title: The fitness cost of antibiotic resistance in Streptococcus pneumoniae: insight from the field.
abstract: BACKGROUND
  Laboratory studies have suggested that antibiotic resistance may result in decreased fitness in the bacteria that harbor it. Observational studies have supported this, but due to ethical and practical considerations, it is rare to have experimental control over antibiotic prescription rates.
  
  
  RESULTS
  We analyze data from a 54-month longitudinal trial that monitored pneumococcal drug resistance during and after biannual mass distribution of azithromycin for the elimination of the blinding eye disease, trachoma. Prescription of azithromycin and antibiotics that can create cross-resistance to it is rare in this part of the world. As a result, we were able to follow trends in resistance with minimal influence from unmeasured antibiotic use. Using these data, we fit a probabilistic disease transmission model that included two resistant strains, corresponding to the two dominant modes of resistance to macrolide antibiotics. We estimated the relative fitness of these two strains to be 0.86 (95% CI 0.80 to 0.90), and 0.88 (95% CI 0.82 to 0.93), relative to antibiotic-sensitive strains. We then used these estimates to predict that, within 5 years of the last antibiotic treatment, there would be a 95% chance of elimination of macrolide resistance by intra-species competition alone.
  
  
  CONCLUSIONS
  Although it is quite possible that the fitness cost of macrolide resistance is sufficient to ensure its eventual elimination in the absence of antibiotic selection, this process takes time, and prevention is likely the best policy in the fight against resistance.
authors.affiliation: Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, California, United States of America.
authors.forename: M Cyrus
authors.initials: MC
authors.lastname: Maher
authors.forename: Wondu
authors.initials: W
authors.lastname: Alemayehu
authors.forename: Takele
authors.initials: T
authors.lastname: Lakew
authors.forename: Bruce D
authors.initials: BD
authors.lastname: Gaynor
authors.forename: Sara
authors.initials: S
authors.lastname: Haug
authors.forename: Vicky
authors.initials: V
authors.lastname: Cevallos
authors.forename: Jeremy D
authors.initials: JD
authors.lastname: Keenan
authors.forename: Thomas M
authors.initials: TM
authors.lastname: Lietman
authors.forename: Travis C
authors.initials: TC
authors.lastname: Porco
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D000900:Anti-Bacterial Agents / Q000627:therapeutic use; D017963:Azithromycin / Q000627:therapeutic use*; D001426:Bacterial Proteins / Q000235:genetics; D024881:Drug Resistance, Bacterial / Q000187:drug effects* / Q000235:genetics; D005002:Ethiopia / Q000453:epidemiology; D056726:Genetic Association Studies / Q000706:statistics & numerical data; D006801:Humans; D008565:Membrane Proteins / Q000235:genetics; D050296:Microbial Viability / Q000187:drug effects / Q000235:genetics; D008957:Models, Genetic; D011008:Pneumococcal Infections / Q000188:drug therapy* / Q000453:epidemiology / Q000382:microbiology; D015995:Prevalence; D013296:Streptococcus pneumoniae / Q000187:drug effects* / Q000235:genetics; D014141:Trachoma / Q000382:microbiology / Q000517:prevention & control
chemical_list: D000900:Anti-Bacterial Agents; D001426:Bacterial Proteins; C117866:MefA protein, Streptococcus; C431304:MefE protein, Streptococcus pneumoniae; D008565:Membrane Proteins; D017963:Azithromycin