Supplementary material from: Burden of Shigella among children with diarrhea in the Americas: A systematic review and meta-analysis
Bibliographic record
Abstract
Introduction: Shigella infection is a leading cause of diarrhea worldwide. While the burden of Shigella has been shown to be highest in Africa and Asia, recent studies have also shown considerable burden in the Americas. With several pediatric Shigella vaccines in clinical development, policymakers in the region will eventually consider whether a Shigella vaccine is appropriate for their setting. Methods: We conducted a systematic review and meta-analyses to summarize the burden (characterized by prevalence, incidence, and attributable fraction estimates) of Shigella diarrhea among children under 72 months in the Americas, excluding the U.S., Canada, and Greenland. We searched published and pre-print articles available in six databases from January 1, 2000 through July 23, 2024. Random effects meta-analyses were conducted for subgroups of interest when relevant data from at least two studies were present. Results: This review included 34 studies conducted across 14 countries in the region. Prevalence was most frequently reported, followed by incidence, then attributable fraction. Across all prevalence studies that used a culture detection method (n=23), the pooled prevalence of Shigella among diarrhea cases was 3.1% (95% CI: 1.6- 5.8). The pooled prevalence among 12 studies that used PCR/qPCR detection methods was 16.5% (95% CI: 11.1-24.0). Among culture-based results, the pooled prevalence estimate for children <12 months was 1.0% (95% CI: 0.1 – 7.7) compared to 4.6% (95% CI: 1.2 – 15.4) for children ≥12 months. Conclusion: Despite varying reporting practices, we found Shigella to be an important contributor to diarrhea in many settings in the Americas with substantial heterogeneity. Limited geographic representation and variable reporting of age group specific estimates were the major gaps in data. Investment in Shigella surveillance in the Americas using a standardized methodology can contribute to accelerating Shigella vaccine development in consideration of regional preferences and optimal age of introduction.
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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 | 0.006 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.012 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.132 | 0.005 |
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".