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arXiv · 2207.05671

Inferring sources of substandard and falsified products in pharmaceutical supply chains

Eugene Wickett·Matthew Plumlee·Karen Smilowitz·Souly Phanouvong·Victor Pribluda
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Abstract

Substandard and falsified pharmaceuticals, prevalent in low- and middle-income countries, substantially increase levels of morbidity, mortality and drug resistance. Regulatory agencies combat this problem using post-market surveillance by collecting and testing samples where consumers purchase products. Existing analysis tools for post-market surveillance data focus attention on the locations of positive samples. This paper looks to expand such analysis through underutilized supply-chain information to provide inference on sources of substandard and falsified products. We first establish the presence of unidentifiability issues when integrating this supply-chain information with surveillance data. We then develop a Bayesian methodology for evaluating substandard and falsified sources that extracts utility from supply-chain information and mitigates unidentifiability while accounting for multiple sources of uncertainty. Using de-identified surveillance data, we show the proposed methodology to be effective in providing valuable inference.

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Eugene Wickett, Matthew Plumlee, Karen Smilowitz, Souly Phanouvong, Victor Pribluda. 2022-07-12. Inferring sources of substandard and falsified products in pharmaceutical supply chains. https://doi.org/10.1080/24725854.2023.2174277

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