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

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

SUBMITTER: Kendall EA

PROVIDER: S-EPMC4684734 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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

Kendall Emily A EA Fofana Mariam O MO Dowdy David W DW

The Lancet. Respiratory medicine 20151118 12

<h4>Background</h4>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 o ...[more]

PMID: 26597127

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Project description:BackgroundTo end the global tuberculosis epidemic, latent tuberculosis infection needs to be addressed. All standard treatments for latent tuberculosis contain drugs to which multidrug-resistant (MDR) Mycobacterium tuberculosis is resistant. We aimed to estimate the global burden of multidrug-resistant latent tuberculosis infection to inform tuberculosis elimination policy.MethodsBy fitting a flexible statistical model to tuberculosis drug resistance surveillance and survey data collated by WHO, we estimated national trends in the proportion of new tuberculosis cases that were caused by MDR strains. We used these data as a proxy for the proportion of new infections caused by MDR M tuberculosis and multiplied trends in annual risk of infection from previous estimates of the burden of latent tuberculosis to generate trends in the annual risk of infection with MDR M tuberculosis. These estimates were used in a cohort model to estimate changes in the global and national prevalence of latent infection with MDR M tuberculosis. We also estimated recent infection levels (ie, in 2013 and 2014) and made predictions for the future burden of MDR tuberculosis in 2035 and 2050.Findings19·1 million (95% uncertainty interval [UI] 16·4 million-21·7 million) people were latently infected with MDR tuberculosis in 2014-a global prevalence of 0·3% (95% UI 0·2-0·3). MDR strains accounted for 1·2% (95% UI 1·0-1·4) of the total latent tuberculosis burden overall, but for 2·9% (95% UI 2·6-3·1) of the burden among children younger than 15 years (risk ratio for those younger than 15 years vs those aged 15 years or older 2·65 [95% UI 2·11-3·25]). Recent latent infection with MDR M tuberculosis meant that 1·9 million (95% UI 1·7 million-2·3 million) people globally were at high risk of active MDR tuberculosis in 2015.InterpretationWe estimate that three in every 1000 people globally carry latent MDR tuberculosis infection, and prevalence is around ten times higher among those younger than 15 years. If current trends continue, the proportion of latent tuberculosis caused by MDR strains will increase, which will pose serious challenges for management of latent tuberculosis-a cornerstone of tuberculosis elimination strategies.FundingUK Medical Research Council, Bill & Melinda Gates Foundation, and European Research Council.

Project description:BackgroundIn May, 2016, WHO endorsed a 9 month regimen for multidrug-resistant tuberculosis that is cheaper and potentially more effective than the conventional, longer (20-24 month) therapy. We aimed to investigate the population-level implications of scaling up this new regimen.MethodsIn this population modelling analysis, we developed a dynamic transmission model to simulate the introduction of this short-course regimen as an instantaneous switch in 2016. We projected the corresponding percentage reduction in the incidence of multidrug-resistant tuberculosis by 2024 compared with continued use of longer therapy. In the primary analysis in a representative southeast Asian setting, we assumed that the short-course regimen would double treatment access (through savings in resources or capacity) and achieve long-term efficacy at levels seen in preliminary cohort studies. We then did extensive sensitivity analyses to explore a range of alternative scenarios.FindingsUnder the optimistic assumptions in the primary analysis, the incidence of multidrug-resistant tuberculosis in 2024 would be 3·3 (95% uncertainty range 2·2-5·6) per 100 000 population with the short-course regimen and 4·3 (2·9-7·6) per 100 000 population with continued use of longer therapy-ie, the short-course regimen could reduce incidence by 23% (10-38). Incidence would be reduced by 14% (4-28) if the new regimen affected only treatment effectiveness and by 11% (3-24) if it affected only treatment availability. Under more pessimistic assumptions, the short-course regimen would have minimal effect and even potential for harm-eg, when 30% of patients are ineligible for the new regimen because of second-line drug resistance, we projected a change in incidence of -2% (-20 to +28). The new regimen's effect was greater in settings with more ongoing transmission of multidrug-resistant tuberculosis, but results were otherwise similar across settings with different levels of tuberculosis incidence and prevalence of multidrug resistance.InterpretationThe short-course regimen has potential to substantially lessen the multidrug-resistant tuberculosis epidemic, but this effect depends on its long-term efficacy, its ability to expand treatment access, and the role of second-line drug resistance.FundingUS National Institutes of Health and Bill & Melinda Gates Foundation.

Project description:BACKGROUND:Tuberculosis (TB) burden shows wide disparities across ages in Taiwan. In 2016, the age-specific notification rate in those older than 65?years old was about 100 times as much as in those younger than 15?years old (185.0 vs 1.6 per 100,000 population). Similar patterns are observed in other intermediate TB burden settings. However, driving mechanisms for such age disparities are not clear and may have importance for TB control efforts. METHODS:We hypothesised three mechanisms for the age disparity in TB burden: (i) older age groups bear a higher risk of TB progression due to immune senescence, (ii) elderly cases acquired TB infection during a past period of high transmission, which has since rapidly declined and thus contributes to little recent infections, and (iii) assortative mixing by age allows elders to maintain a higher risk of TB infection, while limiting spillover transmission to younger age groups. We developed a series of dynamic compartmental models to incorporate these mechanisms, individually and in combination. The models were calibrated to the TB notification rates in Taiwan over 1997-2016 and evaluated by goodness-of-fit to the age disparities and the temporal trend in the TB burden, as well as the deviance information criterion (DIC). According to the model performance, we compared contributions of the hypothesised mechanisms. RESULTS:The 'full' model including all the three hypothesised mechanisms best captured the age disparities and temporal trend of the TB notification rates. However, dropping individual mechanisms from the full model in turn, we found that excluding the mechanism of assortative mixing yielded the least change in goodness-of-fit. In terms of their influence on the TB dynamics, the major contribution of the 'immune senescence' and 'assortative mixing' mechanisms was to create disparate burden among age groups, while the 'declining transmission' mechanism served to capture the temporal trend of notification rates. CONCLUSIONS:In settings such as Taiwan, the current TB burden in the elderly may be impacted more by prevention of active disease following latent infection, than by case-finding for blocking transmission. Further studies on these mechanisms are needed to disentangle their impacts on the TB epidemic and develop corresponding control strategies.

Dataset Information

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

Publications

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

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