About this Research Topic
We hope to address the TB-associated health-care burden, and the current insufficient or imprecise control strategies for TB management. More importantly, we would like to discuss more efficient approaches in this field with the development of molecular epidemiology method and share insights to reduce TB burden.
In the purpose of this research topic, we hope to shed light on studies of the following, including: updated clinical epidemiology studies investigating on TB-related incidence, prevalence, mortality, recurrence and transmission; screening, prevention, management of coexisting diseases in TB; cost-effective analysis; updated molecular epidemiology studies using new approaches to reveal molecular mechanisms, potential targets or pathways for the transmission, diagnosis, treatment, genetic evolution, and drug resistance for TB. Moreover, studies investigating on TB transmission models based on model algorithm, artificial intelligence and machine learning are welcomed. The subtopics of interests include but not limited to:
• Recent updates on TB-related health-care burden
• Recent updates on screening, prevention, diagnosis, treatment, recurrence and transmission, and management of coexisting diseases in TB/drug-resistant TB.
• Recent updates on molecular epidemiology approaches to reveal potential molecular mechanisms, targets or pathways for the transmission, diagnosis, treatment, genetic evolution, and TB/drug-resistant TB.
• Recent updates on TB/drug-resistant TB transmission based on statistics models
Keywords: Tuberculosis, Drug resistant tuberculosis, Multi-drug resistant tuberculosis, Clinical epidemiology, Molecular epidemiology
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