Prevalence, incidence, and trends of epilepsy among children and adolescents in Africa: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Epilepsy contributes to a significant disease burden in children and adolescents worldwide. The incidence of childhood epilepsy is threefold higher in low and middle income countries compared in high-income countries. Epilepsy is a serious neurological condition associated with stigma and discrimination, an impaired quality of life, and other mental health related problems. Objective This study is aimed to synthesize existing evidence and estimate the pooled prevalence and incidence of epilepsy in children and adolescents in Africa. Methods A comprehensive and systematic search of relevant databases was conducted. The quality of each study was assessed using the Newcastle-Ottawa Quality Assessment Scale adapted for meta-analysis. Two reviewers screened retrieved articles, conducted critical appraisals, and extracted the data. Heterogeneity between studies was assessed by visual inspection of forest plots and statistically using Cochran’s Q statistics and the I 2 test. Publication bias was checked by visual inspection of funnel plots as well as statistically using Egger’s correlation and Begg’s regression tests. Finally, the pooled prevalence and incidence of childhood epilepsy were computed with 95% confidence intervals. Result In this review and meta-analysis 42 studies with 56 findings were included to compute the pooled prevalence of childhood epilepsy. On the other hand, 6 studies were included to estimate the combined incidence. The pooled prevalence of cumulative epilepsy was 17.3 per 1000 children. Whereas the pooled prevalence of active and lifetime epilepsy was 6.8 and 18.6 per 1000 children respectively. The pooled incidence of childhood epilepsy was 2.5 per 1000 children. Conclusion Nearly 1 in 50 children are suffering from epilepsy in Africa. However, little attention has been paid to the prevention and treatment of childhood epilepsy. Mass epilepsy screening, scaling up treatment coverage, and designing strict treatment follow up and monitoring mechanisms are recommended.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".