Tuberculosis prevalence trends from a predictive modelling study-10 high-burden countries, 1980-2035

Chen Qiuping, Liu Qiao, Li Kangguo, Gavotte Laurent, Frutos Roger, Chen Tianmu. 2024. Tuberculosis prevalence trends from a predictive modelling study-10 high-burden countries, 1980-2035. China CDC Weekly, 6 (12) : 225-229.

https://doi.org/10.46234/ccdcw2024.045

Article de revue ; Article de recherche ; Article de revue à facteur d'impact Revue en libre accès total

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Url - jeu de données - Entrepôt autre : https://www.who.int/teams/global-tuberculosis-programme/data

Résumé : What is already known about this topic? Given the challenges presented by drug-resistant strains of tuberculosis (TB) and the rising mobility of the population, achieving the objective of eradicating TB appears uncertain. What is added by this report? The examination of TB incidence trends in 10 high-burden countries (HBCs) indicated a steady rise in cases, with India and China jointly accounting for nearly 70% of the burden. Projections for the future show diverse trajectories in these countries, with potential difficulties in reaching the TB elimination target, especially in Nigeria, Congo, and South Africa. What are the implications for public health practice? The number of TB cases is on the rise. It is crucial to learn from successful strategies to improve TB prevention and control worldwide through collaborative efforts.

Mots-clés Agrovoc : tuberculose, modélisation, technique de prévision, modèle mathématique, épidémiologie, morbidité

Mots-clés géographiques Agrovoc : Afrique du Sud, Nigéria, Chine, Inde, Congo

Mots-clés libres : Tuberculosis, Modeling, Epidemiology, China

Classification Agris : S50 - Santé humaine
U10 - Informatique, mathématiques et statistiques

Champ stratégique Cirad : CTS 4 (2019-) - Santé des plantes, des animaux et des écosystèmes

Agences de financement hors UE : (CHN) Guangzhou Laboratory

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