General Departmental Seminar Series
Grade of Membership Models Applications to the Demography of Aging
and the Epidemiology of Tropical Diseases
Dr. Burton Singer, Woodrow Wilson School of Public and International Affairs, Princeton University
Friday, April 7, 2000, 12:00-1:00 pm
3285 Medical Sciences Center
1300 University Avenue
When individuals or communities are represented by a multiplicity of conditions, no combination of which occurs at high frequency in an overall population, just describing how they are distributed presents a considerable analytic challenge. The family of Grade-of-Membership (GoM) models provide a useful and interpretable response to this challenge. We will describe the theoretical principles underlying GoM models and illustrate their use in two quite different settings(1) Characterizing the health status of elderly communities, where many people have multiple chronic conditons and disabilities, no combination of which occurs at high frequency, and (2) quantifying the risk of Chagas' Disease transmission in northwestern Argentina, where multiple facets of house and peridomiciliary-structure disrepair coupled to proximity of persons to a diverse set of animal reservoirs of the parasite T. Cruzi, can all contribute -- in principle -- to risk profiles for individuals. Public health and policy implications of both examples will also be discussed.
Dr. Singer's research interests include the epidemiology of tropical diseases; demography and economics of aging; health and social consequences of economic development; and the interrelationships between genetics and historical demography. Formerly chair of the Department of Epidemiology and Public Health and professor of economics and statistics at Yale University, he has served as chair of the National Research Council Committee on National Statistics and as chair of the Steering Committee for Social and Economic Research in the World Health Organization. He was elected to the National Academy of Sciences and was a Guggenheim fellow in 1981-1982.
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