Tuberculosis in times of COVID-19
Bibliographic record
Abstract
The COVID-19 pandemic has caused widespread disruptions to tuberculosis (TB) care and service delivery in 2020, setting back progress in the fight against TB by several years. As newer COVID-19 variants continue to devastate many low and middle-income countries in 2021, the extent of this setback is likely to increase. Despite these challenges, the TB community can draw on the comprehensive approaches used to manage COVID-19 to help restore progress and mitigate the impact of COVID-19 on TB. Our team developed the 'Swiss Cheese Model for Ending TB' to illustrate that it is only through multisectoral collaborations that address the personal, societal and health system layers of care that we will end TB. In this paper, we examine how COVID-19 has impacted the different layers of TB care presented in the model and explore how we can leverage some of the lessons and outcomes of the COVID-19 pandemic to strengthen the global TB response.
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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 | 0.031 | 0.115 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".