Development and validation of an immunoperoxidase antigen detection test for improved diagnosis of rabies in Indonesia
Bibliographic record
Abstract
Rabies continues to pose a significant threat to human and animal health in regions of Indonesia. Indonesia has an extensive network of veterinary diagnostic laboratories and the 8 National laboratories are equipped to undertake diagnostic testing for rabies using the commercially-procured direct fluorescent antibody test (FAT), which is considered the reference (gold standard) test. However, many of the Indonesian Provincial diagnostic laboratories do not have a fluorescence microscope required to undertake the FAT. Instead, certain Provincial laboratories continue to screen samples using a chemical stain-based test (Seller's stain test, SST). This test has low diagnostic sensitivity, with negative SST-tested samples being forwarded to the nearest National laboratory resulting in significant delays for completion of testing and considerable additional costs. This study sought to develop a cost-effective and diagnostically-accurate immunoperoxidase antigen detection (RIAD) test for rabies that can be readily and quickly performed by the resource-constrained Provincial laboratories. This would reduce the burden on the National laboratories and allow more rapid diagnoses and implementation of post-exposure prophylaxis. The RIAD test was evaluated using brain smears fixed with acetone or formalin and its performance was validated by comparison with established rabies diagnostic tests used in Indonesia, including the SST and FAT. A proficiency testing panel was distributed between Provincial laboratories to assess the reproducibility of the test. The performance of the RIAD test was improved by using acetone fixation of brain smears rather than formalin fixation such that it was of equivalent accuracy to that of the World Organisation for Animal Health (OIE)-recommended FAT, with both tests returning median diagnostic sensitivity and specificity values of 0.989 and 0.993, respectively. The RIAD test and FAT had higher diagnostic sensitivity than the SST (median = 0.562). Proficiency testing using a panel of 6 coded samples distributed to 16 laboratories showed that the RIAD test had good reproducibility with an overall agreement of 97%. This study describes the successful development, characterisation and use of a novel RIAD test and its fitness for purpose as a screening test for use in provincial Indonesian veterinary laboratories.
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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 | 0.002 |
| 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 | 0.000 |
| 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".