DIGITAL SOLUTIONS FOR TUBERCULOSIS SURVEILLANCE AND CONTROL IN PRIMARY HEALTH CARE: A SCOPING REVIEW

Abstract

Abstract Digital solutions are essential for eliminating tuberculosis as a public health problem. They can be applied across all stages of patient care, health surveillance, program management, workforce development, and community engagement. This study aimed to identify and map digital solutions for tuberculosis developed and/or validated within the context of primary health care. We retrieved studies focusing on digital solutions for tuberculosis targeting managers, health professionals, or patients from Medline, Scopus, Embase, Web of Science, and Google Scholar. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR) guidelines to review, synthesize, and report the findings of articles that met our inclusion criteria. We identified 3133 publications, of which 96 were included after full-text screening. Most solutions focused on treatment monitoring and adherence (46 studies). There was particular emphasis on electronic directly observed therapy, smart pillboxes, and mobile applications. Artificial intelligence–based solutions also emerged, applied to diagnosis, prediction of treatment nonadherence, and prognosis. The findings show that digital solutions have evolved from simple tools to advanced artificial intelligence models. We conclude that the systematic incorporation of these technologies into national protocols is crucial to accelerate progress toward the targets established by the End TB Strategy.

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