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Spatio-Temporal Modelling of Dengue Fever Patterns in Peninsular Malaysia from 2015–2017

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Abstract

Spatio-temporal disease mapping models can be used to describe the geographical pattern of disease incidence across space and time. This paper discusses the development and application of spatio-temporal disease models based on generalized linear mixed models (GLMM) incorporating spatially correlated random effects, temporal effects and space–time interaction. Further, the models are fitted within a hierarchical Bayesian framework with Integrated Nested Laplace Approximation (INLA) methodology. The main objectives of this study are to choose the model that best represents the pattern of dengue incidence in Peninsular Malaysia from 2015 to 2017, to estimate the relative risk of disease based on the model selected and to visualize the risk spatial pattern and temporal trend. The models were applied to weekly dengue fever data at the district level in Peninsular Malaysia as reported to the Ministry of Health Malaysia from 2015 to 2017. In conclusion, it can be seen that there was a difference in dengue trend for every district for 2015–2017 and the models used was effective in identifying the high and low risk areas of dengue incidence.

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Acknowledgements

Special thanks to Vector Borne Disease Sector, Ministry of Health Malaysia, for the dengue disease data provided in this study. Acknowledgement to Ministry of Higher Education Malaysia for Fundamental Research Grant Scheme with Project Code: FRGS/1/2018/STG06/USM/02/12. We also thank the reviewers and editors of Bulletin of the Malaysian Mathematical Sciences Society for their valuable comments with preparation of this manuscript.

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Authors and Affiliations

  1. School of Mathematical Sciences, Universiti Sains Malaysia, 11800, Gelugor, Pulau Pinang, Malaysia

    Nurul Syafiah Abd Naeeim & Nuzlinda Abdul Rahman

  2. Center for Statistical Studies and Decision Sciences, Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, 40450, Shah Alam, Selangor, Malaysia

    Nor Azura Md. Ghani

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  1. Nurul Syafiah Abd Naeeim
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  2. Nuzlinda Abdul Rahman
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  3. Nor Azura Md. Ghani
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Correspondence to Nuzlinda Abdul Rahman.

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Communicated by Anton Abdulbasah Kamil.

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Appendix A Map and District ID of Peninsular Malaysia

Appendix A Map and District ID of Peninsular Malaysia

See Fig. 7 and Table 6.

Table 6 ID number for districts in peninsular Malaysia
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Abd Naeeim, N.S., Abdul Rahman, N. & Md. Ghani, N.A. Spatio-Temporal Modelling of Dengue Fever Patterns in Peninsular Malaysia from 2015–2017. Bull. Malays. Math. Sci. Soc. 45 (Suppl 1), 345–364 (2022). https://doi.org/10.1007/s40840-022-01313-0

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