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Serology for trachoma surveillance after cessation of mass drug administration.

Martin DL, Bid R, Sandi F, Goodhew EB, Massae PA, Lasway A, Philippin H, Makupa W, Molina S, Holland MJ, Mabey DC, Drakeley C, Lammie PJ, Solomon AW - PLoS Negl Trop Dis (2015)

Bottom Line: Among 1-9 year olds, TF prevalence was 6.5%, whereas only 3.5% were seropositive.Force of infection modelling indicated a 10-fold decrease in seroconversion rate at a time corresponding to MDA commencement.Without baseline serological data, the inferences we can make about antibody status before MDA and the longevity of the antibody response are limited, though our use of catalytic modelling overcomes some of these limitations.

View Article: PubMed Central - PubMed

Affiliation: Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.

ABSTRACT

Background: Trachoma, caused by Chlamydia trachomatis (Ct), is the leading infectious cause of blindness worldwide. Yearly azithromycin mass drug administration (MDA) plays a central role in efforts to eliminate blinding trachoma as a public health problem. Programmatic decision-making is currently based on the prevalence of the clinical sign "trachomatous inflammation-follicular" (TF) in children. We sought to test alternative tools for trachoma surveillance based on serology in the 12-year cohort of Kahe Mpya, Rombo District, Tanzania, where ocular chlamydial infection was eliminated with azithromycin MDA by 2005.

Methodology and principal findings: The present study was a community-based cross-sectional survey in Kahe Mpya. Of 989 residents, 571 people aged 6 months to 87 years were enrolled: 58% of the total population and 73% of 1-9 year olds, the key WHO indicator age group. Participants were examined for TF, had conjunctival swabs collected for nucleic acid amplification test (NAAT)-based detection of Ct, and blood collected for analysis of antibodies to the Ct antigens pgp3 and CT694 by multiplex bead-based immunoassay. Seroconversion rate was used to estimate changes in the force of infection in a reversible catalytic model. No conjunctival swabs tested positive for Ct infection by NAAT. Among 1-9 year olds, TF prevalence was 6.5%, whereas only 3.5% were seropositive. Force of infection modelling indicated a 10-fold decrease in seroconversion rate at a time corresponding to MDA commencement. Without baseline serological data, the inferences we can make about antibody status before MDA and the longevity of the antibody response are limited, though our use of catalytic modelling overcomes some of these limitations.

Conclusions/significance: Serologic tests support NAAT findings of very low to zero prevalence of ocular Ct in this community and have potential to provide objective measures of transmission and useful surveillance tools for trachoma elimination programs.

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Related in: MedlinePlus

Force of infection modelling of seroconversion rates before and after MDA.A. Maximum likelihood fits from reversible catalytic equilibrium model for antibody responses either pgp3 or CT694 is shown. X-axis represents the time in years that each model has a change point. The y-axis is the log-likelihoods from each model where log-likelihoods are rescaled against a maximum of 0 and a log-likelihood above -2 is an approximate 95% confidence interval when the change occurred. B. A model in which SCR changed 10 years previously, to represent the time at which MDA ceased, had a better fit than the model that assumed the SCR had remained constant (likelihood ratio test X2 = 45.4 p,0.0001). The triangles represent deciles of observed seroprevalence; the solid blue line represents the predicted values based on the model with dotted lines and the 95% CI.
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pntd.0003555.g002: Force of infection modelling of seroconversion rates before and after MDA.A. Maximum likelihood fits from reversible catalytic equilibrium model for antibody responses either pgp3 or CT694 is shown. X-axis represents the time in years that each model has a change point. The y-axis is the log-likelihoods from each model where log-likelihoods are rescaled against a maximum of 0 and a log-likelihood above -2 is an approximate 95% confidence interval when the change occurred. B. A model in which SCR changed 10 years previously, to represent the time at which MDA ceased, had a better fit than the model that assumed the SCR had remained constant (likelihood ratio test X2 = 45.4 p,0.0001). The triangles represent deciles of observed seroprevalence; the solid blue line represents the predicted values based on the model with dotted lines and the 95% CI.

Mentions: When a seroconversion model, which allowed for a single change in SCR, was fitted to the data, the best fit was provided by a change in transmission between 10–15 years previously, consistent with the timing of MDA in the years 2000 and 2002 (Fig. 2A for antibody responses to either antigen; responses to individual antigens gave similar profiles). We chose a model in which SCR changed 10 years previously, which had a better fit than the model that assumed the SCR had remained constant (Fig. 2B). The change in SCR before and after this change point is approximately a 10-fold reduction, from a pre-MDA SCR of 0.0448 (95%CI 0.0373–0.0537) to a post-MDA SCR of 0.004 (95%CI 0.0024–0.0093)].


