Spatial Mapping and Modeling of Reported Dengue Incidences in Luzon

• Main Authors: Hernandez, Nicole M., Lucero, Carla Katrine P., Yumol, Dianne C., Zulueta, Jericho Manuel A.
• 格式: text
• 出版: Animo Repository 2021
• 主題: spatial mapping; regression modeling; dengue incidence; correlation; Aedes aegypti
• 在線閱讀: https://animorepository.dlsu.edu.ph/conf_shsrescon/2021/paper_fnh/8; https://animorepository.dlsu.edu.ph/context/conf_shsrescon/article/1621/viewcontent/FNH_Spatial_Mapping_and_Modeling_of_Reported_Dengue_Incidences_in_Luzon.pdf
• 機構: De La Salle University

Dengue, the most rapidly spreading mosquito-borne viral infection, has significantly spread worldwide in recent decades - flourishing both in affluent and impoverished locations of tropical and subtropical countries. In 2012, the Philippines ranked fourth out of the ten Association of the Southeast Asian Nations (ASEAN) countries in having the highest number of dengue cases. The following study intends to analyze the spatial distribution of dengue incidences across all Luzon provinces in 2018. It aims to determine significant correlates that affect dengue incidences, map the incidence rate of dengue cases, and explore the clustering of recorded dengue cases. Poisson and Negative Binomial (NB) regression analyses and Multiple Linear Regression Models (MLRM) were applied to determine the significant correlations affecting dengue incidence rates. Simultaneously, spatial mapping was utilized to visualize and detect clustering in the provinces through dengue count, incidence ratios, and standard incidence ratios (SIR). MLRM and NB showed that rainfall and poverty incidence are significant correlates of dengue counts and incidence, and Nueva Ecija and Tarlac were observed to be provinces with distinct dengue count and SIR greater than 1, as well as provinces found in clusters. With the provided results, health organizations can provide health programs and allocate more funds in areas with SIR greater than 1 to prevent dengue spreading.