Evaluation of the Influence of Gastrointestinal Coinfections on Rotavirus Vaccine Effectiveness in Botswana
Bibliographic record
Abstract
BACKGROUND: Studies have demonstrated reduced rotavirus vaccine effectiveness (VE) in resource-limited settings. Enteropathogen coinfections in rotavirus cases have been hypothesized to contribute to the lower VE in such settings. We sought to determine if coinfections affect rotavirus VE in Botswana. METHODS: Between June 2013 and April 2015, children <60 months old, presenting with severe gastroenteritis at 4 hospitals as part of a national rotavirus surveillance were enrolled. Rotavirus enzyme immunoassay (EIA)-positive samples were tested with an in-house real-time polymerase chain reaction (PCR) panel that detected 9 pathogens and a commercial 15 multiplex PCR gastrointestinal pathogen panel. Coinfection was defined as detection of rotavirus plus 1 of the 5 pathogens with the highest attributable fractions for diarrhea. Vaccine status was compared between rotavirus case patients and non-rotavirus "test-negative" controls. VE was also calculated restricting cases to those with rotavirus as the only pathogen detected. RESULTS: Two hundred and forty-two children tested rotavirus EIA positive, and 368 children were negative. Of the 182 rotavirus EIA-positive samples tested with the gastrointestinal pathogen panel assay, coinfections were detected in 60 (33%). The overall adjusted 2-dose VE was 59% (95% confidence interval [CI]: 27-77) in the rotavirus coinfection group and 51% (95% CI: -14 to 79) in the rotavirus monoinfection subgroup. Using in-house multiplex PCR panel, of 213 rotavirus EIA-positive subjects, coinfections were detected in 98 samples (46%). The overall adjusted VEs for 2 doses were 48% (95% CI: -2 to 74) and 62% (95% CI: 25-80) in rotavirus monoinfection subgroup. CONCLUSIONS: We could not find evidence of an effect of enteric coinfections on the effectiveness of rotavirus vaccine.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".