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Validation of Bipartite Network Model of Dengue Hotspot Detection in Sarawak

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Computational Science and Technology

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 481))

Abstract

This paper presents the verification and validation processes in producing a realistic bipartite network model to detect dengue hotspot in Sarawak. Based on the result of previous published work, ranking of location nodes of possible dengue hotspot at Sarawak are used to illustrate the validation by comparing the Spearman rank correlation coefficients (SRCC) between the network models. UCINET 6 is used to generate a benchmark ranking result for model verification. A centrality measure analysis feature available in UCINET is used to determine the node centrality of a network model. The validation results show strong ranking similarity for all three groups of network models with good Spearman rank correlation coefficients values of 1.000, 0.8000 and 0.8824 (ρ>0.80; p<0.001) respectively. The top-ranked locations are seen as dengue hotspots and this study demonstrate a new approach to model dengue transmission at district-level by locating the hotspots and prioritizing the locations according to vector density.

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Acknowledgements

The authors thank Universiti Malaysia Sarawak for the support in carrying out this research under the grant numbered F08/SpFRGS/1601/2017. Our heartfelt thanks also go to Sarawak State Health Department and Sarawak Meteorological Department for providing the research data.

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Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, Sarawak, Malaysia

    Woon Chee Kok & Jane Labadin

Authors
  1. Woon Chee Kok
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  2. Jane Labadin
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Corresponding author

Correspondence to Woon Chee Kok .

Editor information

Editors and Affiliations

  1. Knowledge Technology Research Unit, Faculty of Computing and Informatics, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia

    Rayner Alfred

  2. School of Information Science, Security and Networks Area, Japan Advanced Institute of Science and Technology, Ishikawa, Japan

    Yuto Lim

  3. Faculty of Computing and Informatics, Universiti Malaysia Sabah Faculty of Computing and Informatics, Kota Kinabalu, Sabah, Malaysia

    Ag Asri Ag Ibrahim

  4. Lincoln University , Christchurch, New Zealand

    Patricia Anthony

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Kok, W.C., Labadin, J. (2019). Validation of Bipartite Network Model of Dengue Hotspot Detection in Sarawak. In: Alfred, R., Lim, Y., Ibrahim, A., Anthony, P. (eds) Computational Science and Technology. Lecture Notes in Electrical Engineering, vol 481. Springer, Singapore. https://doi.org/10.1007/978-981-13-2622-6_33

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  • DOI: https://doi.org/10.1007/978-981-13-2622-6_33

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-2621-9

  • Online ISBN: 978-981-13-2622-6

  • eBook Packages: EngineeringEngineering (R0)

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