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Bayesian age-stage modelling of Plasmodium falciparum sequestered parasite loads in severe malaria patients

Published online by Cambridge University Press:  23 August 2004

T. SMITH ,
K. DIETZ ,
P. VOUNATSOU ,
I. MÜLLER ,
M. ENGLISH  and
K. MARSH
T. SMITH
Affiliation:
Swiss Tropical Institute, Socinstrasse 57, Postfach, CH-4002, Basel, Switzerland
K. DIETZ
Affiliation:
Institut für Medizinsche Biometrie, Westbahnhofstrasse 55, D-72070, Tübingen, Germany
P. VOUNATSOU
Affiliation:
Swiss Tropical Institute, Socinstrasse 57, Postfach, CH-4002, Basel, Switzerland
I. MÜLLER
Affiliation:
Swiss Tropical Institute, Socinstrasse 57, Postfach, CH-4002, Basel, Switzerland Current address: Papua New Guinea Institute of Medical Research, PO Box 60, Goroka, EHP, Papua New Guinea.
M. ENGLISH
Affiliation:
Kenya Medical Research Institute Laboratories (KEMRI)/Wellcome Trust Kilifi District Hospital, PO Box 230, Kilifi, Kenya
K. MARSH
Affiliation:
Kenya Medical Research Institute Laboratories (KEMRI)/Wellcome Trust Kilifi District Hospital, PO Box 230, Kilifi, Kenya
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Abstract

A discrete-time age-stage model is proposed for estimating the number of sequestered parasites in severe malaria patients. A Bayesian Markov chain Monte Carlo (MCMC) approach is used to model the dynamics of Plasmodium falciparum parasitaemia in 107 paediatric patients in a randomized controlled trial of quinine and artemether in Kenya, in whom 4-hourly peripheral parasitaemia determinations were made. The MCMC approach allows the model to be fitted simultaneously to the entire dataset, providing point and interval estimates for both population and individual patient parameters. Analysis of a simulated dataset indicated that the models gave good estimates of the distribution of parasites between different stages on enrolment, for patients with a wide range of initial states. The analysis of the Kenyan patients suggested that there is considerable variation between patients within the same centre, in both the proportion of sequestered parasites and the intrinsic rate of increase of the parasite population in the absence of treatment. The resulting models should prove a useful tool for cross-validating biochemical approaches for estimating the sequestered load.

Keywords

sequestrationmathematical modelKenya
Type
Research Article
Information
Parasitology , Volume 129 , Issue 3 , September 2004 , pp. 289 - 299
Copyright
© 2004 Cambridge University Press

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