Driving the usage of tuberculosis diagnostic data through capacity building in low- and middle-income countries

Abstract

Background Connectivity platforms collect a wealth of data from connected GeneXpert instruments, with the potential to provide valuable insights into the burden of disease and effectiveness of tuberculosis programmes. The challenge faced by many countries is a lack of training, analytical skills, and resources required to understand and translate this data into patient management and programme improvement. Objective We describe a novel training programme, the tuberculosis Data Fellowship, designed to build capacity in low- and middle- income countries for tuberculosis data analytics. Methods The programme consisted of classroom and remote training plus mentorship over a 12-month period. The focus was on skills development in Tableau software, followed by training in exploration, analysis, and interpretation of GeneXpert tuberculosis data across five key programme areas: patient services, programme monitoring, quality of testing, inventory management, and disease burden. Results The programme was piloted in six countries (Bangladesh, Ethiopia, Ghana, Malawi, Mozambique) in July 2018 and Nigeria in September 2018; 20 participants completed the training. A number of key outputs have been achieved, such as improved instrument utilisation rates, decreased error rates, and improved instrument management. Conclusion The training programme empowers local tuberculosis programme staff to discover and fix critical inefficiencies, provides high-level technical and operational support to the tuberculosis programme, and provides a platform for continued sharing of insights and best practices between countries. It supports the notion that connectivity can increase efficiencies and clinical benefits with better data for decision making, if coupled with commensurate capacity building in data analysis and interpretation.

Prospective narratives on global issues: An AI-based pedagogical model for assessing complex thinking

“…These clusters or "themes" reflect relationships between ideas and concepts (O'Reilly & Gray, 2022;Chen, Zanocco, Flora, & Rajagopal, 2022) • Visualization tools: The ability to analyze, interpret, and gain insights from large amounts of heterogeneous data within complex dynamic systems acquired from the Internet of Things can receive support from visual analytics, role-based collaboration, and augmented reality (Wachowiak-Smolikova & Zhu, 2023;Ens, Goodwin, Prouzeau, Anderson Wang, Gratzl et al, 2021). Other tools, such as Gephi (Zhong & Lin, 2022) or Tableau (Gous, Nyaruhirira, Cunningham & Macek, 2020), can visualize complex data and relationships, providing insights into the interconnectedness between ideas or concepts to support complex thinking examples like global health issues.…”

Connected diagnostics systems: The future of disease control in Africa

“… 8 , 9 Gous and Macek describe a new in-person and remote training programme, the TB Data Fellowship, which builds a tableau-based tuberculosis analytics capacity in low- and middle-income countries. 10 Rapid advances in data connectivity and digital computing, coupled with increased access to internet coverage and portable communications such as mobile phones in Africa, provide us with a window of opportunity to adapt these technologies to strengthen diagnostic systems for the surveillance of diseases of epidemic potential, as well as for HIV, tuberculosis and neglected tropical diseases. A well-connected diagnostic system will cause a seismic shift in the way disease control is tackled in Africa.…”