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The development of an age-structured model for trachoma transmission dynamics, pathogenesis and control.

Gambhir M, Basáñez MG, Burton MJ, Solomon AW, Bailey RL, Holland MJ, Blake IM, Donnelly CA, Jabr I, Mabey DC, Grassly NC - PLoS Negl Trop Dis (2009)

Bottom Line: We present an age-structured mathematical model of trachoma transmission and disease to predict the impact of interventions on the prevalence of blinding trachoma.The model is based on the concept of multiple reinfections leading to progressive conjunctival scarring, trichiasis, corneal opacity and blindness.We present a framework that is sufficiently comprehensive to examine the outcomes of the A (antibiotic) component of the SAFE strategy on disease.

View Article: PubMed Central - PubMed

Affiliation: Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom. m.gambhir@imperial.ac.uk

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.

Methodology/principal findings: 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/significance: 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.

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Related in: MedlinePlus

The age-dependent prevalence of the disease sequelae in a hyperendemic setting.Prevalence curves for trachomatous scarring (solid line) and trachomatous trichiasis (dotted line) are shown along with the data from [28] (circles (TS) and squares (TT) and 95%CI error bars), which were collected from the same district as the data of West et al. [25] during the mid-1990s, prior to drug treatment interventions. An assumption made here is that the incidence of the sequelae did not change over the decade prior to the first mass drug administration.
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pntd-0000462-g005: The age-dependent prevalence of the disease sequelae in a hyperendemic setting.Prevalence curves for trachomatous scarring (solid line) and trachomatous trichiasis (dotted line) are shown along with the data from [28] (circles (TS) and squares (TT) and 95%CI error bars), which were collected from the same district as the data of West et al. [25] during the mid-1990s, prior to drug treatment interventions. An assumption made here is that the incidence of the sequelae did not change over the decade prior to the first mass drug administration.

Mentions: The threshold numbers of infections necessary for individuals to show signs of each of the sequelae were calculated for the hyperendemic setting. These thresholds were estimated by maximum likelihood using the published data of Munoz et al. [28], for the age-dependent prevalence of each of the disease sequelae. The maximum likelihood estimate for the threshold number of infections required for TS was 102 and for TT it was 151. In terms of the natural history of trachoma infection, disease, and disease sequelae, it is assumed here that these threshold values do not vary over the different endemicity levels but should be reached at different ages according to the intensity of transmission—individuals living in areas of different endemicity are assumed to show signs of each of the disease sequelae after having experienced the same number of infections, but they experience the sequelae earlier in their lives in those environments in which they are infected more frequently. The threshold infection numbers estimated here were used to generate the curves shown in Figure 5.


The development of an age-structured model for trachoma transmission dynamics, pathogenesis and control.

Gambhir M, Basáñez MG, Burton MJ, Solomon AW, Bailey RL, Holland MJ, Blake IM, Donnelly CA, Jabr I, Mabey DC, Grassly NC - PLoS Negl Trop Dis (2009)

The age-dependent prevalence of the disease sequelae in a hyperendemic setting.Prevalence curves for trachomatous scarring (solid line) and trachomatous trichiasis (dotted line) are shown along with the data from [28] (circles (TS) and squares (TT) and 95%CI error bars), which were collected from the same district as the data of West et al. [25] during the mid-1990s, prior to drug treatment interventions. An assumption made here is that the incidence of the sequelae did not change over the decade prior to the first mass drug administration.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2691478&req=5

pntd-0000462-g005: The age-dependent prevalence of the disease sequelae in a hyperendemic setting.Prevalence curves for trachomatous scarring (solid line) and trachomatous trichiasis (dotted line) are shown along with the data from [28] (circles (TS) and squares (TT) and 95%CI error bars), which were collected from the same district as the data of West et al. [25] during the mid-1990s, prior to drug treatment interventions. An assumption made here is that the incidence of the sequelae did not change over the decade prior to the first mass drug administration.
Mentions: The threshold numbers of infections necessary for individuals to show signs of each of the sequelae were calculated for the hyperendemic setting. These thresholds were estimated by maximum likelihood using the published data of Munoz et al. [28], for the age-dependent prevalence of each of the disease sequelae. The maximum likelihood estimate for the threshold number of infections required for TS was 102 and for TT it was 151. In terms of the natural history of trachoma infection, disease, and disease sequelae, it is assumed here that these threshold values do not vary over the different endemicity levels but should be reached at different ages according to the intensity of transmission—individuals living in areas of different endemicity are assumed to show signs of each of the disease sequelae after having experienced the same number of infections, but they experience the sequelae earlier in their lives in those environments in which they are infected more frequently. The threshold infection numbers estimated here were used to generate the curves shown in Figure 5.

Bottom Line: We present an age-structured mathematical model of trachoma transmission and disease to predict the impact of interventions on the prevalence of blinding trachoma.The model is based on the concept of multiple reinfections leading to progressive conjunctival scarring, trichiasis, corneal opacity and blindness.We present a framework that is sufficiently comprehensive to examine the outcomes of the A (antibiotic) component of the SAFE strategy on disease.

View Article: PubMed Central - PubMed

Affiliation: Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom. m.gambhir@imperial.ac.uk

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.

Methodology/principal findings: 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/significance: 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.

Show MeSH
Related in: MedlinePlus