Typhoidal Salmonella Trends in Thailand
Bibliographic record
Abstract
Typhoid and paratyphoid fever remain endemic diseases in Thailand with wide variation in subnational incidence trends. We examined these trends alongside contextual factors to study potential interactions and guide control strategies for this disease. Culture-confirmed typhoid and paratyphoid fever data from 2003 to 2014 were collected from the Ministry of Public Health website. Contextual factor data were collected from various sources including World Health Organization/United Nations Children's Fund Joint Monitoring Program, United Education Statistical World Bank database, World Bank, Development Research group, and global child mortality estimates published in the Lancet. Typhoid fever exhibited a declining trend with peak incidence reported in 2003 at 8.6 cases per 100,000 persons per year. Incidence dropped to three cases per 100,000 persons in 2014. The trend in paratyphoid fever remained stable with the peak incidence of 0.77 cases per 100,000 persons observed in 2009. Subnational variations of typhoid were seen throughout the study period with the highest incidence observed in the northwestern region of Thailand. Increases in female literacy, and access to improved water and sanitation were observed with decreases in poverty head count ratio and diarrheal mortality rate per 1,000 live births. Case fatality remained consistently low at 0.4% or less in all years with reported deaths. At the national level, typhoid fever incidence has shown a notable decline; however, incidence appears to have plateaued since 2007 with access to improved water supply and sanitation above 80%. Eliminating this disease will require strong disease prevention measures in conjunction with effective treatment interventions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".