Article

Compound processes as models for clumped parasite data

Institute of Mathematics, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland; Institute of Parasitology, University of Zurich, Switzerland; School of Veterinary Medicine, Ross University, PO Box 334, Basseterre, St Kitts, West Indies
Mathematical Biosciences DOI:10.1016/j.mbs.2009.08.007 pp.27-35

ABSTRACT Compound processes are proposed as models for the acquisition of hydatid cysts in sheep, caused by the parasite Echinococcus granulosus. The hypothesis of a clumped infection process against single ingestions is tested and it is shown that the clump-based approach provides a more accurate description of the two data sets investigated. Models with simple and mixed Poisson incidence processes and different clump size distributions are compared. A mixed Poisson incidence process with a zero-truncated negative binomial distribution for the clump sizes is shown to give an adequate description, suggesting that the acquisition of hydatid cysts in the sheep population is heterogeneous, and that the clump sizes are aggregated. The estimates of the parameters derived from the data take plausible values. The average infection rate and the clump size distribution are comparable in both data sets. Goodness-of-fit measures indicate that the model fits the data reasonably well.

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Keywords

accurate description
 
adequate description
 
clump size distribution
 
clump sizes
 
clump-based approach
 
clumped infection process
 
Compound processes
 
data sets
 
different clump size distributions
 
estimates
 
Goodness-of-fit measures
 
hydatid cysts
 
mixed Poisson incidence process
 
mixed Poisson incidence processes
 
parasite Echinococcus granulosus
 
plausible values
 
single ingestions
 
two data sets
 
zero-truncated negative binomial distribution