Large-scale infectious disease testing programs have little consideration for equity: findings from a scoping review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: This scoping review aimed to identify how equity has been considered in large-scale infectious disease testing initiatives. STUDY DESIGN AND SETTING: Large-scale testing interventions are instrumental for infectious disease control and a central tool for the coronavirus 19 (COVID-19) pandemic. We searched Web of Science: core collection, Embase and Medline in June 2021 and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses recommendations for scoping reviews. We critically analyzed the content of all included articles. RESULTS: Our search resulted in 2448 studies of which 86 were included for data extraction after screening. Of the included articles, 80% reported on COVID-19 -related screening programs. None of the studies presented a formal definition of (in)equity in testing, however, 71 articles did indirectly include elements of equity through the justification of their target population. Of these 71 studies, 58% articles indirectly alluded to health equity according to the PROGRESS-Plus framework, an acronym used to identify a list of socially stratifying characteristics driving inequity in health outcomes. CONCLUSION: The studies included in our scoping review did not explicitly consider equity in their design or evaluation which is imperative for the success of infectious disease testing programs.
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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 | 0.024 | 0.508 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 it