Philippine Journal of Science
153 (5): 1605-1622, October 2024
ISSN 0031 – 7683
Date Received: 20 Mar 2024
Spatiotemporal Analysis of Dengue Cases Distribution in Cavite, Philippines with Geographic Choropleth Mapping and Emerging Hotspot Analysis
Norie Neil C. Acosta1,2* and Nelda A. Nacion3,4,5
1Strategic and Advanced Analytics, Smart Communications, Inc., Legaspi Village, Makati City 1229 Metro Manila, the Philippines 2College of Science and Computer Studies, De La Salle University – Dasmariñas, Dasmariñas City 4114 Cavite, the Philippines 3Mathematics and Statistics Department, De La Salle University – Dasmariñas, Dasmariñas City 4114 Cavite, the Philippines 4Department of Mathematics and Statistics, De La Salle University Manila, Malate, Manila City 1004 Metro Manila, the Philippines 5College of Arts and Sciences, University of the Philippines Manila, Ermita, Manila City 1000 Metro Manila, the Philippines
*Corresponding author: norieneil_acosta@outlook.com
Acosta NN, Nacion N. 2024. Spatiotemporal Analysis of Dengue Cases Distribution in Cavite, Philippines with Geographic Choropleth Mapping and Emerging Hotspot Analysis. Philipp J Sci 153(5): 1605–1622.
ABSTRACT
Dengue fever, a viral infection transmitted by mosquitoes, presents a major public health challenge across different regions of the Philippines. Conducting spatiotemporal studies of dengue cases is essential for uncovering patterns and identifying emerging hotspots, thereby guiding effective public health interventions. This study utilized spatiotemporal analysis to reveal the combined effects of spatial and temporal factors in understanding the localized clustering patterns of dengue case distribution in Cavite, the Philippines. The research aimed to identify high-risk areas and periods prone to dengue outbreaks by identifying the emerging dengue hotspots and cold spots, providing valuable insights for targeted intervention strategies in the local aggregates of the province. The methodology entailed dengue data spanning from 01 Jan 2016–31 Dec 2020 in terms of demographic variables for preliminary descriptive statistics. Spatial analyses were employed to unravel the spatial clustering and spatial autocorrelation of the locality variable, whereas time-series analysis was employed to decompose the time-series data of the exposure variable into discernible trends and seasonality patterns of dengue. Results were summarized via choropleth mapping of the combined overlay of dengue hotspot maps and significant dengue clustering maps to produce the emerging dengue hotspot clustering maps. The analyses revealed evident heterogeneity in dengue distributions across temporal exposure and spatial localities. Furthermore, spatiotemporal heterogeneity was evident in specific cities and municipalities. The study identified six distinct classifications of emerging dengue hotspots within Cavite. Imus demonstrated persistent dengue hotspot characteristics, whereas Maragondon remained a consistent dengue coldspot. Bacoor exhibited sporadic hotspot tendencies, whereas Alfonso, General Emilio Aguinaldo, and Magallanes collectively exhibited sporadic coldspot attributes. The municipality of Tanza emerged as an intensifying hotspot, whereas conversely, Dasmariñas, General Trias, and Amadeo displayed diminishing dengue hotspots. Tailored dengue interventions should be implemented based on the specific characteristics of each hotspot classification, accounting for the temporal dynamics and geographical locations of dengue cases. Public health authorities in Cavite can employ targeted and effective measures to control the disease within different areas and at different times, thereby alleviating the overall burden of dengue in the province.
Keywords: dengue, epidemiology, spatial, spatiotemporal, temporal