Special Issue "Point-of-Care Diagnostic Tests for Tuberculosis Disease"
Deadline for manuscript submissions: 31 October 2023 | Viewed by 2105
Interests: epidemiologic studies; epidemiological statistics; clinical epidemiology; tuberculosis; health; community health; health services research; public health; epidemiologic methods; TB-HIV
Rapid TB diagnosis is one of the key strategies to end tuberculosis (TB) globally. Point-of-care tests (POCTs) facilitate early detection, help to provide immediate treatment, and halt the transmission of TB disease. The TB community has always dreamt of having state-of-the-art point-of-care tests which are simple, feasible for field implementation, and yet specific. The development of a second simple, rapid, point-of-care test is a major step forward for advancing tuberculosis diagnostics and could save lives as a result of early detection and treatment. In fact, in the patient care cascade, POCT reduces the length of time for diagnosis and treatment significantly. The aim of this Special Issue is to provide a platform to exchange knowledge, novel research findings, and experiences between epidemiologists, clinician-scientists, laboratory scientists, academicians, public health program managers, and other health professionals on the thematic area of ‘Point-of-Care Diagnostic Tests for Tuberculosis Disease’. These POCTs may include newer nucleic acid amplification tests, antigen-based detection, antibody detection, novel biomarkers or enzymes, low-cost portable chest-X-ray technologies, AI-based or other novel detection platforms or technologies. In addition to the development of these POCTs, experiences of implementation of these tests in real-world field settings for detection of the disease would be vital. Field-based studies to evaluate the feasibility, validity, clinical impact, and cost-effectiveness of newer tests are also encouraged.
Dr. Jaya Prasad Tripathy
Dr. Sharath Nagaraja
Manuscript Submission Information
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- point-of-care test
- rapid TB diagnosis
- implementation research
- diagnostic test validity
- AI-based algorithms