03370nas a2200493   4500000000100000008004100001653001600042653001300058653001300071653001500084653002400099653001600123653000900139653001100148653001100159653001100170653002600181653002100207653001000228653002700238653002600265653002200291653000900313653001600322653001000338653001500348100001400363700001600377700001300393700001400406700001300420700001500433700001200448700001600460700001100476700001200487700001500499245010900514856007800623300000900701490000600710520214600716022001402862       2009                            d10aYoung Adult10aTrachoma10aTanzania10aPrevalence10aModels, Theoretical10aMiddle Aged10aMale10aHumans10aGambia10aFemale10aChlamydia trachomatis10aChild, Preschool10aChild10aAntibiotic Prophylaxis10aAnti-Bacterial Agents10aAged, 80 and over10aAged10aAge Factors10aAdult10aAdolescent1 aGambhir M1 aBasáñez M1 aBurton M1 aSolomon A1 aBailey R1 aHolland MJ1 aBlake I1 aDonnelly CA1 aJabr I1 aMabey D1 aGrassly NC00aThe development of an age-structured model for trachoma transmission dynamics, pathogenesis and control.  uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2691478/pdf/pntd.0000462.pdf  ae4620 v33 a<p><strong>BACKGROUND: </strong>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.</p>

<p><strong>METHODOLOGY/PRINCIPAL FINDINGS: </strong>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.</p>

<p><strong>CONCLUSIONS/SIGNIFICANCE: </strong>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.</p>
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