MULTI AGENT SIMULATION TECHNIQUES FOR DYNAMIC SIMULATION OF SOCIAL INTERACTION AND SPREAD OF DISEASES WITH DIFFERENT SEROTYPES
Author(s)
Endel G1, Schiller - Frühwirth I1, Popper N2, Miksch F2, Zauner G2, Breitenecker F31Hauptverband der Österreichischen Sozialversicherungsträger, Vienna, Vienna, Austria, 2DWH - Simulation Services, Vienna, Vienna, Austria, 3Vienna University of Technology, Vienna, Vienna, Austria
OBJECTIVES: For modeling vaccination strategies and spreading of infectious diseases by airborne infection or contact transmission detailed individual based simulation is needed. A new technique modeling heterogeneous populations with age specific behavior and population dynamics during simulation is presented. METHODS: A multi agent based model is implemented. Requirements: Simulate long periods for long term effects; consider changing population structure; implement a social model to simulate individual contacts; and simulate various pathogens to differentiate between vaccine-covered and non-covered serotypesThe model consists of three parts. Population part. Individual attributes for agents: Age, Gender, Infection State, Pregnancy (women only) and a unique ID-Number, Age Class and Infection Protocol are stored. Aging, Death and Birth of Agents is implemented. Parameters can be identified with real population data of Austria provided by “Statistik Austria”. Social part. Epidemics can be spread only through direct contact between two agents. Contacts can happen at home, at work, and randomly. Additional rules (f.e. age distribution of people in contact depending on the age of the persons) are defined. Epidemics part. The procedure of the epidemics part is depicting the contact based infections, carrying time and end of illness, including, time and age specific carrying time of special bacterial strains. Extra features for simulation of two or more pathogens in parallel are developed. RESULTS: The concept has been validated using detailed data for serious pneumococcal indicated diseases for Austria. Stability analysis and dependency on starting parameters was examined . Results show stable realistic behavior for single serotype and competing serotypes. CONCLUSIONS: Using this dynamic modeling concept simulation of non linear effects like herd immunity and serotype replacement is possible for testing vaccination strategies. One of the main benefits is that for parameterization and identification no abstract values are used, so objectivity and traceability are assured.
Conference/Value in Health Info
2009-10, ISPOR Europe 2009, Paris, France
Value in Health, Vol. 12, No. 7 (October 2009)
Code
PMC32
Topic
Methodological & Statistical Research
Topic Subcategory
Modeling and simulation
Disease
Multiple Diseases