Leveraging paired serology to estimate the incidence of typhoidal <i>Salmonella</i> infection in the STRATAA study
Bibliographic record
Abstract
Abstract Serologic surveillance of at-risk populations can be used to directly estimate the incidence of typhoidal Salmonella infection across a variety of settings, including those without access to facility-based blood-culture surveillance. We collected paired blood samples approximately three months apart from an age-stratified random sample of healthy children and adults in Bangladesh, Malawi, and Nepal as part of the Strategic Typhoid Alliance Across Asia and Africa (STRATAA) study. We used a multiplex bead assay to measure the concentration of IgG antibodies against seven Salmonella typhi/paratyphi antigens (CdtB, FliC, HlyE, LPSO2, LPSO9, Vi, and YncE) in each sample and identified recently infected participants by fitting a regression mixture model to the change in IgG concentration between participants’ samples. We estimated the seroincidence of infection in a Bayesian framework for each study site, age group, and antigen target. Finally, we compared the seroincidence estimates with crude and adjusted estimates of clinical incidence based on blood-culture surveillance. Seroincidence estimates were significantly higher than enteric fever incidence across all study sites, age groups, and antigen targets, even after adjusting for underreporting (median ratio: 25.4, interquartile range: 20.2-50.7). Seroincidence consistently peaked in the 0-4-year age group and declined moderately between children and adults (34% to 56% decline in HlyE seroincidence between the 5-9 and 30+ year old age groups), while enteric fever incidence peaked in older children and fell sharply in adults (71% to 95% decline in adjusted clinical incidence). Seroincidence estimates based on the HlyE and YncE antigens individually had the strongest correlation with observed enteric fever incidence across age groups and study sites (r = 0.63 and 0.71, respectively). These findings suggest that in endemic settings, both children and adults are frequently infected by typhoidal Salmonella serotypes, although only a fraction of these infections present as clinically identifiable enteric fever cases.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".