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A statistical approach to schistosome population dynamics and estimation of the life-span of Schistosoma mansoni in man

Published online by Cambridge University Press:  06 April 2009

A. J. C. Fulford
Affiliation:
Department of Pathology, University of Cambridge, Tennis Court Road, Cambridge CB2 1QP
A. E. Butterworth
Affiliation:
Department of Pathology, University of Cambridge, Tennis Court Road, Cambridge CB2 1QP
J. H. Ouma
Affiliation:
Division of Vector-Borne Diseases, Ministry of Health, P.O. Box 20750, Nairobi, Kenya
R. F. Sturrock
Affiliation:
Department of Medical Parasitology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT

Summary

Dynamic models which predict changes in the intensity of schistosome infection with host age are fitted to pre-intervention Schistosoma mansoni data from Kenya. Age-specific post-treatment-reinfection data are used to estimate the force of infection, thus enabling investigation of the rate of worm death. An empirical and statistical approach is taken to the model fitting: where possible, distributional properties and function relationships are obtained from the data rather than assumed from theory. Attempts are made to remove known sources of bias. Maximum likelihood techniques, employed to allow for error in both the pre-intervention and reinfection data, yield confidence intervals for the worm life-span (CI95% = 5·7–10·5 years) and demonstrate that the worm death rate is unlikely to vary with host age. The possibilities and limitations of fitting dynamic models to data are discussed. We conclude that a detailed, quantitative approach will be necessary if progress is to be made with the interpretation of epidemiological data and the models intended to describe them.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1995

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