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

Gwenan M. Knight, Caroline Colijn, Sourya Shrestha, Mariam Fofana, Frank Cobelens, Richard G. White, David W. Dowdy, Ted Cohen

Research output: Contribution to journalArticlepeer-review

Abstract

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 resistanceconferring 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.

Original languageEnglish (US)
Pages (from-to)S147-S154
JournalClinical Infectious Diseases
Volume61
DOIs
StatePublished - Oct 15 2015

Keywords

  • Tuberculosis
  • antibiotic resistance
  • fitness costs
  • mathematical modeling

ASJC Scopus subject areas

  • Microbiology (medical)
  • Infectious Diseases

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