4.7 Article

The Distribution of Fitness Costs of Resistance-Conferring Mutations Is a Key Determinant for the Future Burden of Drug-Resistant Tuberculosis: A Model-Based Analysis

期刊

CLINICAL INFECTIOUS DISEASES
卷 61, 期 -, 页码 S147-S154

出版社

OXFORD UNIV PRESS INC
DOI: 10.1093/cid/civ579

关键词

tuberculosis; antibiotic resistance; fitness costs; mathematical modeling

资金

  1. Bill & Melinda Gates Foundation [21675/OPP1084276, 19790.01]
  2. Medical Research Council (UK) [MR/J005088/1]
  3. Centers for Disease Control and Prevention/President's Emergency Plan for AIDS Relief via Aurum Institute [U2GPS0008111]
  4. US Agency for International Development/International Union Against Tuberculosis and Lung Disease/The Union North America (TREAT TB: Technology, Research, Education, and Technical Assistance for Tuberculosis)
  5. Engineering and Physical Sciences Research Council [EPSRC EP/K026003/1]
  6. Medical Scientist Training Program from National Institutes of Health [T32 GM007309]
  7. Paul and Daisy Soros Fellowships for New Americans scholarship
  8. Engineering and Physical Sciences Research Council [EP/K026003/1] Funding Source: researchfish
  9. Medical Research Council [MR/J005088/1] Funding Source: researchfish
  10. EPSRC [EP/K026003/1] Funding Source: UKRI
  11. MRC [MR/J005088/1] Funding Source: UKRI

向作者/读者索取更多资源

Background. Drug resistance poses a serious challenge for the control of tuberculosis in many settings. It is well established that the expected future trend in resistance depends on the reproductive fitness of drug-resistant Mycobacterium tuberculosis. However, the variability in fitness between strains with different resistance-conferring mutations has been largely ignored when making these predictions. Methods. We developed a novel approach for incorporating the variable fitness costs of drug resistance-conferring mutations and for tracking this distribution of fitness costs over time within a transmission model. We used this approach to describe the effects of realistic fitness cost distributions on the future prevalence of drug-resistant tuberculosis. Results. The shape of the distribution of fitness costs was a strong predictor of the long-term prevalence of resistance. While, as expected, lower average fitness costs of drug resistance-conferring mutations were associated with more severe epidemics of drug-resistant tuberculosis, fitness distributions with greater variance also led to higher levels of drug resistance. For example, compared to simulations in which the fitness cost of resistance was fixed, introducing a realistic amount of variance resulted in a 40% increase in prevalence of drug-resistant tuberculosis after 20 years. Conclusions. The differences in the fitness costs associated with drug resistance-conferring mutations are a key determinant of the future burden of drug-resistant tuberculosis. Future studies that can better establish the range of fitness costs associated with drug resistance-conferring mutations will improve projections and thus facilitate better public health planning efforts.

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