Generating Vulnerability Maps of Dengue Incidences for Petaling District in Malaysia

Nirbhay Mathur, Vijanth S. Asirvadam, Sarat C. Dass, Balvinder Singh Gill

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Dengue has been reported as a major cause of morbidity and mortality for the last 40 years worldwide including Malaysia. This work develops and implements visualization and predictive modelling for dengue in Malaysia. The incidences are visualized using Geographical Information System (GIS) which provides information on coordinates (latitude and longitude) based on the occurrence of incidences registered with the Disease Control Division of the Ministry of Health, Malaysia. Clustering is performed on this data using centroid and distribution models that are representatives of K-means and the Expectation Maximization (EM) algorithms, respectively. The results are validated for Petaling district of Selangor and are shown to possess good performance in predicting the dengue incidences. The proposed method is able to localize the incidences which can further be utilized for vector disease control processes.
Original languageEnglish
Title of host publication2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA)
PublisherIEEE
Pages227-232
Number of pages6
ISBN (Electronic)9781467387804
DOIs
Publication statusPublished - 21 Jul 2016

Keywords

  • dengue
  • clustering algorithm
  • GIS
  • K-means
  • EM algorithm

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