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The Effects of Meteorological Factors on Dengue Cases in Malaysia

Author

Listed:
  • Sarbhan Singh

    (Institute for Medical Research, Ministry of Health, Shah Alam 40170, Malaysia)

  • Lai Chee Herng

    (Institute for Medical Research, Ministry of Health, Shah Alam 40170, Malaysia)

  • Lokman Hakim Sulaiman

    (Institute for Research, Development and Innovation (IRDI), International Medical University, Kuala Lumpur 57000, Malaysia
    School of Medicine, International Medical University, Kuala Lumpur 57000, Malaysia)

  • Shew Fung Wong

    (School of Medicine, International Medical University, Kuala Lumpur 57000, Malaysia
    Centre for Environmental and Population Health, Institute for Research, Development and Innovation (IRDI), International Medical University, Kuala Lumpur 57000, Malaysia)

  • Jenarun Jelip

    (Vector Borne Disease Control Division, Ministry of Health Malaysia, Putrajaya 62000, Malaysia)

  • Norhayati Mokhtar

    (Vector Borne Disease Control Division, Ministry of Health Malaysia, Putrajaya 62000, Malaysia)

  • Quillon Harpham

    (HR Wallingford, Wallingford OX10 8BA, UK)

  • Gina Tsarouchi

    (HR Wallingford, Wallingford OX10 8BA, UK)

  • Balvinder Singh Gill

    (Institute for Medical Research, Ministry of Health, Shah Alam 40170, Malaysia)

Abstract

Dengue is a vector-borne disease affected by meteorological factors and is commonly recorded from ground stations. Data from ground station have limited spatial representation and accuracy, which can be overcome using satellite-based Earth Observation (EO) recordings instead. EO-based meteorological recordings can help to provide a better understanding of the correlations between meteorological variables and dengue cases. This paper aimed to first validate the satellite-based (EO) data of temperature, wind speed, and rainfall using ground station data. Subsequently, we aimed to determine if the spatially matched EO data correlated with dengue fever cases from 2011 to 2019 in Malaysia. EO data were spatially matched with the data from four ground stations located at states and districts in the central (Selangor, Petaling) and east coast (Kelantan, Kota Baharu) geographical regions of Peninsular Malaysia. Spearman’s rank-order correlation coefficient (ρ) was performed to examine the correlation between EO and ground station data. A cross-correlation analysis with an eight-week lag period was performed to examine the magnitude of correlation between EO data and dengue case across the three time periods (2011–2019, 2015–2019, 2011–2014). The highest correlation between the ground-based stations and corresponding EO data were reported for temperature (mean ρ = 0.779), followed by rainfall (mean ρ = 0.687) and wind speed (mean ρ = 0.639). Overall, positive correlations were observed between weekly dengue cases and rainfall for Selangor and Petaling across all time periods with significant correlations being observed for the period from 2011 to 2019 and 2015 to 2019. In addition, positive significant correlations were also observed between weekly dengue cases and temperature for Kelantan and Kota Baharu across all time periods, while negative significant correlations between weekly dengue cases and temperature were observed in Selangor and Petaling across all time periods. Overall negative correlations were observed between weekly dengue cases and wind speed in all areas from 2011 to 2019 and 2015 to 2019, with significant correlations being observed for the period from 2015 to 2019. EO-derived meteorological variables explained 48.2% of the variation in dengue cases in Selangor. Moderate to strong correlations were observed between meteorological variables recorded from EO data derived from satellites and ground stations, thereby justifying the use of EO data as a viable alternative to ground stations for recording meteorological variables. Both rainfall and temperature were found to be positively correlated with weekly dengue cases; however, wind speed was negatively correlated with dengue cases.

Suggested Citation

  • Sarbhan Singh & Lai Chee Herng & Lokman Hakim Sulaiman & Shew Fung Wong & Jenarun Jelip & Norhayati Mokhtar & Quillon Harpham & Gina Tsarouchi & Balvinder Singh Gill, 2022. "The Effects of Meteorological Factors on Dengue Cases in Malaysia," IJERPH, MDPI, vol. 19(11), pages 1-24, May.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:11:p:6449-:d:824402
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    References listed on IDEAS

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    4. Felipe J Colón-González & Leonardo Soares Bastos & Barbara Hofmann & Alison Hopkin & Quillon Harpham & Tom Crocker & Rosanna Amato & Iacopo Ferrario & Francesca Moschini & Samuel James & Sajni Malde &, 2021. "Probabilistic seasonal dengue forecasting in Vietnam: A modelling study using superensembles," PLOS Medicine, Public Library of Science, vol. 18(3), pages 1-30, March.
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    Cited by:

    1. Adivânia Cardoso da Silva & Paulo Sérgio Scalize, 2023. "Environmental Variables Related to Aedes aegypti Breeding Spots and the Occurrence of Arbovirus Diseases," Sustainability, MDPI, vol. 15(10), pages 1-21, May.
    2. Luba Pascoe & Thomas Clemen & Karen Bradshaw & Devotha Nyambo, 2022. "Review of Importance of Weather and Environmental Variables in Agent-Based Arbovirus Models," IJERPH, MDPI, vol. 19(23), pages 1-24, November.

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