Serology for trachoma surveillance after cessation of mass drug administration.

Martin DL, Bid R, Sandi F, Goodhew EB, Massae PA, Lasway A, Philippin H, Makupa W, Molina S, Holland MJ, Mabey DC, Drakeley C, Lammie PJ, Solomon AW - PLoS Negl Trop Dis (2015)

Force of infection modelling of seroconversion rates before and after MDA.A. Maximum likelihood fits from reversible catalytic equilibrium model for antibody responses either pgp3 or CT694 is shown. X-axis represents the time in years that each model has a change point. The y-axis is the log-likelihoods from each model where log-likelihoods are rescaled against a maximum of 0 and a log-likelihood above -2 is an approximate 95% confidence interval when the change occurred. B. A model in which SCR changed 10 years previously, to represent the time at which MDA ceased, had a better fit than the model that assumed the SCR had remained constant (likelihood ratio test X2 = 45.4 p,0.0001). The triangles represent deciles of observed seroprevalence; the solid blue line represents the predicted values based on the model with dotted lines and the 95% CI.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4340913&req=5

pntd.0003555.g002: Force of infection modelling of seroconversion rates before and after MDA.A. Maximum likelihood fits from reversible catalytic equilibrium model for antibody responses either pgp3 or CT694 is shown. X-axis represents the time in years that each model has a change point. The y-axis is the log-likelihoods from each model where log-likelihoods are rescaled against a maximum of 0 and a log-likelihood above -2 is an approximate 95% confidence interval when the change occurred. B. A model in which SCR changed 10 years previously, to represent the time at which MDA ceased, had a better fit than the model that assumed the SCR had remained constant (likelihood ratio test X2 = 45.4 p,0.0001). The triangles represent deciles of observed seroprevalence; the solid blue line represents the predicted values based on the model with dotted lines and the 95% CI.
Mentions: When a seroconversion model, which allowed for a single change in SCR, was fitted to the data, the best fit was provided by a change in transmission between 10–15 years previously, consistent with the timing of MDA in the years 2000 and 2002 (Fig. 2A for antibody responses to either antigen; responses to individual antigens gave similar profiles). We chose a model in which SCR changed 10 years previously, which had a better fit than the model that assumed the SCR had remained constant (Fig. 2B). The change in SCR before and after this change point is approximately a 10-fold reduction, from a pre-MDA SCR of 0.0448 (95%CI 0.0373–0.0537) to a post-MDA SCR of 0.004 (95%CI 0.0024–0.0093)].

Bottom Line: Among 1-9 year olds, TF prevalence was 6.5%, whereas only 3.5% were seropositive.Force of infection modelling indicated a 10-fold decrease in seroconversion rate at a time corresponding to MDA commencement.Without baseline serological data, the inferences we can make about antibody status before MDA and the longevity of the antibody response are limited, though our use of catalytic modelling overcomes some of these limitations.

View Article: PubMed Central - PubMed

Affiliation: Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.

ABSTRACT

Background: Trachoma, caused by Chlamydia trachomatis (Ct), is the leading infectious cause of blindness worldwide. Yearly azithromycin mass drug administration (MDA) plays a central role in efforts to eliminate blinding trachoma as a public health problem. Programmatic decision-making is currently based on the prevalence of the clinical sign "trachomatous inflammation-follicular" (TF) in children. We sought to test alternative tools for trachoma surveillance based on serology in the 12-year cohort of Kahe Mpya, Rombo District, Tanzania, where ocular chlamydial infection was eliminated with azithromycin MDA by 2005.

Methodology and principal findings: The present study was a community-based cross-sectional survey in Kahe Mpya. Of 989 residents, 571 people aged 6 months to 87 years were enrolled: 58% of the total population and 73% of 1-9 year olds, the key WHO indicator age group. Participants were examined for TF, had conjunctival swabs collected for nucleic acid amplification test (NAAT)-based detection of Ct, and blood collected for analysis of antibodies to the Ct antigens pgp3 and CT694 by multiplex bead-based immunoassay. Seroconversion rate was used to estimate changes in the force of infection in a reversible catalytic model. No conjunctival swabs tested positive for Ct infection by NAAT. Among 1-9 year olds, TF prevalence was 6.5%, whereas only 3.5% were seropositive. Force of infection modelling indicated a 10-fold decrease in seroconversion rate at a time corresponding to MDA commencement. Without baseline serological data, the inferences we can make about antibody status before MDA and the longevity of the antibody response are limited, though our use of catalytic modelling overcomes some of these limitations.

Conclusions/significance: Serologic tests support NAAT findings of very low to zero prevalence of ocular Ct in this community and have potential to provide objective measures of transmission and useful surveillance tools for trachoma elimination programs.

Show MeSH
Related in: MedlinePlus