Early Economic Evaluation to Identify the Necessary Test Characteristics of a New Typhoid Test to be Cost Effective in Ghana
Bibliographic record
Abstract
BACKGROUND: In Ghana, there are issues with the diagnosis of typhoid fever; these include delays in diagnosis, concerns about the accuracy of current tests, and lack of availability. These issues highlight the need for the development of a rapid, accurate, and easily accessible diagnostic test. The aim of this study was to conduct an early economic analysis of a hypothetical rapid test for typhoid fever diagnosis in Ghana and identify the necessary characteristics of the test for it to be cost effective in Ghana. METHODS: An early cost-utility analysis was conducted using a decision tree parameterized with secondary data sources, with reasonable assumptions made for unknown parameters. The patient population considered is individuals presenting with symptoms suggestive of typhoid fever at a healthcare facility in Ghana; a time horizon of 180 days and the Ghanaian national health service perspective were adopted for the analysis. Extensive sensitivity analysis was undertaken, including headroom analysis. RESULTS: The results here show that for a hypothetical test to perform better than the existing test (Widal) in terms of QALYs gained and cost effectiveness, it is necessary for it to have a high specificity (at least 70%) and should not be priced more than US$4. The overall value of conducting research to reduce uncertainty (over 5 years) is US$3287. CONCLUSION: The analysis shows the potential for the hypothetical test to replace the Widal test and the market potential of developing a new test in the Ghanaian setting.
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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 | 0.013 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".