Past Research

Modelling Temporal Scales and Patterns of Population Variability

Summary

The research focused on developing a stage-structured population dynamic models for studying the dynamic fish species. The model was applied to study the population dynamics of mature and immature Barents Sea capelin. The optimal parameters of the model were estimated numerically using an optimisation algorithm involving spline interpolation and minimisation of error function subject to parameters constraints. The Runke Kutta numerical method for solving systems of ordinary differential equations and spline interpolation were used to solve the system and for estimating model predictions.

Bayesian Analysis of Hemagglutination-Inhibition Data

Summary

Data obtained from hemagglutination-inhibition (HI) assay plays an instrumental role in influenza survellance. The HI data is influenced by two main parameters: antigenic and non-antigenic parameters. A key problem of this data is the presence of non-antigenic parameters which hinder a correct interpretation of the data. This research shows how antigenic and non-antigenic parameters can be systematically decoupled using a previously published model and the bayesian statistical inference.