Measuring training effectiveness of laboratory biosafety program offered at African Center for Integrated Laboratory Training in 22 President's Emergency Plan for AIDS Relief supported countries (2008–2014)
Bibliographic record
Abstract
Abstract Introduction The African Center for Integrated Laboratory Training (ACILT) in Johannesburg, South Africa offered a laboratory biosafety program to improve laboratory biosafety practices in 22 President's Emergency Plan for AIDS Relief (PEPFAR) supported countries. This manuscript evaluates the transference of newly gained knowledge and skills to the participants' place of employment for HIV and TB diagnostic laboratory programs. It also serves as a follow-on to a previously published manuscript that measured training effectiveness for all courses offered at ACILT. Methods ACILT offered 20 Laboratory Biosafety and Infrastructure courses (2008–2014), also referred as biosafety course/course comprising of 14 core laboratory safety elements to 402 participants from 22 countries. In 2015, participants received 22 e-questions divided into four categories: (1) Safety Policies, (2) Management's Engagement, (3) Safety Programs and (4) Assessments of Safety Practices to determine retrospectively the training effectiveness of biosafety practices in their place of employment 6 months before and after attending their course. We used Kirkpatrick model to assess the transference of knowledge, skills and obstructive factors. Results 20% (81/402) of the participants completed the e-questionnaire. The overall percentage of positive responses indicating implementation of new safety practices increased from 50% to 84%. Improvement occurred in all four categories after attending the course, with the greatest increases in Safety Policies (67–94%) and Safety Programs (43–91%). Creating a safety committee, allocating resources, and establishing a facility safety policy were important drivers for implementing and maintaining laboratory safety practices. In addition, accredited laboratories and countries with national safety regulations or policies had a higher percentage of improvements. The most reported challenges were inadequate funding and lack of management enforcement. Conclusions PEPFAR and other partners' investments in training institutions, such as ACILT, were effective in building sustainable country ownership to strengthen biosafety practices and were leveraged to combat zoonotic diseases and COVID-19. Although support continues at the national/regional level, a standardized, coordinated and continent-wide sustainable approach to offer a biosafety program-like ACILT is missing. Continuous offerings of biosafety programs similar to ACILT could contribute to sustainable strengthening of laboratory biosafety, QMS and pandemic preparedness.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".