Spatio-temporal analysis of dengue cases in Sabah
Introduction: Dengue fever is a significant public health issue worldwide. Geographic Information System is a powerful tool in public health, allowing for the analysis and visualisation of spatial data to understand disease distribution and identify clusters of cases. Therefore, this study aims to d...
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| Format: | Article |
| Language: | English |
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Universiti Putra Malaysia
2023
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| Online Access: | https://eprints.ums.edu.my/id/eprint/42554/1/FULL%20TEXT.pdf |
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| author | Priya Dharishini Kunasagran Syed Sharizman Syed Abdul Rahim Mohammad Saffree Jeffree Azman Atil Aizuddin Hidrus Khalid Mokti Mohammad Aklil Abd Rahim Adora J Muyou Sheila Miriam Mujin Nabihah Ali Norsyahida Md Taib S Muhammad Izuddin Rabbani Mohd Zali Rahmat Dapari Zahir Izuan Azhar Koay Teng Khoon |
| author_facet | Priya Dharishini Kunasagran Syed Sharizman Syed Abdul Rahim Mohammad Saffree Jeffree Azman Atil Aizuddin Hidrus Khalid Mokti Mohammad Aklil Abd Rahim Adora J Muyou Sheila Miriam Mujin Nabihah Ali Norsyahida Md Taib S Muhammad Izuddin Rabbani Mohd Zali Rahmat Dapari Zahir Izuan Azhar Koay Teng Khoon |
| author_sort | Priya Dharishini Kunasagran |
| collection | UMS |
| description | Introduction: Dengue fever is a significant public health issue worldwide. Geographic Information System is a powerful tool in public health, allowing for the analysis and visualisation of spatial data to understand disease distribution and identify clusters of cases. Therefore, this study aims to determine the spatiotemporal distribution of dengue cases in Sabah. Methods: Quantum Geospatial Information System (QGIS) and GeoDa software were used to determine the spatial distribution, pattern, and cluster analysis. Results: The spatial distribution of dengue cases shifted, with most cases concentrated on the east coast of Sabah. The distribution of dengue cases in Beluran, Tenom, Kota Marudu, Kudat, Keningau, and Papar changed from 2017 to 2020. The scatter plots of Moran’s index values were generated to analyse the spatial clustering of dengue cases in Sabah over four years: 2017 (Moran’s index = 0.271), 2018 (Moran’s index = 0.333), 2019 (Moran’s index = 0.367), and 2020 (Moran’s index = 0.294). The statistical significance of clustering was established by observing p-values below the threshold of 0.05 for all four years. Local indicators of spatial association showed the spatial autocorrelation pattern of high-high (hotspot) areas with elevated dengue incidence and low-low (cold-spot) areas with relatively lower dengue rates. Conclusion: This study has provided evidence of dengue case distribution patterns, spatial clustering, and hotspot and coldspot areas. Prioritising these clusters can improve planning and resource allocation for more efficient dengue prevention and control. |
| first_indexed | 2025-03-05T01:35:13Z |
| format | Article |
| id | ums.eprints-42554 |
| institution | Universiti Malaysia Sabah |
| language | English |
| last_indexed | 2025-03-05T01:35:13Z |
| publishDate | 2023 |
| publisher | Universiti Putra Malaysia |
| record_format | dspace |
| spelling | ums.eprints-425542025-01-07T04:05:09Z https://eprints.ums.edu.my/id/eprint/42554/ Spatio-temporal analysis of dengue cases in Sabah Priya Dharishini Kunasagran Syed Sharizman Syed Abdul Rahim Mohammad Saffree Jeffree Azman Atil Aizuddin Hidrus Khalid Mokti Mohammad Aklil Abd Rahim Adora J Muyou Sheila Miriam Mujin Nabihah Ali Norsyahida Md Taib S Muhammad Izuddin Rabbani Mohd Zali Rahmat Dapari Zahir Izuan Azhar Koay Teng Khoon RA643-645 Disease (Communicable and noninfectious) and public health Introduction: Dengue fever is a significant public health issue worldwide. Geographic Information System is a powerful tool in public health, allowing for the analysis and visualisation of spatial data to understand disease distribution and identify clusters of cases. Therefore, this study aims to determine the spatiotemporal distribution of dengue cases in Sabah. Methods: Quantum Geospatial Information System (QGIS) and GeoDa software were used to determine the spatial distribution, pattern, and cluster analysis. Results: The spatial distribution of dengue cases shifted, with most cases concentrated on the east coast of Sabah. The distribution of dengue cases in Beluran, Tenom, Kota Marudu, Kudat, Keningau, and Papar changed from 2017 to 2020. The scatter plots of Moran’s index values were generated to analyse the spatial clustering of dengue cases in Sabah over four years: 2017 (Moran’s index = 0.271), 2018 (Moran’s index = 0.333), 2019 (Moran’s index = 0.367), and 2020 (Moran’s index = 0.294). The statistical significance of clustering was established by observing p-values below the threshold of 0.05 for all four years. Local indicators of spatial association showed the spatial autocorrelation pattern of high-high (hotspot) areas with elevated dengue incidence and low-low (cold-spot) areas with relatively lower dengue rates. Conclusion: This study has provided evidence of dengue case distribution patterns, spatial clustering, and hotspot and coldspot areas. Prioritising these clusters can improve planning and resource allocation for more efficient dengue prevention and control. Universiti Putra Malaysia 2023 Article NonPeerReviewed text en https://eprints.ums.edu.my/id/eprint/42554/1/FULL%20TEXT.pdf Priya Dharishini Kunasagran and Syed Sharizman Syed Abdul Rahim and Mohammad Saffree Jeffree and Azman Atil and Aizuddin Hidrus and Khalid Mokti and Mohammad Aklil Abd Rahim and Adora J Muyou and Sheila Miriam Mujin and Nabihah Ali and Norsyahida Md Taib and S Muhammad Izuddin Rabbani Mohd Zali and Rahmat Dapari and Zahir Izuan Azhar and Koay Teng Khoon (2023) Spatio-temporal analysis of dengue cases in Sabah. Malaysian Journal of Medicine and Health Sciences, 19 (supp20). pp. 1-7. ISSN 2636-9346 |
| spellingShingle | RA643-645 Disease (Communicable and noninfectious) and public health Priya Dharishini Kunasagran Syed Sharizman Syed Abdul Rahim Mohammad Saffree Jeffree Azman Atil Aizuddin Hidrus Khalid Mokti Mohammad Aklil Abd Rahim Adora J Muyou Sheila Miriam Mujin Nabihah Ali Norsyahida Md Taib S Muhammad Izuddin Rabbani Mohd Zali Rahmat Dapari Zahir Izuan Azhar Koay Teng Khoon Spatio-temporal analysis of dengue cases in Sabah |
| title | Spatio-temporal analysis of dengue cases in Sabah |
| title_full | Spatio-temporal analysis of dengue cases in Sabah |
| title_fullStr | Spatio-temporal analysis of dengue cases in Sabah |
| title_full_unstemmed | Spatio-temporal analysis of dengue cases in Sabah |
| title_short | Spatio-temporal analysis of dengue cases in Sabah |
| title_sort | spatio temporal analysis of dengue cases in sabah |
| topic | RA643-645 Disease (Communicable and noninfectious) and public health |
| url | https://eprints.ums.edu.my/id/eprint/42554/1/FULL%20TEXT.pdf |
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