Modelling parasite aggregation: disentangling statistical and ecological approaches
Modelling parasite aggregation: disentangling statistical and ecological approaches
The overdispersion in macroparasite infection intensity among host populations is commonly simulated using a constant negative binomial aggregation parameter. We describe an alternative to utilising the negative binomial approach and demonstrate important disparities in intervention efficacy projections that can come about from opting for pattern-fitting models that are not process-explicit. We present model output in the context of the epidemiology and control of soil-transmitted helminths due to the significant public health burden imposed by these parasites, but our methods are applicable to other infections with demonstrable aggregation in parasite numbers among hosts.
Yakob, L.
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Soares Magalhaes, R.J.
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Gray, D.J.
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Milinovich, G.
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Wardrop, N.A.
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Dunning, R.
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Barendregt, J.
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Bieri, F.
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Williams, G.M.
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Clements, A.C.A.
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2014
Yakob, L.
d129e129-59bc-4607-85e3-20d965097ffa
Soares Magalhaes, R.J.
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Gray, D.J.
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Milinovich, G.
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Wardrop, N.A.
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Dunning, R.
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Barendregt, J.
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Bieri, F.
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Williams, G.M.
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Clements, A.C.A.
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Yakob, L., Soares Magalhaes, R.J., Gray, D.J., Milinovich, G., Wardrop, N.A., Dunning, R., Barendregt, J., Bieri, F., Williams, G.M. and Clements, A.C.A.
(2014)
Modelling parasite aggregation: disentangling statistical and ecological approaches.
International Journal for Parasitology.
(doi:10.1016/j.ijpara.2014.02.008).
Abstract
The overdispersion in macroparasite infection intensity among host populations is commonly simulated using a constant negative binomial aggregation parameter. We describe an alternative to utilising the negative binomial approach and demonstrate important disparities in intervention efficacy projections that can come about from opting for pattern-fitting models that are not process-explicit. We present model output in the context of the epidemiology and control of soil-transmitted helminths due to the significant public health burden imposed by these parasites, but our methods are applicable to other infections with demonstrable aggregation in parasite numbers among hosts.
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Published date: 2014
Organisations:
Population, Health & Wellbeing (PHeW)
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Local EPrints ID: 364582
URI: http://eprints.soton.ac.uk/id/eprint/364582
ISSN: 0020-7519
PURE UUID: 1ea1f912-93c6-4423-81ef-878ccc3e81a8
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Date deposited: 02 May 2014 10:14
Last modified: 14 Mar 2024 16:38
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Contributors
Author:
L. Yakob
Author:
R.J. Soares Magalhaes
Author:
D.J. Gray
Author:
G. Milinovich
Author:
R. Dunning
Author:
J. Barendregt
Author:
F. Bieri
Author:
G.M. Williams
Author:
A.C.A. Clements
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