Spatio-temporal clustering analysis of dengue disease in Peninsular Malaysia

• Published in: Journal of public health Vol. 31; no. 2; pp. 307 - 317
• Main Authors: Abd Naeeim, Nurul Syafiah, Abdul Rahman, Nuzlinda
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2023; Springer Nature B.V
• Subjects: Cluster analysis; Clustering; Dengue fever; Disease; Disease control; Epidemiology; Health Promotion and Disease Prevention; Infectious diseases; Medicine; Medicine & Public Health; Original Article; Public Health; Similarity; Statistical analysis; Vector-borne diseases; Malaysia; SaTScan; Space-time cluster; Disease mapping; Dengue
• ISSN: 2198-1833; 1613-2238
• DOI: 10.1007/s10389-020-01448-z

Aim This study aims to detect the spatial cluster, the temporal cluster, as well as the spatio-temporal cluster of high dengue disease incidence in Peninsular Malaysia for the year 2015 until 2017. As dengue disease cases are properly recorded according to their location and time, cluster analysis of the dengue disease based on its spatial, temporal, as well as spatio-temporal similarity would be more efficient. Subject and Methods Clustering is one of the essential components in disease mapping that could be helpful in controlling diseases, especially those related to infectious disease. It is used to group large sets of disease data based on their similarity. The clustering method that has been used in this study is Kulldorff’s retrospective space-time scan statistics. The data used in this study are weekly dengue disease cases in districts of Peninsular Malaysia from 2015 to 2017. Results and Conclusions From the results, there were significant spatial cluster, temporal cluster, and spatio-temporal clusters of dengue disease incidence in Peninsular Malaysia for 2015, 2016, and 2017. Results from spatial clustering focused on areas in Selangor as the dengue clustered area and results from temporal clustering revealed the weeks in October until December as the dengue clustered period. Meanwhile, the spatio-temporal clustering demonstrated that there exists another clustered region of high dengue disease incidence in different areas and time periods.