Population-level impact of same-day microscopy and Xpert MTB/RIF for tuberculosis diagnosis in Africa

Abstract

Objective: To compare the population-level impact of two World Health Organization-endorsed strategies for improving the diagnosis of tuberculosis (TB): same-day microscopy and Xpert MTB/RIF (Cepheid, USA).

Methods: We created a compartmental transmission model of TB in a representative African community, fit to the regional incidence and mortality of TB and HIV. We compared the population-level reduction in TB burden over ten years achievable with implementation over two years of same-day microscopy, Xpert MTB/RIF testing, and the combination of both approaches.

Findings: Same-day microscopy averted an estimated 11.0% of TB incidence over ten years (95% uncertainty range, UR: 3.3%-22.5%), and prevented 11.8% of all TB deaths (95% UR: 7.7%-27.1%). Scaling up Xpert MTB/RIF to all centralized laboratories to achieve 75% population coverage had similar impact on incidence (9.3% reduction, 95% UR: 1.9%-21.5%) and greater effect on mortality (23.8% reduction, 95% UR: 8.6%-33.4%). Combining the two strategies (i.e., same-day microscopy plus Xpert MTB/RIF) generated synergistic effects: an 18.7% reduction in incidence (95% UR: 5.6%-39.2%) and 33.1% reduction in TB mortality (95% UR: 18.1%-50.2%). By the end of year ten, combining same-day microscopy and Xpert MTB/RIF could reduce annual TB mortality by 44% relative to the current standard of care.

Conclusion: Scaling up novel diagnostic tests for TB and optimizing existing ones are complementary strategies that, when combined, may have substantial impact on TB epidemics in Africa.

Conflict of interest statement

Competing Interests: Co-authors Dr. Dowdy and Dr. Cattamanchi are PLOS ONE Editorial Board members. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials.

Figures

Figure 1. Model Compartmental Structure.

Upon infection with TB, susceptible individuals may progress rapidly to active TB or enter a state of latent infection, from which active TB can develop at any time. Reinfection of latently-infected individuals occurs, as do relapse and reinfection after treatment/recovery. Smear-negative disease is modeled as a weighted average of smear-negative pulmonary and extrapulmonary disease. The model population is also subdivided by HIV status (positive vs. negative); people living with HIV are at increased risk of primary progression and reactivation of latent TB, are more likely to have smear-negative disease, and experience higher mortality rates (both TB and non-TB mortality).

Figure 2. Projected Trajectory of TB Incidence in Africa, 2013–2022.

Panel A shows the TB incidence rate (per 100,000 population per year), while Panel B shows the projected number of TB cases per year in an area with an adult population of 10 million in 2002, assuming constant 2.25% population growth.

Figure 3. One-Way Sensitivity Analyses.

Blue bars represent the low end of the sensitivity range of each parameter, as shown in Tables 1 and 2, and red bars represent the corresponding high values. The outcome was the percentage reduction in TB incidence, comparing the same-day microscopy strategy to the standard of care at the end of 2022; this was estimated at 17.5% in the base case (vertical line in this Figure, corresponds to the difference between green and red lines at the far right of Figure 1). Although sensitivity analysis was performed on all parameters, only those that caused a +/−5% change in the projected value of the outcome are shown here.