Establishing likelihood ratios for evaluating opposing propositions concerning the activity causing methamphetamine contamination: Smoking or manufacture?. (September 2021)

• Record Type: Journal Article
• Authors: Russell, M; Wevers, Gerhard; Bogun, Ben; Mayo, Erina; McKinnel, Megan; Watson, Janine
• Is Part Of: Forensic science international. Volume 326(2021)
• Publication Date: 2021-09
• Subjects: Evaluative reporting -- Clandestine laboratories -- Likelihood ratio -- Methamphetamine contamination -- Methamphetamine manufacture; Medical jurisprudence -- Periodicals; Chemistry, Forensic -- Periodicals; Forensic Medicine -- Periodicals; Médecine légale -- Périodiques; Chimie légale -- Périodiques; Gerechtelijke geneeskunde; Gerechtelijke chemie; Gerechtelijke psychiatrie; Chemistry, Forensic; Medical jurisprudence; Electronic journals; Periodicals; Electronic journals; 614.1
• DOI: 10.1016/j.forsciint.2021.110939
• Languages: English
• ISSNs: 0379-0738

Abstract

Abstract: In New Zealand, concerns have been raised over the presence of methamphetamine contamination in households, especially when the activity causing the contamination is unknown. The cause of contamination is also a contentious issue in clandestine laboratory cases concerning charges in relation to "Use of Premises" (Section 12: Misuse of Drugs Act 1975, New Zealand). Regardless of the cause, other than scientific opinion, there is currently no analytical technique that can satisfactorily address the provenance of methamphetamine residues. For several years, approximate methamphetamine contamination levels have been collected from suspected clandestine laboratories in New Zealand, where methamphetamine is believed to have been manufactured. This study used this data and compared it to similar data from properties where the drug is suspected to have been used (smoked) to model likelihood ratios (LR). It is well documented that the LR forms the backbone to a Bayesian method of interpreting forensic evidence. As such, this data has the potential to underpin a novel Bayesian approach in the evaluation of clandestine laboratory evidence. Highlights: Methamphetamine contamination from "clan-labs" and general housing are compared. Probabilities relating to contamination cause (smoking/manufacture) are established. A Bayesian method of reporting in clandestine-laboratory cases is proposed.