Bayesian spatio-temporal analysis of dengue transmission in Lao PDR.

Dengue, a zoonotic viral disease transmitted by Aedes mosquitoes, poses a significant public health concern throughout the Lao People's Democratic Republic (Lao PDR). This study aimed to describe spatial-temporal patterns and quantify the effects of environmental and climate variables on dengue transmission at the district level. The dengue data from 2015 to 2020 across 148 districts of Lao PDR were obtained from the Lao PDR National Center for Laboratory and Epidemiology (NCLE).

Opisthorchis viverrini and Strongyloides stercoralis mono- and co-infections: Bayesian geostatistical analysis in an endemic area, Thailand.

Parasitic infections caused by Opisthorchis viverrini and Strongyloides stercoralis remain a major public health threat in the Greater Mekong Sub-region. An understanding of climate and other environmental influences on the geographical distribution and emergence of parasitic diseases is a crucial step to guide targeted control and prevention programs. A parasitological survey was conducted from 2008 to 2013 and included 12,554 individuals (age between 20 and 60 years) from 142 villages in five districts in Khon Kaen Province, Thailand.

Ecological Niche Model based on Maximum Entropy for mapping distribution of Bithynia siamensis goniomphalos, first intermediate host snail of Opisthorchis viverrini in Thailand.

The snail Bithynia siamensis goniomphalos acts as first intermediate host of the liver fluke, Opisthorchis viverrini, which causes opisthorchiasis in humans. In this study, we used a geographic information system (GIS), remote sensing (RS) and software using the maximum entropy (MaxEnt) algorithm to predict the distribution of B. s.

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.

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.