Malaria Prevalence and Associated Risk Factors among Batwa Indigenous People of Kanungu District in Southwestern Uganda: Does “Place” Matter?
Bibliographic record
Abstract
Introduction: Malaria is an important disease, causing high morbidity and mortality, especially in Sub-Saharan Africa. Measuring malaria prevalence using malaria rapid diagnostic tests (mRDTs), particularly among a vulnerable population sub-group, is a vital public health step in discovering effective methods of prevention and control. This study set out to examine the association between “place” and other risk factors with malaria prevalence among Batwa Indigenous People (IP). Methods: An analytical cross-sectional study design was implemented. Two surveys January 2014 (n = 572) and April 2014 (n = 541) involving interviews and testing for malaria using mRDTs were conducted in 10 Batwa settlements where a total of 1113 Batwa of all ages were surveyed and tested. The data were first compiled in MS Excel and then imported and analyzed using STATA ver.14. Descriptive statistics, were generated, followed by bivariable and multivariable regression model analysis to establish associations between the predictor and outcome variables with p ≤ 0.05 considered statistically significant. Results: Overall prevalence was 13.94% (n = 146). There is a significant relationship between settlement (place) and malaria prevalence AOR 11.7, 95% CI (1.38 - 98.93), p-value = 0.02. More males 16.97% (n = 84) tested positive compared to females 11.23% (n = 62) but there was no statistically significant association between gender and mRDT (p-value > 0.005). Children less than 5 years registered high prevalence and there was a significant relationship between age and mRDT (p-value ≤ 0.005). Wealth proxy indicators showed no association with prevalence p-value = 0.390. Season had no association with prevalence (p-value = 0.80). However, the proportion of the day spent in the forest/woodlands was significantly associated with malaria prevalence COR 12.83, 95% CI (1.14 - 143.73) p-value = 0.04. Low elevation was significantly associated with malaria prevalence COR 2.42, 95% CI (1.32 - 4.41), p = 0.004 but sleeping under a net and level of education did not show any association with malaria prevalence. Conclusion: This study highlights the importance of place in predicting malaria prevalence among Batwa Indigenous People a marginalized and remortely located sub-population. This study has shown that place matters in determining malaria prevalence. However, other factors like age, elevation and gender also contribute to malaria prevalence. Batwa have higher prevalence than the national and even non-indigenous populations in the same district. We recommend targeting hotspots intervention approach since it has proven reasonable impact on reducing malaria prevalence.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".