Assessment of land use factors associated with dengue cases in Malaysia using Boosted Regression Trees
Assessment of land use factors associated with dengue cases in Malaysia using Boosted Regression Trees
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DOI：
10.1016/j.sste.2014.05.002
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发表时间：
2014-07-01
影响因子：
3.4
通讯作者：
Lakes, Tobia
中科院分区：
文献类型：
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作者：
Cheong, Yoon Ling;Leitao, Pedro J.;Lakes, Tobia
登革热的传播受媒介、宿主和病毒之间复杂的相互作用影响。水体等土地使用或某些农业做法已被确定为登革热的可能危险因素，因为它们为病媒提供了适宜的栖息地。许多研究侧重于小区域登革热媒介丰度的土地利用因素，但尚未研究大区域土地利用因素与登革热病例之间的关系。本研究旨在澄清人类住区以外的土地利用因素，例如不同类型的农业用地、水体和森林是否与马来西亚雪兰莪州2008年至2010年报告的登革热病例有关。从相关关系出发，生成预测风险图。我们使用增强回归树（BRT）来解释具有高预测精度的因素之间的非线性和相互作用。交叉验证性能评分（ROC AUC）为0.81的模型显示，最重要的土地利用因子是人类住区（39.2%），其次是水体（16.1%）、混合园艺（8.7%）、开阔地（7.5%）和被忽视草地（6.7%）。100次模型运行后的风险图，交叉验证的ROC AUC平均值为0.81 （+/- 0.001 s.d）。我们的发现可能是改善登革热监测和控制干预措施的重要资产。(C) 2014年作者。Elsevier Ltd.出版。
The transmission of dengue disease is influenced by complex interactions among vector, host and virus. Land use such as water bodies or certain agricultural practices have been identified as likely risk factors for dengue because of the provision of suitable habitats for the vector. Many studies have focused on the land use factors of dengue vector abundance in small areas but have not yet studied the relationship between land use factors and dengue cases for large regions. This study aims to clarify if land use factors other than human settlements, e.g. different types of agricultural land use, water bodies and forest are associated with reported dengue cases from 2008 to 2010 in the state of Selangor, Malaysia. From the correlative relationship, we aim to generate a prediction risk map. We used Boosted Regression Trees (BRT) to account for nonlinearities and interactions between the factors with high predictive accuracies. Our model with a cross-validated performance score (Area Under the Receiver Operator Characteristic Curve, ROC AUC) of 0.81 showed that the most important land use factors are human settlements (model importance of 39.2%), followed by water bodies (16.1%), mixed horticulture (8.7%), open land (7.5%) and neglected grassland (6.7%). A risk map after 100 model runs with a cross-validated ROC AUC mean of 0.81 (+/- 0.001 s.d.) is presented. Our findings may be an important asset for improving surveillance and control interventions for dengue. (C) 2014 The Authors. Published by Elsevier Ltd.