gesjGEOGRAPHY, ENVIRONMENT, SUSTAINABILITYGEOGRAPHY, ENVIRONMENT, SUSTAINABILITY2071-93882542-1565Russian Geographical Society10.24057/2071-9388-2025-3298gesj-3990Research ArticleRESEARCH PAPERСтатьиGeospatial Dynamics Of Dengue Fever Density In Kuantan, Malaysia: GIS-Based ApproachAbdul HadiZ.

42300, Puncak Alam, Selangor

Che DomN.

42300, Puncak Alam, Selangor

nazricd@uitm.edu.myIshakA. R.

42300, Puncak Alam, Selangor

SallehS. A.

40450, Shah Alam, Selangor

AbdullahS.

21030, Kuala Nerus, Terengganu

PrechaN.

Nakhon Si Thammarat

Faculty of Health Sciences, Universiti Teknologi MARA (UiTM), UITM Cawangan SelangorMalaysiaFaculty of Health Sciences, Universiti Teknologi MARA (UiTM), UITM Cawangan Selangor; Integrated Mosquito Research Group (I-MeRGe), Universiti Teknologi MARA (UiTM), UITM Cawangan SelangorMalaysiaInstitute for Biodiversity and Sustainable Development (IBSD), Universiti Teknologi MARAMalaysiaFaculty of Ocean Engineering Technology and Informatics, Universiti Malaysia TerengganuMalaysiaDepartment of Environmental Health and Technology, School of Public Health, Walailak UniversityThailand2025070420251815464Copyright © Abdul Hadi Z., Che Dom N., Ishak A.R., Salleh S.A., Abdullah S., Precha N., 20252025Abdul Hadi Z., Che Dom N., Ishak A.R., Salleh S.A., Abdullah S., Precha N.Abdul Hadi Z., Che Dom N., Ishak A.R., Salleh S.A., Abdullah S., Precha N.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://ges.rgo.ru/jour/article/view/3990

Dengue fever (DF) presents a significant public health challenge, particularly in tropical regions like Kuantan, Malaysia. This study utilizes Geographic Information System (GIS) technology to analyze spatial and temporal patterns of DF cases from 2011 to 2020. The aim is to understand geographical distribution, identify high-density areas, and discern temporal trends to guide targeted interventions. Kuantan, a rapidly urbanizing city with a notable DF incidence, serves as the study area. Leveraging a decade of Ministry of Health data encompassing 11,330 confirmed cases, ArcGIS 10.6 software maps disease distribution and identifies high-density clusters. Statistical analyses, including Kernel Density Estimation (KDE) and Standard Deviational Ellipses (SDE), reveal directional spread with Kuala Kuantan as the epicenter. Collaboration with vector control units validates high-density areas, linking environmental conditions and infrastructure to DF incidence. Demographic and socioeconomic variables, urbanization, and transportation connections are identified as influential factors. The study underscores the importance of collaborative data sharing and validates GIS-based approaches for targeted interventions. Integration into an early warning system is proposed, enhancing public health strategies in Kuantan and similar regions. Overall, this research contributes to understanding DF transmission dynamics and offers proactive frameworks for mitigating its impact through advanced technologies and collaborative efforts.

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The authors declare that there are no conflicts of interest present.