A Collaborative Epidemiological Investigation into the Criminal Fake Artesunate Trade in South East Asia
Bibliographic record
Abstract
BACKGROUND: Since 1998 the serious public health problem in South East Asia of counterfeit artesunate, containing no or subtherapeutic amounts of the active antimalarial ingredient, has led to deaths from untreated malaria, reduced confidence in this vital drug, large economic losses for the legitimate manufacturers, and concerns that artemisinin resistance might be engendered. METHODS AND FINDINGS: With evidence of a deteriorating situation, a group of police, criminal analysts, chemists, palynologists, and health workers collaborated to determine the source of these counterfeits under the auspices of the International Criminal Police Organization (INTERPOL) and the Western Pacific World Health Organization Regional Office. A total of 391 samples of genuine and counterfeit artesunate collected in Vietnam (75), Cambodia (48), Lao PDR (115), Myanmar (Burma) (137) and the Thai/Myanmar border (16), were available for analysis. Sixteen different fake hologram types were identified. High-performance liquid chromatography and/or mass spectrometry confirmed that all specimens thought to be counterfeit (195/391, 49.9%) on the basis of packaging contained no or small quantities of artesunate (up to 12 mg per tablet as opposed to approximately 50 mg per genuine tablet). Chemical analysis demonstrated a wide diversity of wrong active ingredients, including banned pharmaceuticals, such as metamizole, and safrole, a carcinogen, and raw material for manufacture of methylenedioxymethamphetamine ('ecstasy'). Evidence from chemical, mineralogical, biological, and packaging analysis suggested that at least some of the counterfeits were manufactured in southeast People's Republic of China. This evidence prompted the Chinese Government to act quickly against the criminal traders with arrests and seizures. CONCLUSIONS: An international multi-disciplinary group obtained evidence that some of the counterfeit artesunate was manufactured in China, and this prompted a criminal investigation. International cross-disciplinary collaborations may be appropriate in the investigation of other serious counterfeit medicine public health problems elsewhere, but strengthening of international collaborations and forensic and drug regulatory authority capacity will be required.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".