Objectives: In this work, a cellular automaton software package for simulating different infectious diseases, storing the simulation results in a data warehouse system and analyzing the obtained results to generate prediction models as well as contingency plans, is proposed. The Brisbane H3N2 flu virus, which has been spreading during the winter season 2009, was used for simulation in the federal state of Tyrol, Austria.
Methods: The simulation-modeling framework consists of an underlying cellular automaton. The cellular automaton model is parameterized by known disease parameters and geographical as well as demographical conditions are included for simulating the spreading. The data generated by simulation are stored in the back room of the data warehouse using the Talend Open Studio software package, and subsequent statistical and data mining tasks are performed using the tool, termed Knowledge Discovery in Database Designer (KD3).
Results: The obtained simulation results were used for generating prediction models for all nine federal states of Austria.
Conclusion: The proposed framework provides a powerful and easy to handle interface for parameterizing and simulating different infectious diseases in order to generate prediction models and improve contingency plans for future events.
5
Triampo W,
Baowan D,
Tang IM,
Nuttavut N,
Wong-Ekkabut J,
Doungchawee G.
A Simple Deterministic Model for the Spread of Leptospirosis in Thailand. International Journal of Biological and Life Sciences 2006; 2: 22-26.
6
Tiensin T,
Nielen M,
Vernooij H,
Songserm T,
Kalpravidh W,
Chotiprasatintara S,
Chaisingh A,
Wongkasemjit S,
Chanachai K,
Thanapongtham W,
Srisuvan T,
Stegeman A.
Transmission of the highly pathogenic avian influenza virus H5N1 within flocks during the 2004 epidemic in Thailand. J Infect Dis 2007; 196 (11) 1679-1684. Epub Oct 25, 2007.
7
Codeço Coelho F,
Codeco C,
Cruz O.
Epigrass: a tool to study disease spread in complex networks. Source Code for Biology and Medicine 2008; 3: 3. doi: 10.1186/1751-0473-3-3.
8
Mossong J,
Hens N,
Jit M,
Beutels P,
Auranen K,
Mikolajczyk R,
Massari M,
Salmaso S,
Tomba GS,
Wallinga J,
Heijne J,
Sadkowska-Todys M,
Rosinska M,
Edmunds WJ.
Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases. PLoS Med 2008; 5 (03) e74.
12
Fayyad UM,
Piatetsky-Shapiro G,
Smyth P.
From data mining to knowledge discovery: An overview. Advances in Knowledge Discovery and Data Mining 1996 pp. 1-34.
13
Pfeifer B,
Tejada MM,
Kugler K,
Osl M,
Netzer M,
Seger M,
Modre-Osprian R,
Schreier G,
Tilg B.
A Biomedical Knowledge Discovery in Databases Design Tool – Turning Data into Information. eHealth. 2008 Wien: May 29-30, 2008. CD-ROM.
22
Pfeifer B,
Kugler K,
Tejada MM,
Baumgartner C,
Seger M,
Osl M,
Netzer M,
Handler M,
Dander A,
Wurz M,
Graber A,
Tilg B.
A cellular automaton framework for infectious disease spread simulation. Open Med Inform J 2008; 2: 70-81.
23
Plaisier AP,
Subramanian S,
Das PK,
Souza W,
Lapa T,
Furtado AF,
Van der Ploeg CP,
Habbema JD,
van Oortmarssen GJ.
The LYMFASIM simulation program for modeling lymphatic filariasis and its control. Methods Inf Med 1998; 37 (01) 97-108.
25
Rubel F,
Fuchs K.
A decision-support system for real-time risk assessment of airborne spread of the foot-and-mouth disease virus. Methods Inf Med 2005; 44 (04) 590-595.