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Project

The stride towards health economic evaluation with individual-based models integrating transmission dynamics, stochasticity and uncertainty.

Background – Infectious diseases have substantial impact on society and model-based health economic evaluation has acquired prominence for policy making. Stochastic individual-based models, in which each individual is modelled separately, are highly relevant to capture heterogeneities in social contacts patterns and transmission dynamics. Although they are suitable to predict disease burden and medical costs in detail, they are not fully exploited yet due to model complexity and computational burden. Aim – To improve health economic evaluations with stochastic individual-based disease transmission models while accounting for uncertainty. Methods – To advance from a C++ simulator towards a new platform for health economic evaluation, "rStride" in the widely used R software. This open-source package will integrate high-performant transmission modelling and state-of-the-art uncertainty analysis. Expected results – (1) New and improved individual-based modelling methods on demography and transmission dynamics. (2) Insights on the effect of social mixing assumptions on the estimated burden of disease. (3) The integration of stochastic effects from individual-based transmission models within uncertainty analysis in economic evaluations. (4) Long-term model predictions, including household dynamics, to explore between- and within-host dynamics. All methods will be applied to case studies on Respiratory Syncytial Virus (RSV) and Varicella-Zoster Virus (VZV).
Date:1 Oct 2019 →  30 Sep 2022
Keywords:HEALTH ECONOMICS, INFECTIOUS DISEASES, COST EFFECTIVENESS
Disciplines:Statistics, Health economy, Preventive medicine, Infectious diseases, Mathematical methods, programming models, mathematical and simulation modelling