Impact of precipitation on the prevalence of schistosomiasis mekongi in Lao PDR: Structural equation modelling using Earth observation satellite data.

Increasing attention is being given to the effect of climate change on schistosomiasis, but the impact is currently unknown. As the intermediate snail host (Neotricula aperta) of Schistosoma mekongi inhabits the Mekong River, it is thought that environmental factors affecting the area of water will have an impact on the occurrence of schistosomiasis mekongi. The aim of the present study was to assess the impact of precipitation on the prevalence of human schistosomiasis mekongi using epidemiological data and Earth observation satellite data in Khong district, Champasak province, Lao PDR. Structural equation modelling (SEM) using epidemiological data and Earth observation satellite data was conducted to determine the factors associated with the number of schistosomiasis mekongi patients. As a result, SEM identified 3 significant factors independently associated with schistosomiasis mekongi: (1) a negative association with mass drug administration (MDA); (2) negative association with total precipitation per year; and (3) positive association with precipitation during the dry season. Precisely, regardless of MDA, the increase in total yearly precipitation was suggested to decrease the number of schistosomiasis patients, whereas an increase in precipitation in the dry season increased the number of schistosomiasis patients. This is probably because when total precipitation increases, the water level of the Mekong River rises, thus decreasing the density of infected larvae, cercaria, in the water, and the frequency of humans entering the river would also decrease. In contrast, when precipitation in the dry season is higher, the water level of the Mekong River also rises, which expands the snail habitant, and thus water contact between humans and the snails would also increase. The present study results suggest that increasing precipitation would impact the prevalence of schistosomiasis both positively and negatively, and precipitation should also be considered in the policy to eliminate schistosomiasis mekongi in Lao PDR.

Detection of Schistosoma mekongi DNA in Human Stool and Intermediate Host Snail Neotricula aperta via Loop-Mediated Isothermal Amplification Assay in Lao PDR.

Schistosomiasis mekongi infection represents a public health concern in Laos and Cambodia. While both countries have made significant progress in disease control over the past few decades, eradication has not yet been achieved. Recently, several studies reported the application of loop-mediated isothermal amplification (LAMP) for detecting Schistosoma DNA in low-transmission settings. The objective of this study was to develop a LAMP assay for Schistosoma mekongi using a simple DNA extraction method. In particular, we evaluated the utility of the LAMP assay for detecting S. mekongi DNA in human stool and snail samples in endemic areas in Laos. We then used the LAMP assay results to develop a risk map for monitoring schistosomiasis mekongi and preventing epidemics. A total of 272 stool samples were collected from villagers on Khon Island in the southern part of Laos in 2016. DNA for LAMP assays was extracted via the hot-alkaline method. Following the Kato-Katz method, we determined that 0.4% (1/272) of the stool samples were positive for S. mekongi eggs, as opposed to 2.9% (8/272) for S. mekongi DNA based on the LAMP assays. Snail samples (n = 11,762) were annually collected along the riverside of Khon Island from 2016 to 2018. DNA was extracted from pooled snails as per the hot-alkaline method. The LAMP assay indicated that the prevalence of S. mekongi in snails was 0.26% in 2016, 0.08% in 2017, and less than 0.03% in 2018. Based on the LAMP assay results, a risk map for schistosomiasis with kernel density estimation was created, and the distribution of positive individuals and snails was consistent. In a subsequent survey of residents, schistosomiasis prevalence among villagers with latrines at home was lower than that among villagers without latrines. This is the first study to develop and evaluate a LAMP assay for S. mekongi detection in stools and snails. Our findings indicate that the LAMP assay is an effective method for monitoring pathogen prevalence and creating risk maps for schistosomiasis.

Spatiotemporal dengue fever hotspots associated with climatic factors in Taiwan including outbreak predictions based on machine-learning.

Early warning systems (EWS) have been proposed as a measure for controlling and preventing dengue fever outbreaks in countries where this infection is endemic. A vaccine is not available and has yet to reach the market due to the economic burden of development, introduction and safety concerns. Understanding how dengue spreads and identifying the risk factors will facilitate the development of a dengue EWS, for which a climate-based model is still needed. An analysis was conducted to examine emerging spatiotemporal hotspots of dengue fever at the township level in Taiwan, associated with climatic factors obtained from remotely sensed data in order to identify the risk factors. Machinelearning was applied to support the search for factors with a spatiotemporal correlation with dengue fever outbreaks. Three dengue fever hotspot categories were found in southwest Taiwan and shown to be spatiotemporally associated with five kinds of sea surface temperatures. Machine-learning, based on the deep AlexNet model trained by transfer learning, yielded an accuracy of 100% on an 8-fold cross-validation test dataset of longitudetime sea surface temperature images.