Adaptive Area-Based Risk Model for Dengue Fever: Algorithm of Dynamic Spreading in Network

Wahjoe T. Sesulihatien, Yasushi Kiyoki

研究成果: Conference contribution


Dengue fever is the fastest spreading communicable disease in the world. Spreading of virus is driven by increasing number of human moving. In many dengue-endemic countries, problem in dengue spreading is predicting infected area and determine perfect strategy to prevent the disease. Predicting infected area spot relates with pattern of human moving, while strategy to prevent is depend on vulnerability of area. In this paper we proposed an adaptive spreading model of area-disease based on human movement. This method combines an area-based mathematical model with discrete life-cycle of virus. The proposed method includes (1) state-space model of routine movement cycle, (2) algorithm of spreading, (3) prediction of the next infection area by graph relation, and (4) vulnerability value of suspected area. There are two important features in this method: real-time prediction of infected area and flexibility to adapt in the different situation. To perform the simulation we utilize real data of infected people in Surabaya in January 2011.The result shows that this method is suitable for near future prediction and easy to compensate time-varying changing. However, the accuracy needs to be improved.

ホスト出版物のタイトルInformation Modelling and Knowledge Bases XXVII
出版社IOS Press
出版ステータスPublished - 2016


名前Frontiers in Artificial Intelligence and Applications

ASJC Scopus subject areas

  • 人工知能


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