Burden of transmitted multidrug resistance in epidemics of tuberculosis: a transmission modelling analysis

Abstract

Background: Multidrug-resistant (MDR) tuberculosis can be acquired through de-novo mutation during tuberculosis treatment or through transmission from other individuals with active MDR tuberculosis. Understanding the balance between these two mechanisms is essential when allocating resources for MDR tuberculosis. We aimed to create a dynamic transmission model of an MDR tuberculosis epidemic to estimate the contributions of treatment-related acquisition and person-to-person transmission of resistance to incident MDR tuberculosis cases.

Methods: In this modelling analysis, we constructed a dynamic transmission model of an MDR tuberculosis epidemic, allowing for both treatment-related acquisition and person-to-person transmission of resistance. We used national tuberculosis notification data to inform Bayesian estimates of the proportion of each country's 2013 MDR tuberculosis incidence that resulted from MDR transmission rather than treatment-related MDR acquisition.

Findings: Global estimates of 3·5% MDR tuberculosis prevalence among new tuberculosis notifications and 20·5% among re-treatment notifications translate into an estimate that resistance transmission rather than acquisition accounts for a median 95·9% (95% uncertainty range [UR] 68·0-99·6) of all incident MDR tuberculosis, and 61·3% (16·5-95·2) of incident MDR tuberculosis in previously treated individuals. The estimated proportion of MDR tuberculosis resulting from transmission varied substantially with different countries' notification data-ranging from 48% (95% UR 30-75) in Bangladesh to 99% (91-100) in Uzbekistan. Estimates were most sensitive to estimates of the transmissibility of MDR strains, the probability of acquiring MDR during tuberculosis treatment, and the responsiveness of MDR tuberculosis to first-line treatment.

Interpretation: Notifications of MDR prevalence from most high-burden settings are consistent with most incident MDR tuberculosis resulting from transmission rather than new treatment-related acquisition of resistance. Merely improving the treatment of drug-susceptible tuberculosis is unlikely to greatly reduce future MDR tuberculosis incidence. Improved diagnosis and treatment of MDR tuberculosis-including new tests and drug regimens-should be highly prioritised.

Funding: National Institutes of Health and the Bill & Melinda Gates Foundation.

Figure 1. Model structure

This simplified schematic of the model shows progression through stages of tuberculosis infection, disease, and treatment, and shows opportunities to develop drug-resistant (DR) tuberculosis (TB) via either acquisition or transmission of resistance. The arrows labeled as pathway “A” show how drug resistance in a previously treated case may result from prior treatment, and the arrows labeled as pathway “B” show how drug resistance in a previously treated case may result from transmission of resistance (with subsequent failure of the initial course of standard treatment). MDR-TB in a previously treated case, indicated by the box with a heavy outline, can result from either acquired (pathway A) or transmitted (pathway B) resistance. Asterisks (*) indicate that transitions through these states, including possibilities for reinfection, proceed as for states of the same name to the left (denoted with daggers (†)). Not shown here, but also included in the model, are subdivisions into treatment-naïve and treatment-experienced compartments (with differing probabilities of each treatment outcome; see Figure S1), and death and spontaneous cure (either of which can occur from any active disease or treatment state).

Figure 2. Converting multidrug-resistant tuberculosis (MDR-TB) notifications into estimated percentage of incident MDR-TB due to MDR transmission

Shown is the estimated percentage of incident MDR-TB reflecting MDR transmission (rather than acquisition during previous treatment in the same person) across all simulations (upper left) and within the estimated prevalence of MDR among notifications globally (namely, MDR prevalence of 2·2–4·7% among new TB notifications and four to eight times higher MDR prevalence among retreatment notifications (inset)). Current global notifications were most consistent with a vast majority of MDR-TB cases reflecting transmission (median 96%, 95% uncertainty range: 68–100%) (inset). Treatment-related acquisition of resistance was high only when the ratio of MDR prevalence in retreatment versus new notifications was extremely high (red and yellow dots). The same trends are illustrated in line graphs without a color scale in Figure S2.

Figure 2. Converting multidrug-resistant tuberculosis (MDR-TB) notifications into estimated percentage of incident MDR-TB due to MDR transmission

Shown is the estimated percentage of incident MDR-TB reflecting MDR transmission (rather than acquisition during previous treatment in the same person) across all simulations (upper left) and within the estimated prevalence of MDR among notifications globally (namely, MDR prevalence of 2·2–4·7% among new TB notifications and four to eight times higher MDR prevalence among retreatment notifications (inset)). Current global notifications were most consistent with a vast majority of MDR-TB cases reflecting transmission (median 96%, 95% uncertainty range: 68–100%) (inset). Treatment-related acquisition of resistance was high only when the ratio of MDR prevalence in retreatment versus new notifications was extremely high (red and yellow dots). The same trends are illustrated in line graphs without a color scale in Figure S2.

Figure 3. Partial rank correlation coefficients (PRCCs)

with the fraction of incident MDR-TB cases resulting from MDR transmission, after adjusting for other parameters. PRCCs were calculated both without notification constraints (Panel 1) and within the notification-based tolerance ranges for each of the representative countries shown in table 2 (Panel 2, mean and SD of PRCCs over six countries). Parameters that had either a PRCC > 0.2 across all models or a mean PRCC >0.2 across the six countries are shown in the figure.