title: The development of an age-structured model for trachoma transmission dynamics, pathogenesis and control.
abstract: BACKGROUND
  Trachoma, the worldwide leading infectious cause of blindness, is due to repeated conjunctival infection with Chlamydia trachomatis. The effects of control interventions on population levels of infection and active disease can be promptly measured, but the effects on severe ocular sequelae require long-term monitoring. We present an age-structured mathematical model of trachoma transmission and disease to predict the impact of interventions on the prevalence of blinding trachoma.
  
  
  RESULTS
  The model is based on the concept of multiple reinfections leading to progressive conjunctival scarring, trichiasis, corneal opacity and blindness. It also includes aspects of trachoma natural history, such as an increasing rate of recovery from infection and a decreasing chlamydial load with subsequent infections that depend upon a (presumed) acquired immunity that clears infection with age more rapidly. Parameters were estimated using maximum likelihood by fitting the model to pre-control infection prevalence data from hypo-, meso- and hyperendemic communities from The Gambia and Tanzania. The model reproduces key features of trachoma epidemiology: 1) the age-profile of infection prevalence, which increases to a peak at very young ages and declines at older ages; 2) a shift in this prevalence peak, toward younger ages in higher force of infection environments; 3) a raised overall profile of infection prevalence with higher force of infection; and 4) a rising profile, with age, of the prevalence of the ensuing severe sequelae (trachomatous scarring, trichiasis), as well as estimates of the number of infections that need to occur before these sequelae appear.
  
  
  CONCLUSIONS
  We present a framework that is sufficiently comprehensive to examine the outcomes of the A (antibiotic) component of the SAFE strategy on disease. The suitability of the model for representing population-level patterns of infection and disease sequelae is discussed in view of the individual processes leading to these patterns.
authors.affiliation: Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom. m.gambhir@imperial.ac.uk
authors.forename: Manoj
authors.initials: M
authors.lastname: Gambhir
authors.forename: Maria-Gloria
authors.initials: MG
authors.lastname: Basáñez
authors.forename: Matthew J
authors.initials: MJ
authors.lastname: Burton
authors.forename: Anthony W
authors.initials: AW
authors.lastname: Solomon
authors.forename: Robin L
authors.initials: RL
authors.lastname: Bailey
authors.forename: Martin J
authors.initials: MJ
authors.lastname: Holland
authors.forename: Isobel M
authors.initials: IM
authors.lastname: Blake
authors.forename: Christl A
authors.initials: CA
authors.lastname: Donnelly
authors.forename: Ibrahim
authors.initials: I
authors.lastname: Jabr
authors.forename: David C
authors.initials: DC
authors.lastname: Mabey
authors.forename: Nicholas C
authors.initials: NC
authors.lastname: Grassly
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000900:Anti-Bacterial Agents / Q000627:therapeutic use; D019072:Antibiotic Prophylaxis; D002648:Child; D002675:Child, Preschool; D002692:Chlamydia trachomatis / Q000302:isolation & purification* / Q000472:pathogenicity*; D005260:Female; D005714:Gambia / Q000453:epidemiology; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D015995:Prevalence; D013636:Tanzania / Q000453:epidemiology; D014141:Trachoma / Q000188:drug therapy / Q000453:epidemiology* / Q000517:prevention & control / Q000635:transmission*; D055815:Young Adult
chemical_list: D000900:Anti-Bacterial Agents