title: Assessment of land use factors associated with dengue cases in Malaysia using Boosted Regression Trees.
abstract: 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.
authors.affiliation: Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany; Medical Research Resource Centre, Institute for Medical Research, Jalan Pahang, 50588 Kuala Lumpur, Malaysia. Electronic address: yoon.ling.cheong@geo.hu-berlin.de.
authors.forename: Yoon Ling
authors.initials: YL
authors.lastname: Cheong
authors.affiliation: Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany. Electronic address: p.leitao@geo.hu-berlin.de.
authors.forename: Pedro J
authors.initials: PJ
authors.lastname: Leitão
authors.affiliation: Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany. Electronic address: tobia.lakes@geo.hu-berlin.de.
authors.forename: Tobia
authors.initials: T
authors.lastname: Lakes
mesh_terms: D003140:Communicable Disease Control; D003715:Dengue / Q000453:epidemiology* / Q000517:prevention & control; D006801:Humans; D008296:Malaysia / Q000453:epidemiology; D015233:Models, Statistical; D011156:Population Density; D012372:ROC Curve; D062206:Spatial Analysis
keywords: Aedes mosquitoes; Boosted Regression Trees; Environmental; Horticulture; Human settlements; Land use