Prevalence of schistosomiasis and its association with anemia in Ethiopia, 2024: a systematic review and meta‑analysis
Bibliographic record
Abstract
BACKGROUND: Schistosomiasis is a neglected tropical disease that affects over 250 million people, predominantly in impoverished communities, including those in Ethiopia. However, there is currently no available national data regarding its prevalence in Ethiopia or its potential association with anemia. METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-2020) guideline was followed in our study. A comprehensive search strategy was conducted using international databases (PUB Med, Embase, Scopus, and Science Direct) and websites (Google Scholar and Google) from their date of inception to April 22, 2024. The quality of the retrieved studies was assessed using an adapted version of the Newcastle-Ottawa Scale. Publication bias and statistical heterogeneity were statistically assessed. A random effects model was applied, and all analysis was performed with STATA 17 statistical software. RESULT: The prevalence of schistosomiasis was assessed in twelve studies with 5747 participants. S. mansoni was studied in 11 research papers, while S. hematobium was assessed in one study. Using a random effect model due to high heterogeneity (I2 = 98.46%; P < 0.001), the overall pooled prevalence of schistosomiasis in Ethiopia was 22% (95% CI: 14.3, 29.6). The prevalence of schistosomiasis was about two and a half times higher in rural settings (23%) (95% CI: 15, 31) than in urban areas (10%) (95% CI: 3, 17). The burden of schistosomiasis was 23% between 2020 and 2024, compared to 16% from 2015-2019, with a higher prevalence among pediatric age groups (22%) versus 14% in mixed pediatric and adult age groups. The magnitude of schistosomiasis for good and very good-quality papers was 22% and 17%, respectively. In all the subgroup analyses, there was considerable statistically significant heterogeneity. No study was found to evaluate the association of schistosomiasis with anemia. CONCLUSION: The study reveals Ethiopia's higher schistosomiasis prevalence. Rural areas have a high burden of schistosomiasis. No eligible study was found to evaluate the association of schistosomiasis with anemia. Therefore, prevention and control measures should focus on rural settings. TRIAL REGISTRATION: The registration number at PROSPERO is CRD42024538522.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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".