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Kinetics of the IgG antibody response to pertussis toxin after infection with B. pertussis

Published online by Cambridge University Press:  10 January 2003

P. F. M. TEUNIS
Affiliation:
Computerization and Methodological Consultancy Unit, National Institute for Public Health and the Environment, PO Box 1, 3720 BA Bilthoven, The Netherlands
O. G. VAN DER HEIJDEN
Affiliation:
Centre for Infectious Diseases Epidemiology, National Institute for Public Health and the Environment, PO Box 1, 3720 BA Bilthoven, The Netherlands
H. E. DE MELKER
Affiliation:
Centre for Infectious Diseases Epidemiology, National Institute for Public Health and the Environment, PO Box 1, 3720 BA Bilthoven, The Netherlands
J. F. P. SCHELLEKENS
Affiliation:
Laboratory of Infectious Diseases Screening, National Institute for Public Health and the Environment, PO Box 1, 3720 BA Bilthoven, The Netherlands
F. G. A. VERSTEEGH
Affiliation:
Groene Hart Ziekenhuis, Department of Pediatrics, Gouda, The Netherlands
M. E. E. KRETZSCHMAR
Affiliation:
Centre for Infectious Diseases Epidemiology, National Institute for Public Health and the Environment, PO Box 1, 3720 BA Bilthoven, The Netherlands
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Abstract

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We aimed to provide a quantitative description of decay in pertussis antibody levels to aid in finding a serological estimate of the incidence of pertussis. The serum IgG response against pertussis toxin was studied in a group of clinically diagnosed patients. Individual records consisted of repeated serum IgG measurements at irregular intervals for up to 10 years post diagnosis. These data were analysed with a nonlinear regression model taking into account censoring at upper and lower threshold levels, measurement errors, and individual variation in the shape and magnitude of the immune response. There was considerable variation between individual responses, both in strength (amplitude) and duration (shape). The inverse model relating IgG levels to time from infection (diagnosis) can be applied to cross-sectional IgG data to generate distributions of times from infection, which may be used to calculate infection rates and their variation, in populations sampled for cross-sectional IgG data.

Type
Research Article
Copyright
2002 Cambridge University Press