The Burden of Typhoid Fever in South Africa: The Potential Impact of Selected Interventions
Bibliographic record
Abstract
Typhoid fever is notifiable in South Africa but clinical notification is notoriously poor. South Africa has an estimated annual incidence rate of 0.1 cases per 100,000 population of culture-confirmed typhoid fever, decreased from 17 cases per 100,000 population in the 1980s. This work was undertaken to identify the reasons for this decrease and identify potential weaknesses that may result in an increase of observed cases. Culture-confirmed cases, with additional demographic and clinical data have been collected from selected sentinel sites since 2003. Data on contextual factors (gross domestic product [GDP], sanitation, female education, and childhood diarrhea mortality) were collected. National incidence rates of culture-confirmed typhoid fever have remained constant for the past 13 years, with the exception of an outbreak in 2005: incidence was 0.4 per 100,000 population. Paratyphoid fever remains a rare disease. Antimicrobial susceptibility data suggest resistance to ciprofloxacin and azithromycin is emerging. The South African population increased from 27.5 million in 1980 to 55.0 million in 2015: urbanization increased from 50% to 65%, GDP increased from United States Dollar (USD) $2,910 to USD $6,167, access to sanitation improved from 64.4% to 70.0% in the urban population and 26.4% to 60.5% in rural areas. Female literacy levels improved from 74.8% to 92.6% over the period. Improved socioeconomic circumstances in South Africa have been temporally associated with decreasing incidence rates of typhoid fever over a 35-year period. Ongoing challenges remain including potential for large outbreaks, a large immigrant population, and emerging antimicrobial resistance. Continued active surveillance is mandatory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".