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Compound processes as models for clumped parasite data


Heinzmann, D; Barbour, A D; Torgerson, P R (2009). Compound processes as models for clumped parasite data. Mathematical Biosciences, 222(1):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.

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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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:05 Vetsuisse Faculty > Institute of Parasitology
04 Faculty of Medicine > Institute of Parasitology

07 Faculty of Science > Institute of Mathematics
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
600 Technology
510 Mathematics
Scopus Subject Areas:Physical Sciences > Statistics and Probability
Physical Sciences > Modeling and Simulation
Life Sciences > General Biochemistry, Genetics and Molecular Biology
Life Sciences > General Immunology and Microbiology
Life Sciences > General Agricultural and Biological Sciences
Physical Sciences > Applied Mathematics
Language:English
Date:2009
Deposited On:04 Nov 2009 08:03
Last Modified:03 Nov 2023 03:07
Publisher:Elsevier
ISSN:0025-5564
OA Status:Green
Publisher DOI:https://doi.org/10.1016/j.mbs.2009.08.007
PubMed ID:19715705
  • Content: Accepted Version