scholarly journals Bayesian maximum entropy-based prediction of the spatiotemporal risk of schistosomiasis in Anhui Province, China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Fuju Wang ◽  
Xin Liu ◽  
Robert Bergquist ◽  
Xiao Lv ◽  
Yang Liu ◽  
...  
Keyword(s):  
Maximum Entropy ◽  
Yangtze River ◽  
Anhui Province ◽  
Bayesian Maximum Entropy ◽  
Spatiotemporal Pattern ◽  
The Yangtze River ◽  
Spatiotemporal Interpolation ◽  
Absolute Residual ◽  
Wide Range ◽  
Spatiotemporal Risk

Abstract Background “Schistosomiasis” is a highly recurrent parasitic disease that affects a wide range of areas and a large number of people worldwide. In China, schistosomiasis has seriously affected the life and safety of the people and restricted the economic development. Schistosomiasis is mainly distributed along the Yangtze River and in southern China. Anhui Province is located in the Yangtze River Basin of China, with dense water system, frequent floods and widespread distribution of Oncomelania hupensis that is the only intermediate host of schistosomiasis, a large number of cattle, sheep and other livestock, which makes it difficult to control schistosomiasis. It is of great significance to monitor and analyze spatiotemporal risk of schistosomiasis in Anhui Province, China. We compared and analyzed the optimal spatiotemporal interpolation model based on the data of schistosomiasis in Anhui Province, China and the spatiotemporal pattern of schistosomiasis risk was analyzed. Methods In this study, the root-mean-square-error (RMSE) and absolute residual (AR) indicators were used to compare the accuracy of Bayesian maximum entropy (BME), spatiotemporal Kriging (STKriging) and geographical and temporal weighted regression (GTWR) models for predicting the spatiotemporal risk of schistosomiasis in Anhui Province, China. Results The results showed that (1) daytime land surface temperature, mean minimum temperature, normalized difference vegetation index, soil moisture, soil bulk density and urbanization were significant factors affecting the risk of schistosomiasis; (2) the spatiotemporal distribution trends of schistosomiasis predicted by the three methods were basically consistent with the actual trends, but the prediction accuracy of BME was higher than that of STKriging and GTWR, indicating that BME predicted the prevalence of schistosomiasis more accurately; and (3) schistosomiasis in Anhui Province had a spatial autocorrelation within 20 km and a temporal correlation within 10 years when applying the optimal model BME. Conclusions This study suggests that BME exhibited the highest interpolation accuracy among the three spatiotemporal interpolation methods, which could enhance the risk prediction model of infectious diseases thereby providing scientific support for government decision making.

scholarly journals Spatiotemporal Pattern of Pine Wilt Disease in the Yangtze River Basin

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 731
Author(s):  
Zhuoqing Hao ◽  
Jixia Huang ◽  
Yantao Zhou ◽  
Guofei Fang
Keyword(s):  
River Basin ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Pine Wilt Disease ◽  
Wilt Disease ◽  
Spatiotemporal Pattern ◽  
Pinewood Nematode ◽  
The Yangtze River ◽  
Pine Wilt ◽  
The Yangtze River Basin

The Yangtze River Basin is among the river basins with the strongest strategic support and developmental power in China. As an invasive species, the pinewood nematode (PWN) Bursaphelenchus xylophilus has introduced a serious obstacle to the high-quality development of the economic and ecological synchronization of the Yangtze River Basin. This study analyses the occurrence and spread of pine wilt disease (PWD) with the aim of effectively managing and controlling the spread of PWD in the Yangtze River Basin. In this study, statistical data of PWD-affected areas in the Yangtze River Basin are used to analyse the occurrence and spread of PWD in the study area using spatiotemporal visualization analysis and spatiotemporal scanning statistics technology. From 2000 to 2018, PWD in the study area showed an “increasing-decreasing-increasing” trend, and PWD increased explosively in 2018. The spatial spread of PWD showed a “jumping propagation-multi-point outbreak-point to surface spread” pattern, moving west along the river. Important clusters were concentrated in the Jiangsu-Zhejiang area from 2000 to 2015, forming a cluster including Jiangsu and Zhejiang. Then, from 2015–2018, important clusters were concentrated in Chongqing. According to the spatiotemporal scanning results, PWD showed high aggregation in the four regions of Zhejiang, Chongqing, Hubei, and Jiangxi from 2000 to 2018. In the future, management systems for the prevention and treatment of PWD, including ecological restoration programs, will require more attention.

