Prevalence and Risk Factors of Human Leishmaniasis in Ethiopia: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Tropical diseases are public health problems affecting hundreds of millions of people globally. However, the development of adequate, affordable, and accessible treatments is mostly neglected, resulting in significant morbidity and mortality that could otherwise be averted. Leishmaniasis is one of the neglected tropical diseases caused by the obligate intracellular protozoan Leishmania parasite and transmitted by the bite of infected phlebotomine sandflies. No systematic review and meta-analysis has been done to identify the prevalence and risk factors of leishmaniasis to the authors’ knowledge. Therefore, the objective was to determine the prevalence and risk factors of human leishmaniasis in Ethiopia. Eleven studies conducted in all regions of Ethiopia, which were fully accessible, written in any language, and original articles done on prevalence and risk factors of leishmaniasis, were included. STATA™ version 11.1 was used for statistical analysis. Chi-square, I 2 , and p values were assessed to check heterogeneity. A random effects model with heterogeneity taken from an inverse-variance model was employed to estimate the pooled effect. Subgroup meta-analysis was computed to reduce random variations among each article’s point prevalence, and Egger and funnel plots were used to check for publication bias. The highest proportion of human leishmaniasis was reported from a study done in Amhara region (39.1%), and the lowest was reported from a survey done in Tigray (2.3%). The overall pooled prevalence of leishmaniasis was 9.13% (95% CI 5–13.27). Subgroup analysis by region revealed moderate heterogeneity ( I 2 = 51.8%) in studies conducted in the Southern Nations Nationalities and Peoples Region (SNNPR). The presence of hyraxes and being male were associated with an increased risk of human leishmaniasis. The prevalence of leishmaniasis in Ethiopia remains high (9.13%), with significant risk factors being male and the presence of hyraxes within a 300-m radius of the sleeping 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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.035 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".