A Cellular Automata Modeling for Visualizing and Predicting Spreading Patterns of Dengue Fever

Puspa Eosina Hosen, Taufik Djatna, Helda Khusun

Abstract


A Cellular Automata (CA) model is used for visualizing and predicting spreading pattern of the disease. The main problem of this model is how to find a function that represents an update rule that changes the state of a cell in time steps affected by neighborhood. This research aims to develop visualization and prediction model of the spreading patterns of Dengue Hemorrhagic Fever. The contribution of our study is to introduce a new approach in defining a probabilistic function that represents CA transmission rule by employing Von Neumann neighborhood and the Hidden Markov Model (HMM). This study only considered an infective state which dedicated particular attention to the spatial distribution of infected areas. The infected data were devided into four categories and change the definition of a cell as an area. The evaluation was conducted by comparing the results of the proposed model to that of one yielded by a Susceptible-Infected-Recovered (SIR) model. The evaluation result showed that the CA model was capable of generating patterns that similar to the patterns generated by SIR models with a similarities value of 0.95.


Keywords


Cellular Automata, Dengue Fever, HMM, Neighborhood, SIR

Full Text:

PDF

References


Cuesta H. Practical Data Analysis. Packt Publishing Ltd, Birmingham-Mumbai.2013: 153-173.

Pfeiffer D. Spatial Analysis in Epidemiology. Oxford University Press. 2008.

White SH, Rey AMD, Sänchez GR. Modeling Epidemic Using Cellular Automata. Applied Mathematics and Computations. 2007; 186:193-202.

Nishiura H. Mathematical and Statistical Analyses of the Spread of Dengue. Dengue Bulletin. 2006; 30: 51-57.

Santos LBL, Maretto RV, Medeiros LCC, Feitosa FF, Monteiro AMV. A Susceptible-Infected Model for Exploring the Effects of Neighborhood Structures on Epidemic Processes- A Segrwgation Analysis. Proceedings XII Geoinfo. Campus do Jordio Brasil. 2011, 12. 85-96.

White SH. Using Cellular Automata to Simulate Epidemic Diseases. Applied Mathematical Sciences. 2009; 3(20): 959-968.

López L, Burguener G, Giovanini L, Baldomenico P. A Cellular Automata to Model Epidemics. Proceedings of the JAIIO – Congreso Argentino de Informatica y Salud (CAIS). 2013; 42: 150-161.

Athithan S, Shukla VP, Biradar SR. Dynamic Cellular Automata Based Epidemic Spread Model for Population in Patches with Movement. Journal of Computational Environmental Sciences. 2014. Article ID 518053. Hindawi Publishing Corporation. http://dx.doi.org/10.1155/2014/518053.

Santos LBL, Costa MC, Pinho STR, Andrade RFS, Barreto FR, Teixeira MG, Barreto ML. Periodic Forcing in a three-level Cellular Automata Model for a Vector-transmitted Disease. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics (Print). 2009; 80: 016102.

Elsayed WM, .El-Bassiouny AH,. Radwan EF. Applying Inhomogeneous Probabilistic Cellular Automata Rules on Epidemic Model. International Journal of Advanced Research in Artificial Intelligence. 2013; 2(4).

Hagoort M, Geertman S, Ottens H. Spatial Externalities, Neighborhood Rules and CA Land-use Modeling. In: The Ammals of Regional Science. 2008; 42(1).

Jyh-Ying P, John ADA, Cheng-Yuan L. Modeling Time Series and Sequences Using Markov Chain Embedded Finite Automata. International Journal of Innovative Computing, Information, and Control. 2011; 7(1): 407-431.

German B, Leonardo L, Leonardo G. Modelling Population Heterogeneity in Epidemics using Cellular Automata. Proceeding of Association Argentina de Mecanica Computacional. Rosario. 2011; 30: 3501-3514.

Mitchell M. Evolving Cellular Automata with Genetic Algorithms: A Review of Recent Work. Proceedings of the First International Conference on Evolutionary Computation and Its applications. Moscow, Russia. 1996.

Dugat R. A Tutorial on Hidden Markov Models. Indian Institute of Technology. Report number: SPANN-96.1. 1996.

Saragi D. Trend Analisis dengan Metode Time Series untuk Meramalkan Penderita Demam Berdarah Tahun 2010-2014 Berdasarkan Data Penderita Demam Berdarah Tahun 2005-2009 di Propinsi Sumatra Utara. Master Thesis. Medan: Fakultas Kesehatan USU. 2011.

Octora M. Perbandingan Metode ARIMA (Box Jenkins) dan Metode Winter dalam Peramalan Jumlah Kasus DBD. Master Thesis. Surabaya: Fakultas Kesehatan Masyarakat, Unair. 2010.

Wang Z. Public Evacuation Process Modeling and Simulation based on Cellular Automata. TELKOMNIKA. 2013; 11(11):. 6468~6476.

Djatna T, Morimoto Y. Attribute Selection for Numerical Databases that Contain Correlations. Int. J. Software and Informatics. 2008: 2(2): 125-139.

Knutson JD. A Survey of the Use of Cellular Automata and Cellular Automata-Like Models for Simulating a Population of Biological Cells. Master Thesis. Iowa: Iowa State University. 2011.

Terry L. Ergodic Hidden Markov Models for Visual-Only Isolated Digit Recognition. PhD Dissertation. Evanston Illinois. 2007.

Emillia NR, Suyanto, Maharani W. Isolated Word Recognition Using Ergodic Hidden Markov Model and Genetic Algorithm. TELKOMNIKA. 2012; 10(1):. 129-136.

Gentle JE. Random Number Generation and Monte Carlo Methods. In: Chambers J, Eddy W, Härdle W, Sheather S, Tierney L. Editors. Statistic and Computing. New York: Springer Science + Business Media, Inc. 2003.

Sargent RG. Verification and Validation of Simulation Models. Proceedings of the 2007 Winter Simulation Conference. IEEE. 2007: 124-137.

Bootsma MCJ, Ferguson NM. The effect of Public Health Measures on the 1918 Influenza Pandemic in US cities. Proceedings of the. National Academy of Science. US: The National Academy of Sciences. 2007; 104(18): 7588-7593.10.1073/pnas.0611071104..

Sung-Hyuk C. Comprehensive Survey on Distance/Similarity Measures between Probability Density Functions. International Journal of Mathematical Models and Methods in Applied Sciences. 2007; 1(4): 300-307.

Bajracharya K, Duboz R. Comparison of Three Agent Based Platforms on the Basis of a Simple Epidemiological Model (WIP). Proceedings of The Symposium on Theory of Modeling & Simulation. 2013.




DOI: http://doi.org/10.12928/telkomnika.v14i1.2404

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

TELKOMNIKA Telecommunication, Computing, Electronics and Control
ISSN: 1693-6930, e-ISSN: 2302-9293
Universitas Ahmad Dahlan, 4th Campus
Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, Yogyakarta, Indonesia 55191
Phone: +62 (274) 563515, 511830, 379418, 371120
Fax: +62 274 564604

View TELKOMNIKA Stats