Matrix Approaches to Health Demography
Start: 13 March 2017
End: 24 March 2017
Location: Max Planck Institute for Demographic Research (MPIDR), Rostock, Germany
This course will introduce matrix methods for the analysis of health demography. Health demography is particularly concerned with measures of longevity and healthy longevity, with the dynamics of individual transitions among health and disease states, with the projection of the future health composition of populations, and analyses accounting for causes of death. Matrix methods describe the dynamics of individuals, cohorts, and populations, in a powerful generalization of classical life table methods. We will use them to extend the usual analyses in two directions. First, we will incorporate variance and stochasticity into the analyses, going beyond the usual obsession with mean results. Second, we will use sensitivity analyses to quantify the effects of parameters on the results.
The class will introduce methods based on Markov chains, Markov chains with rewards, multistate matrix models, and matrix calculus. These methods will be compared to traditional approaches, and applied to data on prevalence of health conditions, incidence of disease and disability, population projections, and causes of death.
Although the applications will focus on human populations, all of these topics have direct (or, at least potential) applications in animal and plant demography. Biodemographers and population biologists interested in new perspectives in demographic analysis are encouraged to apply.
The course will be a mixture of lectures, discussions, and computer exercises.
Basic demography (human, plant, or animal), including life tables, mortality and fertility schedules, and their applications. Familiarity with the basic operations of matrix algebra (matrices, vectors, multiplication, inverses, eigenvalues and eigenvectors). Fluency in Matlab or R.
Students will be evaluated on the basis of computer exercises and class participation.
Specific readings will be provided before the beginning of the course. The following are some useful sources.
A comprehensive treatment of the "classical" methods and applications health demography:
Siegel, J.S. 2012. The Demography and Epidemiology of Human Health and Aging. Springer-Verlag
The basic source for matrix population models is:
Caswell, H. 2001. Matrix Population Models. 2nd edition. Sinauer Associates, Sunderland, MA.
Some of the matrix material is also covered in:
Keyfitz, N. and H. Caswell. 2005. Applied Mathematical Demography. 3rd edition. Springer-Verlag.
Some of the methods we will explore are presented in the following papers.
van Daalen, S. and H. Caswell. 2015. Lifetime reproduction and the second demographic transition: stochasticity and individual variation. Demographic Research 33:561-588.
Caswell, H. 2012. Matrix models and sensitivity analysis of populations classified by age and stage: a vec-permutation matrix approach. Theoretical Ecology 5:403-417. DOI 10.1007/s12080-011-0132-2 (published online 2011)
Caswell, H. 2009. Stage, age, and individual stochasticity in demography. The Per Brinck Oikos Award Lecture 2008. Oikos 118:1763-1782.
There is no tuition fee for this course. Students are expected to pay their own transportation and living costs. However, a limited number of scholarships are available on a competitive basis for outstanding candidates and for those applicants who might otherwise not be able to come.
Recruitment of students
Applicants should either be enrolled in a PhD program (those well on their way to completion will be favored) or have received their PhD.
A maximum of 15 students will be admitted.
The selection will be made by the MPIDR based on the applicants’ scientific qualifications.
How to apply
Applications should be sent by email to the MPIDR (address below). Please begin your email message with a statement saying that you apply for course IDEM 134 – Matrix Approaches to Health Demography. You also need to attach the following items integrated in *a single pdf file*: (1) A two-page curriculum vitae, including a list of your scholarly publications. (2) A one-page letter from your supervisor at your home institution supporting your application. (3) A two-page statement of your research and how it relates to the course. Please include a short description of your knowledge of life tables and matrix algebra and of your fluency in Matlab or R. At the very end of your research statement, in a separate paragraph, please indicate (a) whether you would like to be considered for financial support and (b) if you would be able to come without financial aid from our side.
Send your email to Heiner Maier (email@example.com).
Application deadline is 29 January 2017.
Applicants will be informed of their acceptance by 10 February 2017.
Applications submitted after the deadline will be considered only if space is available.