Global Trends in Typhoidal Salmonellosis: A Systematic Review
Bibliographic record
Abstract
Typhoid and paratyphoid fever continue to significantly contribute to global morbidity and mortality. Disease burden is higher in low-and middle-income settings where surveillance programs are rare and little systematic information exists at population level. This review evaluates national, regional, and global trends in the incidence of typhoid fever and of related morbidity and mortality. A literature search in Medline, Embase, and Web of Science was conducted in June 2016, followed by screening and data extraction in duplicate. Studies reporting blood culture estimates of typhoid or paratyphoid morbidity and mortality were included in the analysis. Our search yielded 5,563 unique records, of which 1978 were assessed for relevance with 219 records meeting the eligibility criteria. Salmonella enterica serotype Typhi was the most commonly reported organism (91%), with the occurrence of typhoidal Salmonella (either incidence or prevalence) being the most commonly reported outcome (78%), followed by typhoid fever mortality, ileal perforation morbidity, and perforation mortality, respectively. Fewer than 50% of studies stratified outcomes by age or urban/rural locality. Surveillance data were available from 29 countries and patient-focused studies were available from 32 countries. Our review presents a mixed picture with declines reported in many regions and settings but with large gaps in surveillance and published data. Regional trends show generally high incidence rates in South Asia, sub-Saharan Africa, and East Asia and Pacific where the disease is endemic in many countries. Significant increases have been reported in certain countries but should be explored in the context of long-term trends and underlying at-risk populations.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.016 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".