Abstract
Introduction: Dengue fever (DF) is a viral disease transmitted by the Aedes-spp mosquito. Each year, 390 million dengue virus infections of which 96 million (67-136 million) show clinical symptoms (with any severity of disease). The current risk affects about half of the world's population. GIS analysis is crucial for dengue research because it helps show and model the geographic relationship between cause and disease. A dengue risk map has been produced using a variety of spatial statistics methods as well as GIS. DF frequently shows distinct spatial and temporal patterns. Urban disease dynamics present a significant challenge to public health systems
Methodology: To ascertain the geographical distribution of dengue fever cases in Kuantan, several statistical analytic techniques in ArcGIS v10.6 were employed. The spatial pattern of dengue epidemics was measured using the geographical distribution pattern. Distributions in ambiguous areas were established and potential hot spots were found using Kernel Density Estimation (KDE).
Result: More than 11330 confirmed dengue fever (DF) cases were recorded in Kuantan between 2011 and 2020. The number of DF cases was examined to identify hotspots for DF occurrences, which were discovered and illustrated by overlaying maps. The Kuala Kuantan sub district had the highest density of hotspot clustering, followed by Sungai Karang and Penor sub districts.
Discussion: By identified dengue fever hot spots within the district of Kuantan between 2011 to 2020, this study suggests that distinct patterns occur in various places at different times. An infectious disease that is highly transmissible due to its mosquito vector, Aedes aegypti , dengue fever has adapted to urban and sub-urban environments well. As such, it can spread from the initial point of an outbreak to locations well beyond the flight range of its mosquito vectors. This implies that the transmission of dengue fever is influenced by variables other than the flight of mosquitoes.
Conclusion: The results of this study show that the suggested methods and resources can assist public health professionals in developing warnings and public awareness campaigns by assisting them in visualising and understanding the distribution and trends of illness spreading patterns. Identifying spatiotemporal dispersion patterns and hot spots of dengue fever may assist public health officials control and forecast its spread. Recommendation: Programs for public health education are necessary to promote habitat reduction and keep working waste disposal systems. The threat of vector re-entry into the area may also encourage locals to keep up these practises after the relevant mosquito species has been eliminated. However, these eradication methods demand additional spatiotemporal research to find other factors that might cause dengue fever outbreaks in a particular area.
Links
- https://apcph.cphm.my/wp-content/uploads/2022/07/APCPH2022-P-108.pdf
- https://apcph.cphm.my/wp-content/uploads/wpforms/1176-1e04940bb5d885bf8711ed1909[...]
BibTeX (Download)
@proceedings{APCPH2022-P-108,
title = {Spatial Temporal Analysis of Dengue Risk Area in Kuantan, Malaysia},
author = {Zulkifli Abdul Hadi and Nazri Che Dom and Siti Aekbal Salleh and Samsuri Abdullah and Nopadol Precha and Mohd Rahim Sulong},
url = {https://apcph.cphm.my/wp-content/uploads/2022/07/APCPH2022-P-108.pdf
https://apcph.cphm.my/wp-content/uploads/wpforms/1176-1e04940bb5d885bf8711ed19095a89ed/APCPH-ZulkifliAbdulHadi_V01-fa6f067bcdc465138f6a2d07d65fb235.pdf},
year = {2022},
date = {2022-08-02},
urldate = {2022-08-02},
issue = {7},
abstract = {Introduction: Dengue fever (DF) is a viral disease transmitted by the Aedes-spp mosquito. Each year, 390 million dengue virus infections of which 96 million (67-136 million) show clinical symptoms (with any severity of disease). The current risk affects about half of the world's population. GIS analysis is crucial for dengue research because it helps show and model the geographic relationship between cause and disease. A dengue risk map has been produced using a variety of spatial statistics methods as well as GIS. DF frequently shows distinct spatial and temporal patterns. Urban disease dynamics present a significant challenge to public health systems
Methodology: To ascertain the geographical distribution of dengue fever cases in Kuantan, several statistical analytic techniques in ArcGIS v10.6 were employed. The spatial pattern of dengue epidemics was measured using the geographical distribution pattern. Distributions in ambiguous areas were established and potential hot spots were found using Kernel Density Estimation (KDE).
Result: More than 11330 confirmed dengue fever (DF) cases were recorded in Kuantan between 2011 and 2020. The number of DF cases was examined to identify hotspots for DF occurrences, which were discovered and illustrated by overlaying maps. The Kuala Kuantan sub district had the highest density of hotspot clustering, followed by Sungai Karang and Penor sub districts.
Discussion: By identified dengue fever hot spots within the district of Kuantan between 2011 to 2020, this study suggests that distinct patterns occur in various places at different times. An infectious disease that is highly transmissible due to its mosquito vector, Aedes aegypti , dengue fever has adapted to urban and sub-urban environments well. As such, it can spread from the initial point of an outbreak to locations well beyond the flight range of its mosquito vectors. This implies that the transmission of dengue fever is influenced by variables other than the flight of mosquitoes.
Conclusion: The results of this study show that the suggested methods and resources can assist public health professionals in developing warnings and public awareness campaigns by assisting them in visualising and understanding the distribution and trends of illness spreading patterns. Identifying spatiotemporal dispersion patterns and hot spots of dengue fever may assist public health officials control and forecast its spread. Recommendation: Programs for public health education are necessary to promote habitat reduction and keep working waste disposal systems. The threat of vector re-entry into the area may also encourage locals to keep up these practises after the relevant mosquito species has been eliminated. However, these eradication methods demand additional spatiotemporal research to find other factors that might cause dengue fever outbreaks in a particular area.},
howpublished = {published online at https://apcph.cphm.my},
note = {Type: POSTER PRESENTATION; Organisation: Kuantan District Health Office; Centre of Environmental Health \& Safety studies, Faculty of Health Sciences, Universiti Teknologi MARA (UiTM); Institute for Biodiversity and Sustainable Development, Universiti Teknologi MARA (UITM); Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu; Department of Environmental Health and Technology, School of Public Health, Walailak University; Kuantan District Health Office},
keywords = {Hotspot; Dengue Fever; Kernel Density Estimation; KDE},
pubstate = {published},
tppubtype = {proceedings}
}