Monday, October 24, 2011: 5:45 PM
Grand Ballroom CD (Hyatt Regency Chicago)
(ESP) Applied Health Economics, Services, and Policy Research

Candidate for the Lee B. Lusted Student Prize Competition

Christoph Urach1, Günther Zauner2, Niki Popper2, Gottfried Endel3, Irmgard Schiller-Frühwirth3 and Felix Breitenecker1, (1)Vienna University of Technology, Vienna, Austria, (2)Dwh Simulation Services, Vienna, Austria, (3)Main Association of Austrian Social Security Institutions, Vienna, Austria

Purpose: Calculating cases of illnesses caused by droplet infections and evaluating the influence of interventions requires dynamic simulation models. The aim of the work is to develop a module to simulate social interaction in epidemic disease propagation and show that models using such complex structures can provide different and more accurate results than calculations neglecting social networks.

Method: Data from EU-project POLYMOD (SP22-CT-2004-502084) about contacts between people and their location is thoroughly analyzed. We use agent-based modeling to create the social interaction sub model due to the very inhomogeneous contact structure as well as the necessity to create a flexible, extensible module. Data from Statistik Austria and structural knowledge about places is used to create different work places, schools, households and places for leisure activities. Each place type has its own structure. For example the place type school defines a structure which consist of several classes with pupils and teachers which change classes according to their movement rules. The social interaction model uses many realizations of the place type school with different parameters for school and class sizes as well as the age structure of the pupils according to data from Statistik Austria. The spread of the disease happens through contacts between infected and susceptible people who are at the same place at the same time.

Result: Social networks are established through places where people meet regularly. The model does not only allow simulating the quickness of the spread of diseases but also locate places where many potential infectious contacts occur. It also helps identifying key people who are responsible for many infections as well as simulating the outcome of interventions. Actual this social module is used in a model for influenza. At some places and especially in schools many infections occur. Simulating scenarios where teachers are vaccinated or schools are closed show that the pace of the epidemic can be slowed down.

Conclusion: Spread of diseases through contacts between individuals can be more properly assessed when simulating contact places. Especially the evaluation and simulation of interventions which target only certain population groups or locations and therefore affect some people more than others benefit from social interaction models. Due to the modular design the contact model can be adapted and used for other droplet infections.