High-resolution remote sensing-based spatial modeling for the prediction of potential risk areas of schistosomiasis in the Dongting Lake area, China.

Acta Trop

National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, National Center for Tropical Diseases Research, Key Laboratory of Parasite and Vector Biology, National Health Commission of China, WHO Collaborating Center for Tropical Diseases, Shanghai, 200025, People's Republic of China. Electronic address:

Published: October 2019

AI Article Synopsis

  • The study investigates the relationship between the geographical distribution of snails (intermediate hosts of schistosomiasis) and environmental factors in endemic areas along the Yangtze River in China.
  • The research utilizes high-resolution remote sensing to analyze environmental variables like NDVI, soil moisture, and proximity to water bodies that influence snail populations.
  • Findings suggest that this remote sensing approach enhances the accuracy of predicting schistosomiasis risk areas, thus supporting national efforts in schistosomiasis control.

Article Abstract

The geographical distribution of snail (i.e., the intermediate host of schistosomiasis) is consistent with that of endemic areas. The suitable snail habitus requires necessary environmental conditions for snail population. The high-resolution remote sensing provides an important tool for the spatio-temporal analysis of disease monitoring and prediction. This study conducted a typical schistosomiasis epidemic area in the marshland and lake regions along the Yangtze River, Yueyang City, Hunan Province of China. And three types of environmental factors, i.e., NDVI, soil moisture, and shortest distance to water body, associated with the geographical distribution of snail population, were extracted from the high-resolution remoting sensing data. The predicted distribution of snail habitus from the high-resolution environmental factors were compared with the data of annual program of snail survey. The results have shown that the application of high-resolution remote sensing can improve the accuracy of the modeled and predicted the potential risk areas of schistosomiasis, and may become an important tool for the ongoing national schistosomiasis control program.

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Source
http://dx.doi.org/10.1016/j.actatropica.2019.105077DOI Listing

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