Jeniffer Nagudi

Background: Although tuberculosis preventive therapy guidelines support testing for tuberculosis infection in household contacts (HHCs), this adds operational complexity and cost and has often been abandoned. To understand utility of testing, we determined prevalence and risk factors for tuberculosis infection and tuberculosis preventive therapy eligibility among HHCs. Methods: In a cross-sectional study conducted from July 2021 to September 2022 in Lesotho, South Africa, and Tanzania, we enrolled people with microbiologically confirmed pulmonary tuberculosis and their HHCs. HHCs were screened and tested for tuberculosis and tuberculosis infection using Xpert Ultra and QuantiFERON-TB-Gold-Plus, respectively. Generalized linear modelling was used to determine factors associated with tuberculosis infection, using robust standard errors. Tuberculosis preventive therapy eligibility was determined using World Health Organization criteria. Results: We enrolled 342 people with pulmonary tuberculosis and 964 HHCs: 61.9% (597/964) were female with a median age of 18 years (interquartile range, 8–39 years). Overall, tuberculosis prevalence was 3.4% (25/739; 95% confidence interval [CI], 2.2%–4.9%), while tuberculosis infection prevalence was 48.7% (348/714; 95% CI, 45.0%–52.5%). Having tuberculosis infection increased with age per year (adjusted odds ratio [aOR], 1.02; 95% CI, 1.01–1.03), being from Lesotho (aOR, 1.82; 95% CI, 1.04–3.20), previous tuberculosis history (aOR, 2.25; 95% CI, 1.05–4.79), and being HIV negative (aOR, 2.30; 95% CI, 1.31–4.04). Overall, 62.2% (518/833; 95% CI, 58.8%–65.5%) were eligible for tuberculosis preventive therapy. Conclusions: Almost half of tuberculosis-exposed HHCs aged ≥5 years had tuberculosis infection. Approximately two-thirds of HHCs were eligible for tuberculosis preventive therapy, implying that providing tuberculosis preventive therapy without prior testing for tuberculosis infection may be warranted in this population. Further work on cost-effectiveness is warranted when new tests become available. Clinical Trials Registration: ISRCTN10003903.

Background: Mobile health (mHealth) technologies are increasingly used in contact tracing and case finding, enhancing and replacing traditional methods for managing infectious diseases such as Ebola, tuberculosis, COVID-19, and HIV. However, the variations in their development approaches, implementation scopes, and effectiveness introduce uncertainty regarding their potential to improve public health outcomes. Objective: We conducted this systematic review to explore how mHealth technologies are developed, implemented, and evaluated. We aimed to deepen our understanding of mHealth’s role in contact tracing, enhancing both the implementation and overall health outcomes. Methods: We searched and reviewed studies conducted in Africa focusing on tuberculosis, Ebola, HIV, and COVID-19 and published between 1990 and 2023 using the PubMed, Scopus, Web of Science, and Google Scholar databases. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to review, synthesize, and report the findings from articles that met our criteria. Results: We identified 11,943 articles, but only 19 (0.16%) met our criteria, revealing a large gap in technologies specifically aimed at case finding and contact tracing of infectious diseases. These technologies addressed a broad spectrum of diseases, with a predominant focus on Ebola and tuberculosis. The type of technologies used ranged from mobile data collection platforms and smartphone apps to advanced geographic information systems (GISs) and bidirectional communication systems. Technologies deployed in programmatic settings, often developed using design thinking frameworks, were backed by significant funding and often deployed at a large scale but frequently lacked rigorous evaluations. In contrast, technologies used in research settings, although providing more detailed evaluation of both technical performance and health outcomes, were constrained by scale and insufficient funding. These challenges not only prevented these technologies from being tested on a wider scale but also hindered their ability to provide actionable and generalizable insights that could inform public health policies effectively. Conclusions: Overall, this review underscored a need for organized development approaches and comprehensive evaluations. A significant gap exists between the expansive deployment of mHealth technologies in programmatic settings, which are typically well funded and rigorously developed, and the more robust evaluations necessary to ascertain their effectiveness. Future research should consider integrating the robust evaluations often found in research settings with the scale and developmental rigor of programmatic implementations. By embedding advanced research methodologies within programmatic frameworks at the design thinking stage, mHealth technologies can potentially become technically viable and effectively meet specific contact tracing health outcomes to inform policy effectively.

BACKGROUND Mobile health (mHealth) technologies are increasingly used in contact tracing and case finding, enhancing and replacing traditional methods for managing infectious diseases such as Ebola, tuberculosis, COVID-19, and HIV. However, the variations in their development approaches, implementation scopes, and effectiveness introduce uncertainty regarding their potential to improve public health outcomes. OBJECTIVE We conducted this systematic review to explore how mHealth technologies are developed, implemented, and evaluated. We aimed to deepen our understanding of mHealth’s role in contact tracing, enhancing both the implementation and overall health outcomes. METHODS We searched and reviewed studies conducted in Africa focusing on tuberculosis, Ebola, HIV, and COVID-19 and published between 1990 and 2023 using the PubMed, Scopus, Web of Science, and Google Scholar databases. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to review, synthesize, and report the findings from articles that met our criteria. RESULTS We identified 11,943 articles, but only 19 (0.16%) met our criteria, revealing a large gap in technologies specifically aimed at case finding and contact tracing of infectious diseases. These technologies addressed a broad spectrum of diseases, with a predominant focus on Ebola and tuberculosis. The type of technologies used ranged from mobile data collection platforms and smartphone apps to advanced geographic information systems (GISs) and bidirectional communication systems. Technologies deployed in programmatic settings, often developed using design thinking frameworks, were backed by significant funding and often deployed at a large scale but frequently lacked rigorous evaluations. In contrast, technologies used in research settings, although providing more detailed evaluation of both technical performance and health outcomes, were constrained by scale and insufficient funding. These challenges not only prevented these technologies from being tested on a wider scale but also hindered their ability to provide actionable and generalizable insights that could inform public health policies effectively. CONCLUSIONS Overall, this review underscored a need for organized development approaches and comprehensive evaluations. A significant gap exists between the expansive deployment of mHealth technologies in programmatic settings, which are typically well funded and rigorously developed, and the more robust evaluations necessary to ascertain their effectiveness. Future research should consider integrating the robust evaluations often found in research settings with the scale and developmental rigor of programmatic implementations. By embedding advanced research methodologies within programmatic frameworks at the design thinking stage, mHealth technologies can potentially become technically viable and effectively meet specific contact tracing health outcomes to inform policy effectively.