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Evaluating parasite densities and estimation of parameters in transmission systems


Heinzmann, D; Torgerson, P R (2008). Evaluating parasite densities and estimation of parameters in transmission systems. Parasite (Paris, France), 15(3):477-483.

Abstract

Mathematical modelling of parasite transmission systems can provide useful information about host parasite interactions and biology and parasite population dynamics. In addition good predictive models may assist in designing control programmes to reduce the burden of human and animal disease. Model building is only the first part of the process. These models then need to be confronted with data to obtain parameter estimates and the accuracy of these estimates has to be evaluated. Estimation of parasite densities is central to this. Parasite density estimates can include the proportion of hosts infected with parasites (prevalence) or estimates of the parasite biomass within the host population (abundance or intensity estimates). Parasite density estimation is often complicated by highly aggregated distributions of parasites within the hosts. This causes additional challenges when calculating transmission parameters. Using Echinococcus spp. as a model organism, this manuscript gives a brief overview of the types of descriptors of parasite densities, how to estimate them and on the use of these estimates in a transmission model.

Mathematical modelling of parasite transmission systems can provide useful information about host parasite interactions and biology and parasite population dynamics. In addition good predictive models may assist in designing control programmes to reduce the burden of human and animal disease. Model building is only the first part of the process. These models then need to be confronted with data to obtain parameter estimates and the accuracy of these estimates has to be evaluated. Estimation of parasite densities is central to this. Parasite density estimates can include the proportion of hosts infected with parasites (prevalence) or estimates of the parasite biomass within the host population (abundance or intensity estimates). Parasite density estimation is often complicated by highly aggregated distributions of parasites within the hosts. This causes additional challenges when calculating transmission parameters. Using Echinococcus spp. as a model organism, this manuscript gives a brief overview of the types of descriptors of parasite densities, how to estimate them and on the use of these estimates in a transmission model.

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2 citations in Web of Science®
3 citations in Scopus®
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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
Uncontrolled Keywords:Evaluating parasite densities and estimation, mathematical modelling, two part conditional model, Echinococcus, negative binomial distribution, aggregation
Language:English
Date:2008
Deposited On:22 Dec 2008 13:31
Last Modified:05 Apr 2016 12:34
Publisher:Princeps Editions
ISSN:1252-607X
Free access at:Official URL. An embargo period may apply.
Publisher DOI:10.1051/parasite/2008153477
Official URL:http://www.parasite-journal.org/dwld/Parasite08-3_477-483_Heinzmann.pdf
Related URLs:http://www.parasite-journal.org/P6-S08.html (Publisher)
PubMed ID:18814726
Permanent URL: http://doi.org/10.5167/uzh-5444

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