Seroconversion Rate for Post-Validation Surveillance of Trachoma Open Access
Randall, Jessica (Spring 2019)
Abstract
Purpose: The WHO is considering the utility of serological surveillance for trachoma. If comparable to clinical diagnoses, this type of surveillance would be a cost-effective and sustainable solution. Our serological survey from two districts in The Republic of Togo, a country now known to have reached the threshold for elimination of trachoma as a public health problem, supports the use of a seroconversion rate as an estimate of force of infection in non-endemic areas.
Methods: We conducted serological surveillance on 2915 participants 1-9 years old in two districts purposefully selected as the most likely to have trachoma if it would be in the country at all. Each participant had a finger-prick blood sample collected onto filter paper. We fit a logistic regression model to estimate seroprevalence. Participants had blood collected to measure antibody responses to the C. trachomatis (CT) antigens Pgp3 and Ct694 by multiplex bead-based immunoassay (MBA), the lab-based dipstick Pgp3 lateral flow assay (LFA), and the field based cassette Pgp3 lateral flow assay.We calculated a seroconversion rate for each antigen by fitting a reversible serocatalytic model which assumes zero seroreversion. We report median fluorescence intensity-background (MFI-BG ), seroprevalence, age-specific seroprevalence and seroconversion rate.
Results: Out of 2915 samples, 96% were negative by the MBA and LFA. Age-specific seroprevalence was estimated using a logistic regression model. Mean SCRs for each antigen and assay method were estimated by taking the mean of each age-specific seroconversion rate.
Conclusions: Our results support those of a parent study that found that the clinical diagnosis of trachoma, trachomatous inflammation- follicular (TF) falls below the 5% WHO threshold of elimination of trachoma as a public health problem. Our calculation of a seroconversion rate, an estimation of the force of infection, indicated no active transmission.
Table of Contents
Introduction: ........................................................................................................................1
Methods: ..............................................................................................................................3
Results: ................................................................................................................................6
Discussion: ...........................................................................................................................8
Conclusions and Recommendations: ..................................................................................... 10
References: ..........................................................................................................................11
Tables and Figures: ...............................................................................................................13
Appendix…………………………………………………………………….…………...................................15
About this Master's Thesis
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Primary PDF
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Seroconversion Rate for Post-Validation Surveillance of Trachoma () | 2019-04-18 12:42:43 -0400 |
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Supplemental Files
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SAS Code (SAS code for analysis in the project) | 2019-04-18 12:42:46 -0400 |
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Python Code (Python code for all graphs used in thesis) | 2019-04-18 12:42:50 -0400 |
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Jupyter Notebook (Jupyter Notebook of Python code of Graphs) | 2019-04-18 12:42:54 -0400 |
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