Spatiotemporal Analysis of Dengue Cases Distribution in Cavite, Philippines with Geographic Choropleth Mapping and Emerging Hotspot Analysis

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.

Publication Details

Journal
The Philippine journal of science
Published
2024-10-01
DOI
https://doi.org/10.56899/153.05.10
Primary Topic
Higher Education Research Studies
Type
article
Field-Weighted Citation Impact
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article

Spatiotemporal Analysis of Dengue Cases Distribution in Cavite, Philippines with Geographic Choropleth Mapping and Emerging Hotspot Analysis

The Philippine journal of science
Higher Education Research Studies
article

Spatiotemporal Analysis of Dengue Cases Distribution in Cavite, Philippines with Geographic Choropleth Mapping and Emerging Hotspot Analysis

article en

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.

The Philippine journal of scienceVol. 153(5)
Good health and well-being
Openalex Percentile: Top 21%
Higher Education Research Studies
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