Alcohol‐based Hand Sanitizers amid COVID‐19: Chemical Formulation, Analysis, Safety
Bibliographic record
Abstract
Alcohol-based hand sanitizers (ABHSs) containing ethanol (EtOH) or isopropyl alcohol (IPA) to inactivate microorganisms help prevent the spread of respiratory diseases. These products have become very popular during the COVID-19 pandemic. Apart from vaccines or other preventative antiseptic measures, the majority of consumers have relied on different types of ABHSs to disinfect their hands. As a result, there has been a global rush in the demand for these ABHSs and other antiseptic hygiene products. This has resulted in the formation of many new commercial sanitizer producers. There are around fifty companies of varying sizes that have been marketing their ABHSs in Bangladesh, most of which have only been manufacturing their products for the first time since the COVID-19 pandemic. To monitor the quality and components of these products, the Bangladesh Council of Scientific and Industrial Research (BCSIR) analyzed approximately 200 different hand sanitizer samples using GC-FID method. All samples were alcohol-based except for 3 which were alcohol-free aqueous hand sanitizers. Of the supplied formulated ABHSs, 80 samples were found to contain only IPA and 54 contained only EtOH. However, 28 samples were found to be contaminated with methanol (MeOH), 7 samples contained only MeOH and 18 samples contained both EtOH and IPA. This is the first study to explore the analysis of alcohol content in formulated ABHSs and their marketing status in Bangladesh, but the findings could be of use in other jurisdictions as similar issues have been raised in many parts of the world.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".