Changes in incarceration and tuberculosis notifications from prisons during the COVID-19 pandemic in Europe and the Americas: a time-series analysis of national surveillance data
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic disrupted tuberculosis control programmes globally; whether or not this disproportionately affected people who were incarcerated is unknown. We aimed to evaluate changes in incarceration and tuberculosis notifications in prisons in Europe and the Americas during the COVID-19 pandemic. METHODS: Data from WHO Pan American Health Organization (PAHO) and WHO Europe were used to conduct a joint hierarchical Bayesian negative binomial time-series. This approach accounted for world region, country-specific temporal trends, and country-specific autocorrelated random effects to simultaneously model and predict both annual prison population (ie, the offset) and prison tuberculosis cases (ie, the primary outcome). Results were used to calculate percentage differences between predicted and observed annual tuberculosis notifications and prison populations during the COVID-19 pandemic years (2020-22). FINDINGS: In total, 22 of 39 countries from PAHO and 25 of 53 countries from WHO Europe were included (representing 4·9 million people incarcerated annually), contributing 520 country-years of follow-up. Observed tuberculosis notifications in prisons were lower than predicted in 2020 (-26·2% [95% credible interval -66·3 to 7·8), 2021 (-46·4% [-108·8 to 3·9]), and 2022 (-48·9 [-124·4 to 10·3]). These decreasing trends were consistent across Europe and the Americas, but larger decreases were seen in low-burden settings in 2020 (-54·8% [-112·4 to -4·8]) and 2021 (-68·4% [-156·6 to -2·9]), high-burden settings in 2021 (-89·4% [-190·3 to -10·4]), and Central and North America in 2021 (-100·3% [-239·0 to -6·3]). Observed incarceration levels were similar to predicted levels (<10% difference overall) during all COVID-19 pandemic years. INTERPRETATION: Tuberculosis notifications in prisons from 47 countries in Europe and the Americas were lower than expected (at times >50% lower) during COVID-19 pandemic years, despite consistent incarceration levels. Reasons for this change in tuberculosis notifications might be multifactorial and include missed diagnoses and implementation of COVID-19 pandemic measures, reducing transmission. Greater prioritisation of people who are incarcerated is needed to ensure appropriate access to care in the face of future pandemics. FUNDING: Canadian Institutes of Health Research, National Institutes of Health, and Oswaldo Cruz Foundation, Brazil.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".