MaxEnt modeling of soil-transmitted helminth infection distributions in Thailand.

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.

Modeling impacts of climate change on the potential distribution of the carcinogenic liver fluke, Opisthorchis viverrini, in Thailand.

Global climate change is now regarded as imposing a significant threat of enhancing transmission of parasitic diseases. Maximum entropy species distribution modeling (MaxEnt) was used to explore how projected climate change could affect the potential distribution of the carcinogenic liver fluke, Opisthorchis viverrini, in Thailand. A range of climate variables was used: the Hadley Global Environment Model 2-Earth System (HadGEM2-ES) climate change model and also the IPCC scenarios A2a for 2050 and 2070. Occurrence data from surveys conducted in 2009 and 2014 were obtained from the Department of Disease Control, Ministry of Public Health, Thailand. The MaxEnt model performed better than random for O. viverrini with training AUC values greater than 0.8 under current and future climatic conditions. The current distribution of O. viverrini is significantly affected by precipitation and minimum temperature. According to current conditions, parts of Thailand climatically suitable for O. viverrini are mostly in the northeast and north, but the parasite is largely absent from southern Thailand. Under future climate change scenarios, the distribution of O. viverrini in 2050 should be significantly affected by precipitation, maximum temperature, and mean temperature of the wettest quarter, whereas in 2070, significant factors are likely to be precipitation during the coldest quarter, maximum, and minimum temperatures. Maps of predicted future distribution revealed a drastic decrease in presence of O. viverrini in the northeast region. The information gained from this study should be a useful reference for implementing long-term prevention and control strategies for O. viverrini in Thailand.