Prevalence and Determinants of Malaria Infection Among Children of local farmers in Central Malawi
Bibliographic record
Abstract
Abstract BackgroundMalaria is a leading cause of morbidity and mortality among children under five in Malawi. Children from rural areas of central Malawi have high burden of malaria morbidity compared to other regions. The goals of this study were to examine the prevalence and determinants of malaria infection among children in rural areas of Dowa district in central Malawi.Methods A multistage cross-sectional study design was used to systematically sample 523 child-mother dyads from postnatal clinics. The main outcome was child positive malaria diagnostic test during postnatal clinic health assessment. Logistic regressions were used to determine risk factors associated with malaria among children aged 2 to 59 months.Results The prevalence of malaria amongst children under five years was 35.4%. The results of multivariable analyses show that children of mothers who experienced recent intimate partner violence (IPV) were more likely to be diagnosed with malaria ( AOR : 1.88, 95% CI : 1.19-2.97; P = 0.007) than children of mothers who did not. Children of mothers who had no formal education were more likely to be diagnosed with malaria ( AOR : 2.77, 95% CI : 1.24-6.19; P = 0.013) than children of mothers who attained secondary education. In addition, children in the age range of 2 to 5 months, and 6 to 11 months were less likely to be diagnosed with malaria ( AOR :0.21, 95% CI: 0.10-0.46; P = 0.000 and AOR :0.43; 95% CI: 0.22-0.85; P = 0.016, respectively) than children in the age range of 24 to 59 months.Conclusion The study found that the prevalence of malaria infection among children in the study area was comparable to that of national level. We propose that malaria control programs among children should also take into account mothers without formal education, mothers with children aged 24 to 59 months, and mothers that are experiencing IPV in the area.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".