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., S., ., H., ., S., ., F., & ., S. (2021). Developing an Early Warning System Based on Correlation Analysis For Dengue Haemorrhagic Fever. KnE Life Sciences, 6(2), 52–60. https://doi.org/10.18502/kls.v0i0.8867

https://doi.org/10.18502/kls.v0i0.8867

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authors

  • Sumiati .

    Sumiati .

    1Disease Control and Eradication Section (P2P), East Jakarta Sub Department of Health, Jakarta, Indonesia
  • Hidayat .

    Hidayat .

    Research Center for Limnology, Indonesian Institute of Sciences, Bogor, West Java, Indonesia
  • Suprono .

    Suprono .

    Disease Control and Eradication Section (P2P), East Jakarta Sub Department of Health, Jakarta, Indonesia
  • Fachrudin .

    Fachrudin .

    Faculty of Mathematics and Natural Science, Universitas Pertahanan, Bogor, West Java, Indonesia
  • Satyaningsih .

    Satyaningsih .

    Research and Development Center for Meteorology, Climatology and Geophysics, Jakarta, Indonesia

Published Date

  • Mar 25, 2021

Developing an Early Warning System Based on Correlation Analysis For Dengue Haemorrhagic Fever

KnE Life Sciences / The 2nd International Scientific Meeting on Public Health and Sports (ISMoPHS 2020) / Pages 52–60

Abstract

Several cities in Indonesia have been declared as Dengue Haemorrhagic Fever (DHF)-endemic areas, including East Jakarta, an administrative city of DKI Jakarta Province. Surveillance is the most important activity in controlling and monitoring the development of DHF. This ecological study was conducted to assess the correlation between DHF cases, vector density (Larva Free Index [LFI]) and climate (rainfall and humidity). While the DHF cases were collected from hospitals report, vector density data were obtained from public health centres and climate data were obtained from the Meteorological, Climatological, and Geophysical Agency (BMKG). The correlations between DHF cases, vector density, and the climate were analysed based on weekly data, from week 1 to week 33 of 2019. This study showed a consistent trend of increasing and decreasing DHF cases with rainfall and LFI. DHF cases and LFI had a strong negative correlation (r = –0.72) at a time lag of six weeks. LFI and rainfall also showed a strong negative correlation (r = –0.86) at a time lag of five weeks. The strongest correlation between DHF cases and rainfall was found at week 8 (r = 0.87). Humidity, also an indicator of climate, had a strong positive correlation (r = 0.80) with DHF cases at the 11th-week time lag. However, contrarily, humidity had a strong negative correlation with LFI at the 5th-week time lag. These findings can be used for developing an early warning system that is reinforced by utilizing the application of HDF–climate information.


Keywords: dengue fever, vector, climate, early warning system

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