Research Article
Dynamic versus static models in cost-effectiveness analyses of anti-viral drug therapy to mitigate an influenza pandemic
Article first published online: 20 APR 2009
DOI: 10.1002/hec.1485
Copyright © 2009 John Wiley & Sons, Ltd.
Additional Information
How to Cite
Lugnér, A. K., Mylius, S. D. and Wallinga, J. (2010), Dynamic versus static models in cost-effectiveness analyses of anti-viral drug therapy to mitigate an influenza pandemic. Health Economics, 19: 518–531. doi: 10.1002/hec.1485
Publication History
- Issue published online: 8 APR 2010
- Article first published online: 20 APR 2009
- Manuscript Accepted: 20 FEB 2009
- Manuscript Revised: 29 JAN 2009
- Manuscript Received: 5 SEP 2007
- Abstract
- References
- Cited By
Keywords:
- infectious disease;
- transmission;
- modeling choice
Abstract
Conventional (static) models used in health economics implicitly assume that the probability of disease exposure is constant over time and unaffected by interventions. For transmissible infectious diseases this is not realistic and another class of models is required, so-called dynamic models. This study aims to examine the differences between one dynamic and one static model, estimating the effects of therapeutic treatment with antiviral (AV) drugs during an influenza pandemic in the Netherlands. Specifically, we focus on the sensitivity of the cost-effectiveness ratios to model choice, to the assumed drug coverage, and to the value of several epidemiological factors. Therapeutic use of AV-drugs is cost-effective compared with non-intervention, irrespective of which model approach is chosen. The findings further show that: (1) the cost-effectiveness ratio according to the static model is insensitive to the size of a pandemic, whereas the ratio according to the dynamic model increases with the size of a pandemic; (2) according to the dynamic model, the cost per infection and the life-years gained per treatment are not constant but depend on the proportion of cases that are treated; and (3) the age-specific clinical attack rates affect the sensitivity of cost-effectiveness ratio to model choice. Copyright © 2009 John Wiley & Sons, Ltd.

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