A simulation facility for stochastic micropopulation models at the University of Minnesota utilizes a VAZ 11/750 and VMS to run a locally-developed software system called SUMMERS (Simulation Utilities and Monte Carlo Methods for Epidemiological Research Studies). Since SUMMERS is highly modularized, it can be adapted to the simulation of different populations and models of different diseases by changing a limited number of program modules and variable subsets. Various program modules operate the user interfaces, the simulation process, the control functions, the report generation, and the analytic interpretation. Extensive software is being developed for sensitivity analyses of the multivariate parameters which are estimated stochastically. Hardware and software are assembled and integrated to enable convenient, research-oriented studies of stochastic population models. Current model development and research focuses on models of infectious disease epidemics, chronic cardiovascular disease, genetic ascertainment of diabetes, and data distributions from the clinical laboratory. The results of these simulations are of use in analyzing mechanisms of disease incidence, prevalence and case-finding, as well as in exploring strategies for prevention or limitation of spread. These studies and the outcomes of collaborative studies help test the applicability and friendliness of the facility offerings. It will also train new users, disseminate materials concerning the research and facilities available, and provide modeling services for remote users. During the first three years of renewal, different transfer modes will be developed for external users, ranging from multi-user, multi-function programming systems running on super micro- or mini-computers, to single user, single function systems dedicated to a particular version or model type, and to smaller microcomputer versions suitable for demonstration in the classroom or at seminars. Network facilities will also be investigated to link the community of SUMMERS users to other BRT simulation facilities and to each other.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR001632-08
Application #
3103934
Study Section
Special Emphasis Panel (SSS (B))
Project Start
1983-09-01
Project End
1991-08-31
Budget Start
1990-09-01
Budget End
1991-08-31
Support Year
8
Fiscal Year
1990
Total Cost
Indirect Cost
Name
University of Minnesota Twin Cities
Department
Type
Schools of Medicine
DUNS #
168559177
City
Minneapolis
State
MN
Country
United States
Zip Code
55455
Altmann, M (1998) The deterministic limit of infectious disease models with dynamic partners. Math Biosci 150:153-75
Sellers, T A; Weaver, T W; Phillips, B et al. (1998) Environmental factors can confound identification of a major gene effect: results from a segregation analysis of a simulated population of lung cancer families. Genet Epidemiol 15:251-62
Blumenthal, M N; Wang, Z; Weber, J L et al. (1996) Absence of linkage between 5q markers and serum IgE levels in four large atopic families. Clin Exp Allergy 26:892-6
Boult, C; Altmann, M; Gilbertson, D et al. (1996) Decreasing disability in the 21st century: the future effects of controlling six fatal and nonfatal conditions. Am J Public Health 86:1388-93
Altmann, M (1995) Susceptible-infected-removed epidemic models with dynamic partnerships. J Math Biol 33:661-75
Ackerman, E (1995) Simulation of micropopulations in epidemiology: tutorial. 4. Evaluations of simulation models. A series of tutorials illustrated by coronary heart disease models. Int J Biomed Comput 39:219-29
Ackerman, E (1994) Simulation of micropopulations in epidemiology: tutorial 1. Simulation: an introduction. A series of tutorials illustrated by coronary heart disease models. Int J Biomed Comput 36:229-38
Altmann, M; Wee, B C; Willard, K et al. (1994) Network analytic methods for epidemiological risk assessment. Stat Med 13:53-60
Ackerman, E (1994) Simulation of micropopulations in epidemiology: tutorial. 3. Simulation model evaluation methods. A series of tutorials illustrated by coronary heart disease models. Int J Biomed Comput 37:195-204
Zhuo, Z; Tsai, Y J; Ackerman, E et al. (1994) Polychotomous multivariate models for coronary heart disease simulation. IV. The impact of physiological aging. Int J Biomed Comput 37:287-96

Showing the most recent 10 out of 55 publications