title: Estimating rates of carriage acquisition and clearance and competitive ability for pneumococcal serotypes in Kenya with a Markov transition model.
abstract: BACKGROUND
  There are more than 90 serotypes of Streptococcus pneumoniae, with varying biologic and epidemiologic properties. Animal studies suggest that carriage induces an acquired immune response that reduces duration of colonization in a nonserotype-specific fashion.
  
  
  METHODS
  We studied pneumococcal nasopharyngeal carriage longitudinally in Kenyan children 3-59 months of age, following up positive swabs at days 2, 4, 8, 16, and 32 and then monthly thereafter until 2 swabs were negative for the original serotype. As previously reported, 1868/2840 (66%) of children swabbed at baseline were positive. We estimated acquisition, clearance, and competition parameters for 27 serotypes using a Markov transition model.
  
  
  RESULTS
  Point estimates of type-specific acquisition rates ranged from 0.00025/d (type 1) to 0.0031/d (type 19F). Point estimates of time to clearance (inverse of type-specific immune clearance rate) ranged from 28 days (type 20) to 124 days (type 6A). For the serotype most resistant to competition (type 19F), acquisition of other serotypes was 52% less likely (95% confidence interval = 37%-63%) than in an uncolonized host. Fitness components (carriage duration, acquisition rate, lack of susceptibility to competition) were positively correlated with each other and with baseline prevalence, and were associated with biologic properties previously shown to associate with serotype. Duration of carriage declined with age for most serotypes.
  
  
  CONCLUSIONS
  Common S. pneumoniae serotypes appear superior in many dimensions of fitness. Differences in rate of immune clearance are attenuated as children age and become capable of more rapid clearance of the longest-lived serotypes. These findings provide information for comparison after introduction of pneumococcal conjugate vaccine.
authors.affiliation: Center for Communicable Disease Dynamics and Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA. mlipsitc@hsph.harvard.edu
authors.forename: Marc
authors.initials: M
authors.lastname: Lipsitch
authors.forename: Osman
authors.initials: O
authors.lastname: Abdullahi
authors.forename: Alexander
authors.initials: A
authors.lastname: DʼAmour
authors.forename: Wen
authors.initials: W
authors.lastname: Xie
authors.forename: Daniel M
authors.initials: DM
authors.lastname: Weinberger
authors.forename: Eric
authors.initials: E
authors.lastname: Tchetgen Tchetgen
authors.forename: J Anthony G
authors.initials: JA
authors.lastname: Scott
mesh_terms: D000367:Age Factors; D002675:Child, Preschool; D005500:Follow-Up Studies; D056084:Genetic Fitness; D006801:Humans; D007223:Infant; D007630:Kenya; D008390:Markov Chains; D056265:Microbial Interactions; D008954:Models, Biological; D009305:Nasopharynx / Q000382:microbiology*; D012703:Serotyping; D013296:Streptococcus pneumoniae / Q000145:classification / Q000302:isolation & purification / Q000502:physiology*