Abstract
This article provides a description of the population model PopMod, which is designed to simulate the health and mortality experience of an arbitrary population subjected to two interacting disease conditions as well as all other "background" causes of death and disability. Among population models with a longitudinal dimension, PopMod is unique in modelling two interacting disease conditions; among the life-table family of population models, PopMod is unique in not assuming statistical independence of the diseases of interest, as well as in modelling age and time independently. Like other multi-state models, however, PopMod takes account of "competing risk" among diseases and causes of death.PopMod represents a new level of complexity among both generic population models and the family of multi-state life tables. While one of its intended uses is to describe the time evolution of population health for standard demographic purposes (e.g. estimates of healthy life expectancy), another prominent aim is to provide a standard measure of effectiveness for intervention and cost-effectiveness analysis. PopMod, and a set of related standard approaches to disease modelling and cost-effectiveness analysis, will facilitate disease modelling and cost-effectiveness analysis in diverse settings and help make results more comparable.
Highlights
Historical background and analytical context Measuring population health has been inseparable from the modelling of population health for at least three hundred years
PopMod represents a new level of complexity among both generic population models and the family of multi-state life tables
The quadrature formula relies on the values of P(t) determined by the Runge-Kutta method at multiples of the chosen time step. Since these values involve numerical estimation error, there is no simple expression for the order of accuracy of the different output values reported in PopMod.[10]
Summary
Jeremy A Lauer*1, Klaus Röhrich, Harald Wirth, Claude Charette, Steve Gribble and Christopher JL Murray. Address: 1Global Programme on Evidence for Health Policy (GPE/EQC), World Health Organization, 1211 Geneva 27, SWITZERLAND, 2Creative Services, Technoparc Pays de Gex, 55 rue Auguste Piccard, 01630 St Genis Pouilly, FRANCE and 3Statistics Canada, R.H Coats Building, Holland Avenue, Ottawa, Ontario K1A 0T6, CANADA. Published: 26 February 2003 Cost Effectiveness and Resource Allocation 2003, 1:6.
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