Evaluating parasite densities and estimation of parameters in transmission systems

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.

Keywords

• mathematical modelling
• two part conditional model
• Echinococcus
• negative binomial distribution
• aggregation