Risk Factors for Typhoid Fever: Systematic Review
Bibliographic record
Abstract
BACKGROUND: Typhoid fever, a significant global health problem, demonstrates a multifaceted transmission pattern. Knowledge of the factors driving its transmission is critical for developing effective control strategies and optimizing resource allocation. OBJECTIVE: This review aimed to comprehensively synthesize evidence on risk factors associated with typhoid fever transmission from 1928 to 2024. METHODS: We searched PubMed, Scopus, Google Scholar, and Semantic Scholar databases using keywords related to risk, contributors, determinants, and causes of typhoid fever. We followed a registered protocol to support our search and triangulated the results. RESULTS: Overall, we retrieved 1614 articles, of which 219 were reviewed. Of these, 109 addressed multiple, non-mutually exclusive typhoid fever risk factors. Unsurprisingly, of the total articles reviewed on risk factors, approximately 70.6% (77/109) originated from the Asian continent (51/109, 46.8%) and the African continent (26/109, 23.9%). Half of the articles (55/109, 50.5%) focused on risk factors related to demographic and socioeconomic transmission, while 44% (48/109) of the articles examined foodborne transmission. Additional risk factors included water, sanitation, and hygiene practices: waterborne transmissions (45/109, 41.3%) and sanitation and hygiene practices (34/109, 31.2%), travel-related risk (19/109, 17.4%), antimicrobial use (14/109, 12.8%), climate-related factors (15/109, 13.8%), environment-related factors (9/109, 8.3%), typhoid carriers (11/109, 10.1%), and host-related risk factors (6/109, 5.5%). CONCLUSIONS: This review identifies demographic and socioeconomic factors as key drivers of typhoid transmission, underscoring the need for targeted interventions. Strengthening street food regulation in urban Asia and investing in water infrastructure in rural Africa can significantly mitigate risk. Integrating water, sanitation, and hygiene interventions with typhoid vaccines can reduce immediate exposure while enhancing long-term immunity. Prioritizing these strategies in schools and high-risk communities is essential for sustainable typhoid control. Future research should focus on longitudinal studies to assess risk factor causality and vaccine impact, guiding more effective public health 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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".