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A decision support framework for a zoonosis prediction system: case study of Salmonellosis

Erna, Adhistya and Dominic P, Dhanapal Durai and Dayang R.A. Rambli, Rohaya (2011) A decision support framework for a zoonosis prediction system: case study of Salmonellosis. Int. J. Medical Engineering and Informatics, 3 (2). pp. 180-195.

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Abstract

Abstract: The rising number of zoonosis epidemics and the potential threat to humans highlight the need to apply a stringent system to prevent a zoonosis outbreak. Zoonosis is any infectious diseases that can be transmitted from animals to humans. This paper analyses and presents the development of a decision support system (DSS) that is able to support and provide prediction on the number of zoonosis human incidence. The DSS framework consists of three components: database management subsystem, model management subsystem, and user interface. A set of 168 monthly data from 1993–2006 was used to develop the database management subsystem. Data collection was collected from the number of human Salmonellosis occurrences in the USA published by Centers for Disease Control and Prevention (CDC). Six forecasting methods were applied in the model management subsystem. Finally, what-if (sensitivity) analysis was chosen to construct user interface subsystem. The result determined neural network as the most appropriate method. While, sensitivity analysis result for neural network indicated large fluctuation caused by the change of data input when added by new data.

Item Type:Article
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments / MOR / COE:Departments > Computer Information Sciences
ID Code:6244
Deposited By: Assoc Prof Dr Dhanapal Durai Dominic P
Deposited On:02 Aug 2011 04:04
Last Modified:19 Jan 2017 08:23

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