Predicting suitable spatial niches in the Philippines for Ascaris lumbricoides using bioclimatic envelope models.

IF 1.3 4区 医学 Q4 INFECTIOUS DISEASES
Loida M Recopuerto-Medina, Princess Anne T Dizon, Paulene Dg Dumo, Aya R El Oirdighi, Dana Patricia P Fernandez, Karla Sophia L Lumang, Nikki Heherson Dagamac
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引用次数: 0

Abstract

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.

利用生物气候包络模型预测菲律宾蛔虫适宜的空间生态位
最近对菲律宾蚓类的空间分布进行的研究使用了21世纪初全国寄生虫学调查的数据。本研究利用2000-2020年的数据开发了菲律宾蛔虫病发生空间分布的更新预测图,以确定蛔虫病的高风险地区。方法:数据来自WorldClim,包括19个生物气候变量。此外,通过文献和已知的蛔虫病病例医学报告,获得了物种发生记录的地理分布。在Maxent软件中运行发生层和环境层后,利用QGIS绘制空间分布图。结果:预测图显示,中吕宋岛、卡拉巴松岛、西米沙鄢群岛、比科尔地区和中米沙鄢群岛的蛔虫病发病率很高。受试者工作特征曲线(AUC)下的平均训练面积为0.873。变量贡献分析显示,最暖季平均温度的预测贡献率最高(49.4%),年温差(10.9%)和最干燥季平均温度的预测贡献率最高(10.9%)。结论:本研究建立的物种预测图可以识别与腰麻高流行率相关的生物气候变量。由于广泛的寄生虫学调查既昂贵又耗时,对类蚓分布的预测可以填补缺乏数据的地区的空白。因此,对类蚓分布的详细了解将有助于确定高风险地区,以便进行有效的公共卫生干预,特别是在菲律宾资金不足的地区。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.70
自引率
5.30%
发文量
239
审稿时长
4-8 weeks
期刊介绍: The Journal of Infection in Developing Countries (JIDC) is an international journal, intended for the publication of scientific articles from Developing Countries by scientists from Developing Countries. JIDC is an independent, on-line publication with an international editorial board. JIDC is open access with no cost to view or download articles and reasonable cost for publication of research artcles, making JIDC easily availiable to scientists from resource restricted regions.
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