Heinzmann D, Torgerson P R
Institute of Parasitology, University of Zurich, Winterthurestrasse 266a, 8057 Zurich, and Institute of Mathematics, University of Zurich, Winterthurerstrasse 190, 8057 Zürich.
Parasite. 2008 Sep;15(3):477-83. doi: 10.1051/parasite/2008153477.
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.
寄生虫传播系统的数学建模可以提供有关宿主-寄生虫相互作用、生物学特性以及寄生虫种群动态的有用信息。此外，良好的预测模型可能有助于设计控制方案，以减轻人类和动物疾病的负担。模型构建只是这个过程的第一部分。这些模型随后需要与数据进行比对，以获得参数估计值，并且必须评估这些估计值的准确性。寄生虫密度的估计是这一过程的核心。寄生虫密度估计可以包括感染寄生虫的宿主比例（患病率），或者宿主种群中寄生虫生物量的估计值（丰度或强度估计值）。寄生虫密度估计常常因寄生虫在宿主体内的高度聚集分布而变得复杂。这在计算传播参数时会带来额外的挑战。本文以棘球绦虫属作为模式生物，简要概述了寄生虫密度描述符的类型、如何估计它们以及这些估计值在传播模型中的应用。
