Methods to assess environmental surface disinfectants against viruses: the quest and recommendations for a globally harmonized approach to microbicide testing
Bibliographic record
Abstract
Viruses pose a wide-ranging and significant risk to human health through acute and persistent infections that may confer risks for sequelae including musculoskeletal, immunological, and oncological disease. Infection prevention and control (IPAC) remains a highly effective, generic, global, and cost-effective means to mitigate virus spread. IPAC recommends proper disinfection of high-touch environmental surfaces (HITES) to reduce the risk of direct and indirect virus spread. The United States, Canada and many other countries mandate pre-market assessments of HITES disinfectants against viruses and other types of microbial pathogens. However, there are basic disparities in the regulation of disinfectants. Such incongruity in test protocols interferes with the determination of the true breadth of the microbicidal potential of a given product in the field where target pathogens are often unknown or may be encountered as mixtures. This review examines the various methodological disparities and recommends a more cohesive and harmonized approach. While there is particular emphasis on viruses here, an overall harmonization in microbicide testing of HITES disinfectants will greatly assist the numerous stakeholders involved in IPAC.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".