Enhancing biosafety management and governance: a comprehensive assessment of high-containment biological laboratories in Brazil
Bibliographic record
Abstract
High-containment biological laboratories are crucial in preventing and addressing high-risk infectious diseases, encompassing human and animal health. This comprehensive study presents an in-depth analysis of such laboratories in Brazil, covering their quantity, distribution, infrastructure, scope, regulatory compliance, and associated challenges. From a preliminary list of 92 presumed high-containment biological laboratories in Brazil, a total of 66 laboratories from 54 institutions currently operating under characteristics of a biosafety level 3 facility were identified, with 32 participating in the current research by responding to a comprehensive questionnaire. Key findings indicate a lack of official data, emphasizing the need for a National Biosafety and Biosecurity Policy and a strategic plan to assess and optimize the functionality and distribution of these facilities across the country. The study revealed that many high-containment biological laboratories may not comply with essential biosafety and biosecurity standards due to the absence of a national regulatory framework specifically addressing these issues. Furthermore, the sustainability of these laboratories is often jeopardized by financial constraints, particularly those associated with operational costs not covered by research grants. The establishment of a centralized system for laboratory oversight, akin to models in the US and Canada, emerges as a crucial recommendation. Such a framework would ensure standardized practices, facilitate sharing resources and information, and enhance Brazil’s overall biosafety and biosecurity culture. In conclusion, the study advocates for urgent reforms in Brazil’s approach to managing high- containment biological laboratories, including the development of a robust regulatory framework, enhanced government oversight, and the promotion of a strong culture of safety and security within the scientific community. These measures are deemed essential for safeguarding public and animal health and ensuring the country is equipped to address current and future biosecurity challenges. Keywords: High-Containment Biological Laboratories; Biosafety and Biosecurity; Regulatory Framework. Risk Management in Laboratories; Laboratory Sustainability; National Biosafety and Biosecurity Policy; Capacity Building in Biosafety; Biocontainment Facilities; Laboratory Oversight and Governance; Biorisk Management System.
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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 | 0.007 | 0.010 |
| 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 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".