Use and disuse of malaria bed nets in an internally displaced persons camp in the Democratic Republic of the Congo: A mixed-methods study
Bibliographic record
Abstract
INTRODUCTION: Malaria is a major cause of morbidity and mortality among displaced populations in tropical zones. Bed nets are widely used to prevent malaria; however, few data are available on bed net distribution within displaced populations. METHODS: Mixed methods study in a single internally displaced persons (IDP) camp and neighboring community in Eastern Democratic Republic of the Congo (DRC). Qualitative data (focus group discussions, FGDs) and quantitative data (door-to-door survey and individual testing using malaria rapid diagnostic test, RDT) were collected. RESULTS: Ten FGDs were conducted with 55 individuals. Although malaria was widely recognized as a significant threat and bed nets were freely distributed in the camp, many households did not own or use them. IDPs converged on the following reasons for low bed net ownership and use: inconvenience of net installation and sale of nets to meet immediate needs such as food. One hundred households, comprised of 411 individuals, were surveyed in Birambizo. The burden of malaria was high (45/78 (58%) of children <5 were positive for malaria by RDT) and bed net utilization was low (29/100 (29%) households owned a bed net, and 85/411 (20%) individuals slept under a bed net the previous night). Children <5 were more likely to use a bed net than older children or adults (OR 3.4 (95%CI 2.0-5.8), p<0.0001). Compared to 29 bed nets currently in use by study participants, 146 bed nets had been sold (82%) or exchanged (18%) either in the camp (27%) or in the neighbouring village market (73%). CONCLUSIONS: Qualitative descriptions and quantitative analysis revealed pragmatic barriers to bed net usage and widespread sale of freely distributed bed nets within IDP camps, despite a high burden of malaria. Additional strategies, beyond bed net distribution, are warranted to combat malaria in vulnerable and hard-to-reach population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".