Abstract
In times where urbanization becomes more important every day, epidemic outbreaks may be devastating. Powerful forecasting and analysis tools are of high importance for both, small and large scale examinations. Such tools provide valuable insight on different levels and help to establish and improve embankment mechanisms. Here, we present an agent-based algorithmic framework to simulate the spread of epidemic diseases on a national scope. Based on the population structure of Germany, we investigate parameters such as the impact of the number of agents, representing the population, on the quality of the simulation and evaluate them using real world data provided by the Robert Koch Institute [4, 22]. Furthermore, we empirically analyze the effects of certain non-pharmaceutical countermeasures as applied in the USA against the Influenza Pandemic in 1918–1919 [18]. Our simulation and evaluation tool partially relies on the probabilistic movement model presented in [8]. Our empirical tests show that the amount of agents in use may be crucial. Depending on the existing knowledge about the considered epidemic, this parameter alone may have a huge impact on the accuracy of the achieved simulation results. However, with the right choice of parameters—some of them being obtained from real world observations [10]—one can efficiently approximate the course of a disease in real world.
Partially supported by the Austrian Science Fund (FWF) under contract P25214 and by DFG project SCHE 1592/2-1. A preliminary version of this paper was published in the Proceeding of SIMULTECH 2013 [9].
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Notes
- 1.
In [10] the degree represents the number of individuals visiting these places over a time period of 24 h.
- 2.
The amount of overall agents in use (\( n \)) determines how many cities are represented by \( V \). Therefore we sort the list of all cities of Germany in descending order of their population size. Then, starting from the top, we include the currently considered city \( c_{i} \) to \( V \) if and only if the assigned amount of agents to said city is at least \( 1 \). The latter amount is given by \( n\, \cdot \,d_{{c_{i} }} \).
- 3.
The Robert Koch Institute (RKI) is the central federal institution in Germany responsible for disease control and prevention and is therefore the central federal reference institution for both, applied and response-orientated research. (Source http://www.rki.de/EN/Home/homepage_node.html).
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Elsässer, R., Ogierman, A., Meier, M. (2015). Epidemics and Their Implications in Urban Environments: A Case Study on a National Scope. In: Obaidat, M., Koziel, S., Kacprzyk, J., Leifsson, L., Ören, T. (eds) Simulation and Modeling Methodologies, Technologies and Applications. Advances in Intelligent Systems and Computing, vol 319. Springer, Cham. https://doi.org/10.1007/978-3-319-11457-6_4
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