CSNano Seminar Series 13: Associate Professor Dr Jane Labadin

The event is open to the public. All are welcome to attend.

Scientific Talk

Dr. Jane Labadin
Associate Professor
Faculty of Computer Science & Information Technology,
Universiti Malaysia Sarawak
94300 Kota Samarahan, Sarawak, Malaysia

ljane@unimas.my
http://www.fcsit.unimas.my/jane

Date : 7 May 2017 (Sunday)
Time : 2.30 pm – 4.30 pm
Venue : Meeting Room, N31, Centre for Sustainable Nanomaterials (CSNano), Ibnu Sina Institute for Scientific and Industrial Research, Universiti Teknologi Malaysia, Skudai, Johor Bahru
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Jane Labadin is a Assoc. Professor of Faculty of Computer Science & Information Technology at University Malaysia Sarawak, Malaysia. She received her Ph.D. in computational mathematic at the Imperial College of Science, Technology and Medicine, London, UK in 2002. Her research interests lie broadly in the areas of ICT for Development, Soft­ware devel­op­ment for rural communities, Human Com­puter Interaction, and Indige­nous Knowl­edge Management. She has published over 60 research articles and conference papers. She is also currently the Director of UNIMAS Publisher at the University Malaysia Sarawak.
 
Presentation Abstract
“Generic Transmission Model For Mosquito-Borne Infectious Diseases”
 
Dr. Jane Labadin
 
Mosquito-borne diseases are extreme health issues. These diseases are transmitted from human to human via the vector, which is mosquito. The knowledge of the possible behavior of its spread will enable the best control measure to be selected. Previous research has shown that mathematical models are used for predicting the spread of diseases over time. However, the proposed mathematical models are for specific disease, whereas mosquito-borne diseases are usually spread by a common vector, giving rise to notable similarities in their transmission. It is thus, worthwhile to formulate a generic model that includes both the temporal and spatial factors. Starting of with an initial model and compared with published result, the model is then refined until simulations are in good agreement with selected literature. The formulated generic model is validated by comparing the numerical simulations with the actual cases of malaria and dengue.