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
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».