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A Within-Host Stochastic Model for Nematode Infection

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Gómez-Corral, Antonio and López-García, M. (2018) A Within-Host Stochastic Model for Nematode Infection. Mathematics, 6 (9). p. 143. ISSN 2227-7390

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Official URL: https://doi.org/10.3390/math6090143




Abstract

We propose a stochastic model for the development of gastrointestinal nematode infection in growing lambs under the assumption that nonhomogeneous Poisson processes govern the acquisition of parasites, the parasite-induced host mortality, the natural (no parasite-induced) host mortality and the death of parasites within the host. By means of considering a number of age-dependent birth and death processes with killing, we analyse the impact of grazing strategies that are defined in terms of an intervention instant t0, which might imply a move of the host to safe pasture and/or anthelmintic treatment. The efficacy and cost of each grazing strategy are defined in terms of the transient probabilities of the underlying stochastic processes, which are computed by means of Strang–Marchuk splitting techniques. Our model, calibrated with empirical data from Uriarte et al. and Nasreen et al., regarding the seasonal presence of nematodes on pasture in temperate zones and anthelmintic efficacy, supports the use of dose-and-move strategies in temperate zones during summer and provides stochastic criteria for selecting the exact optimum time instant t (sub index 0) when these strategies should be applied.


Item Type:Article
Additional Information:

This article belongs to the Special Issue Stochastic Processes with Applications

Uncontrolled Keywords:Host-parasite interaction; Nematode infection; Nonhomogeneous Poisson process; seasonal environment; Strang–Marchuk splitting approach.
Subjects:Sciences > Mathematics
Sciences > Mathematics > Applied statistics
Sciences > Mathematics > Stochastic processes
Medical sciences > Medicine > Parasitology
Medical sciences > Biology > Biomathematics
ID Code:63191
Deposited On:30 Nov 2020 15:21
Last Modified:30 Nov 2020 17:44

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