Integrated biogeography and assembly process of planktonic and sedimentary bacterial communities in the Yangtze River

2020 ◽  
Author(s):  
Tang Liu ◽  
Jiawen Wang ◽  
Shufeng Liu ◽  
Qian Chen ◽  
Chunmiao Zheng ◽  
...  
Keyword(s):  
Bacterial Communities ◽  
Yangtze River ◽  
Selection Process ◽  
Anthropogenic Impacts ◽  
Spatiotemporal Pattern ◽  
Assembly Process ◽  
The Yangtze River ◽  
Species Sorting ◽  
Biogeographic Patterns ◽  
Water And Sediment

<p>Bacterial communities are essential to the biogeochemical cycle in riverine ecosystems. However, the integrated biogeography and assembly process of planktonic and sedimentary bacterial communities in large rivers is still poorly understood. Here, the study provided the spatiotemporal pattern of bacterial communities in the Yangtze River of 4300 km continuum, which is the largest river in Asia. We found that the taxa in sediments are the main contributors to the bacterial diversity of the river ecosystem since sediments sub-group took 98.8% of the total 38, 904 Operational Taxonomic Units (OTUs) observed in 280 samples. Seasonal differences in bacterial communities were statistically significant in water, whereas bacterial communities in both water and sediment were geographically clustered according to five types of landforms: mountain, foothill, basin, foothill-mountain, and plain. Interestingly, the presence of two huge dams resulted in a drastic fall of bacterial taxa in sediment immediately downstream due to severe riverbed scouring. The integrity of the biogeography was satisfactorily interpreted by the combination of neutral and species sorting perspectives in meta-community theory for bacterial communities in flowing water and sediment. Although deterministic process had dominant influence on assembly processes in water and sediment communities, homogeneous selection was the main contributor in water, while combination of homogeneous selection and variable selection contributed selection process in sediment. In addition, homogenizing dispersal played more important role in community assembly process in sediment than water. Our study fills a gap in understanding of biogeography and assembly process of bacterial communities in one of the world’s largest river and highlights the importance of both planktonic and sedimentary communities to the integrity of bacterial biogeographic patterns in a river subject to varying natural and anthropogenic impacts.</p>

Spatiotemporal pattern analysis of schistosomiasis based on village level in the transmission control stage in lake and marshland areas in China

Parasitology ◽  
2019 ◽  
Vol 147 (2) ◽  
pp. 199-212
Author(s):  
Yanyan Chen ◽  
Jianbing Liu ◽  
Ying Xiao ◽  
Chenhui Zhong ◽  
Fenghua Wei ◽  
...  
Keyword(s):  
Spatial Autocorrelation ◽  
Yangtze River ◽  
Hubei Province ◽  
Control Measures ◽  
Spatiotemporal Pattern ◽  
The Yangtze River ◽  
Jianghan Plain ◽  
Cluster Analyses ◽  
Village Level ◽  
The Village

AbstractHubei Province is one of the endemic regions with severe schistosomiasis in China. To eliminate schistosomiasis in lake and marshland regions, this study detected hotspots of schistosomiasis cases both spatially and spatiotemporally on the basis of spatial autocorrelation; clustering and outlier, purely spatial and spatiotemporal cluster analyses at the village level from 2013 to 2017 in Hubei Province. The number of cases confirmed positive by an immunodiagnostic test and etiological diagnosis and advanced schistosomiasis cases dramatically declined during the study period. Significant global spatial autocorrelation of schistosomiasis patients was found at the village level in the whole province in 5 years. Clustering and outlier analysis showed that most HH villages were mainly concentrated along the Yangtze River, especially in Jianghan Plain. Spatial and spatiotemporal cluster analyses showed that significant clusters of the schistosomiasis cases were detected at the village level. In general, space and spatiotemporal clustering of schistosomiasis cases at the village level demonstrated a downward trend from 2013 from 2017 in Hubei Province. High-risk regions included Jianghan Plain along the middle reach of Yangtze River and Yangxin County in the lower reaches of the Yangtze River in Hubei Province. To eliminate schistosomiasis, precise control and management of schistosomiasis cases should be strictly implemented. Moreover, comprehensive prevention and control measures should be continuously strengthened in these regions.

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