Journal of infection in developing countries · 2026
Predicting suitable spatial niches in the Philippines for Ascaris lumbricoides using bioclimatic envelope models.
СтатьяНазвание и аннотация: Перевод в очереди
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Recopuerto-Medina Loida M, Dizon Princess Anne T, Dumo Paulene Dg, El Oirdighi Aya R, Fernandez Dana Patricia P, Lumang Karla Sophia L, Dagamac Nikki Heherson
Аннотация
INTRODUCTION: Recent studies on the spatial distribution of A. lumbricoides in the Philippines have used the data available from the nationwide parasitological survey in the early 2000s. This study developed an updated predictive map of the spatial distribution of ascariasis occurrences in the Philippines using data from 2000-2020 to identify high-risk areas for ascariasis.
METHODOLOGY: Data were acquired from WorldClim and included 19 bioclimatic variables. Additionally, the geographical distribution of species occurrence records was obtained through literature and known medical reports for ascariasis cases. The spatial distribution was mapped using QGIS after running the occurrence and environmental layers in the software Maxent.
RESULT: The predictive map revealed a high percentage of occurrences of ascariasis in Central Luzon, Calabarzon, Western Visayas, Bicol Region, and Central Visayas. The average training area under the receiver operating characteristic curve (AUC) for the replicate runs was 0.873. Analysis of variable contribution showed the highest percentage predictive contribution of the mean temperature during the warmest quarter (49.4%), annual range of temperature (10.9%), and mean temperature during the driest quarter (10.9%).
CONCLUSIONS: The species predictive map generated in this study can identify bioclimatic variables associated with the high prevalence of A. lumbricoides. Since extensive parasitological surveys can be costly and time-consuming, predictions on A. lumbricoides distribution can fill the gap in areas lacking data. Consequently, a detailed understanding of the distribution of A. lumbricoides will assist in identifying high-risk areas for effective public health intervention, especially in underfunded regions in the Philippines.
METHODOLOGY: Data were acquired from WorldClim and included 19 bioclimatic variables. Additionally, the geographical distribution of species occurrence records was obtained through literature and known medical reports for ascariasis cases. The spatial distribution was mapped using QGIS after running the occurrence and environmental layers in the software Maxent.
RESULT: The predictive map revealed a high percentage of occurrences of ascariasis in Central Luzon, Calabarzon, Western Visayas, Bicol Region, and Central Visayas. The average training area under the receiver operating characteristic curve (AUC) for the replicate runs was 0.873. Analysis of variable contribution showed the highest percentage predictive contribution of the mean temperature during the warmest quarter (49.4%), annual range of temperature (10.9%), and mean temperature during the driest quarter (10.9%).
CONCLUSIONS: The species predictive map generated in this study can identify bioclimatic variables associated with the high prevalence of A. lumbricoides. Since extensive parasitological surveys can be costly and time-consuming, predictions on A. lumbricoides distribution can fill the gap in areas lacking data. Consequently, a detailed understanding of the distribution of A. lumbricoides will assist in identifying high-risk areas for effective public health intervention, especially in underfunded regions in the Philippines.