Refining Estimates of Major Depression Incidence and Episode Duration in Canada Using a Monte Carlo Markov Model

Scott B. Patten and Robert C. Lee
Additional contact information
Scott B. Patten: Departments of Community Health Sciences and Psychiatry, University of Calgary, Alberta, Canada.
Robert C. Lee: Department of Community Health Sciences, University of Calgary, Alberta, Canada.

Medical Decision Making, 2004, vol. 24, issue 4, 351-358

Abstract: Background . Serial period prevalence estimates for recurrent diseases such as major depression are available more frequently than fully detailed longitudinal data, but it is difficult to estimate incidence and episode duration from such data. Incidence and episode duration are critical decision modeling parameters for recurrent diseases . Objectives . To reduce bias that would otherwise occur in national incidence and duration-of-episode estimates for major depressive episodes deriving from studies using serial period prevalence data and to illustrate amethodological approach for the estimation of incidence from such studies . Methods . Monte Carlo simulation was applied to a Markov process describing incidence and recovery from major depressive episodes . Results . The annual incidence and episode duration were found to be 3.1% and 17.1 weeks, respectively. These estimates are expected to be less subject to bias than those generated without modeling . Conclusions . These results highlight the usefulness of Markov models for analysis of longitudinal data. The methods described here may be useful for decision modeling andmay be generalizable to other chronic diseases .

Keywords: depressive disorder; epidemiology; Markov chains; incidence; prevalence; decision modeling (search for similar items in EconPapers)
Date: 2004
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0272989X04267008 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:24:y:2004:i:4:p:351-358

DOI: 10.1177/0272989X04267008

Access Statistics for this article

More articles in Medical Decision Making
Bibliographic data for series maintained by SAGE Publications ().