dCXR/CAD gives patients access to a rapid “one Stop” TB screening service. Instant image availability, combined with a ~30 seconds CAD computation time, reduces travel cost and waiting time to know their TB status to about 2 minutes for most patients. For those patients with a high CAD score the artificial intelligence algorithm speeds-up the decision to start sputum analysis and allows for prompt access to treatment in case TB is confirmed. Low radiation dose exposure makes it a safe tool also for large-scale TB prevalence studies or screening for active TB in high risk groups. For those patients with a high abnormality CAD score, but a negative Xpert test further diagnosis may be required.

TB is mainly a disease of poor and marginalized people and communities. An already risky socioeconomic situation can worsen considerably when an individual or household is struck by TB; potentially entrenching them in a vicious poverty-disease circle. Costs related to diagnosis and treatment are often compounded by costs for transport to a place of care, for temporary accommodation and food, as well as the income foregone when seeking and receiving treatment, and/or lost employment due to disability or discrimination. These costs can have catastrophic consequences as illustrated below.

The socio-economic importance for patients of early TB case detection and TB prevention was again confirmed in the 2018 Kenya National TB Patient Cost Survey whereby it became clear that households affected by TB incur in severe socio-economic consequences [1].

Households affected by TB

  • 62% lost jobs due to TB
  • 9% of households’ children disrupted school
  • 36% experienced social exclusion
  • 28% had to take loans, sell assets or use savings