Knowledge, attitudes and practices of the general population towards Marburg virus disease in sub-Saharan African countries: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Marburg virus disease (MVD) is categorized among viral hemorrhagic fevers. MVD is associated with high rates of morbidity and mortality. This study aimed to identify factors affecting MVD knowledge, attitudes and practices in sub-Saharan African countries. METHODS: Using a validated questionnaire, a cross-sectional survey was conducted from 21 April to 23 May 2023 in eight English-speaking sub-Saharan African countries (Ethiopia, Ghana, Kenya, Lesotho, Nigeria, Senegal, South Africa and Tanzania). RESULTS: Of 3142 participants, 51% were males, 66.0% were aged 18-29 y, 74.4% were living in urban areas, 47.9% completed their university education and 21.7% were healthcare workers (HCWs). Tanzanians had the highest good knowledge (89%), while Kenyans had the lowest (26%). Tanzanians had the highest positive attitude (82%), while Nigerians had the highest negative attitude (95%). The best practices exhibited were by Ethiopians (70%), and the poorest practices exhibited were by Ghanaians (94%). The predictors of good knowledge were marital status (adjusted OR [aOR]=0.75; 95% CI 0.59 to 0.94; p=0.013), knowing the correct mode of transmission (aOR=18.31; 95% CI 13.31 to 25.66; p<0.001), whether the participant has heard before about MVD (aOR=2.24; 95% CI 1.82 to 2.75; p<0.001), whether they modified their working habits (aOR=2.79; 95% CI 2.12 to 3.67; p<0.001), nationality (p<0.001) and being a HCW (aOR=2.71; 95% CI 2.01 to 3.67; p<0.001). The predictors of good attitude were being female (aOR=0.71; 95% CI 0.60 to 0.85; p<0.001), age (aOR=0.99; 95% CI 0.98 to 0.99; p=0.01), place of residence (aOR=3.13; 95% CI 2.46 to 3.99; p<0.001), level of education (aOR=1.67; 95% CI 1.37 to 2.04; p<0.001), knowing the correct mode of transmission (aOR=1.59; 95% CI 1.28 to 1.98; p<0.001), modification of working habits (aOR=1.30; 95% CI 1.01 to 1.68; p=0.039) and nationality (p<0.001). The predictors of practice were being female (aOR=1.17; 95% CI 1.01 to 1.37; p=0.042), place of residence (aOR=1.23; 95% CI 1.02 to 1.48; p=0.033), marital status (aOR=0.65; 95% CI 0.55 to 0.78; p<0.001), knowing the correct mode of transmission (aOR=0.46; 95% CI 0.38 to 0.56; p<0.001), modification of working habits (aOR=0.40; 95% CI 0.32 to 0.49; p<0.001) and occupation (aOR=0.37; 95% CI 0.30 to 0.46; p<0.001). CONCLUSIONS: Different modifiable and non-modifiable risk factors can be targeted to improve population perspectives towards MVD.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".