4.3 Article

MaxEnt modeling of soil-transmitted helminth infection distributions in Thailand

Journal

PARASITOLOGY RESEARCH
Volume 117, Issue 11, Pages 3507-3517

Publisher

SPRINGER
DOI: 10.1007/s00436-018-6048-7

Keywords

Soil-transmitted helminths; Geographic information system; Remote sensing; Ecological niche modeling; Thailand

Categories

Funding

  1. Thailand Research Fund [TRG5790198]
  2. Khon Kaen University New Researcher Development Grant

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Infections due to soil-transmitted helminths (STHs), i.e. Ascaris lumbricoides, Trichuris trichiura, hookworms, and Strongyloides stercoralis, are widely distributed in tropical and subtropical areas in which approximately 1.5 billion people are infected. A clear understanding of the epidemiology and distribution of diseases is an important aid for control and prevention. The aim of our study was to identify the effects of environmental and climatic factors on distribution patterns of STHs and to develop a risk map for STH infections under current environmental and climate regimes in Thailand. Geographical information systems (GIS), remote sensing, and Maximum Entropy (MaxEnt) algorithm software were used to determine the significant factors and to create predictive risk maps for STH infections in Thailand. The disease data from Thailand covered the years from 1969 to 2014, while environmental and climatic data were compiled from the Worldclim database, MODIS satellite imagery, Soilgrids and ISCGM. The models predicted that STHs occur mainly in southern Thailand. Mean annual precipitation was the factor most affecting the current distribution of A. lumbricoides, T. trichiura, and S. stercoralis. Land cover class was the main predictor for distribution of S. stercoralis and important for hookworms. Altitude was the dominant factor affecting the distribution of hookworms, and mean temperature of the wettest quarter was significantly associated with A. lumbricoides distribution. A predicted distribution map of STHs to identify environmental risk factors in Thailand is presented. This work provides a model for use in STH monitoring and health planning not only in Thailand but also in other countries with similar disease conditions.

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