed using SPSS and Python software. Qualitative data were specifically collected from 98 participants through Key Informant Interviews (KIIs) and Focus Group Discussion (FGDs). Interview transcripts were imported into NVIVO 8 for coding and subsequent analysis. RESULTS: As per our quantitative findings, we report that from the 1,010 respondents, 99.6% reported having previously heard of Ebola, 97.2% believed that vaccination is important in combatting the disease and 93.3% of individuals reported a willingness to receive vaccination should one become available. Around 54% of the respondents were correct in identifying that the disease is of a viral origin which originates from wild animals (42.1%). When asked if they believed that Rwanda is at risk of an EVD outbreak, 90% of the respondents believe that the country is at risk of an EVD outbreak, and the cofactors *gender* and *whether people dwell in Rubavu/Rusizi* were found to significantly impact their perception of threat. As per our qualitative findings, the respondents mentioned that both geographical proximity and relations with the Democratic Republic of Congo place Rwanda at risk of developing an internal outbreak. Although the respondents seemed to be aware of the Ebola prevention behaviours, it was noted that some of them will require significant time before reintegrating into the community an EVD survivor, as they will first need assurance that the patient has fully recovered. Therefore, the qualitative findings reinforce what we originally reported in the quantitative approach to this study. CONCLUSION: Our results show that there was high EVD-related knowledge and awareness among the general population in Rwanda. However, for strong public health awareness, preparedness, and protection, a massive investment should always be made in education about EVD with a special focus on districts neighboring countries where the disease is consistently being reported.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".