The objective of this study was to assess the impact of modeling type on the economic evaluation of screening programs for asymptomatic Chlamydia trachomatis infections.
We compared a stochastic network simulation model (dynamic model) with a decision analysis model (static model) for estimating the cost-effectiveness of an opportunistic screening program. The influence of the model type on the required data, the computed results, and the sensitivity of model parameters were investigated.
When compared with static modeling, dynamic modeling yielded different cost-effectiveness ratios and identified other optimal screening strategies as it considers changes in the force of infection caused by screening. However, it is more complex, data- and time-demanding, and more sensitive to some parameters affecting the force of infection than static modeling.
Dynamic models should be applied for the economic evaluation of prevention measures that have the potential to lower the force of infection such as large-scale chlamydial screening programs.
The advantages and disadvantages of dynamic and static modeling in economic evaluation of chlamydial screening programs are presented. We show that dynamic models are necessary to identify optimal screening strategies.
From the * Institute of Health Economics and Health Care Management, GSF-National Research Center for Environment and Health, Neuherberg, Germany; the † Centre for Prevention and Health Services Research, National Institute of Public Health and the Environment, Bilthoven, The Netherlands; ‡ Groningen University Institute for Drug Exploration/Groningen Research Institute for Pharmacy, University of Groningen, The Netherlands; and the § Department of Infectious Diseases Epidemiology, National Institute of Public Health and the Environment, Bilthoven, The Netherlands
Correspondence: Robert Welte, PhD, GSF-National Research Center for Environment and Health, Institute of Health Economics and Health Care Management, Ingolstädter Landstraßae 1, 85764 Neuherberg, Germany. E-mail: firstname.lastname@example.org, email@example.com. http://www.gsf.de/igm/en/index.html.
Received for publication September 2, 2004, and accepted January 20, 2005.