Abstract

Schistosomiasis is one of the most prevalent parasitic diseases impacting human health in the tropics and sub-tropics. The geographic distribution of Schistosoma mansoni, the most widespread species, includes areas in Africa, the Middle East, South America and the Caribbean. Snails of the genus Biomphalaria act as intermediate host for S. mansoni. Biomphalaria straminea is not indigenous in China but was accidentally introduced to Hong Kong from South America and has spread to other habitats in the southern parts of the country. This species is known for its great dispersal capacity that highlights the importance of the snail as a potential host for S. mansoni in China. In this connection, although no such infection has been recorded in the field so far, the continuous expansion of China’s projects in endemic areas of Africa and import of the infection via returning workers or visitors deserve attention. The purpose of this study was to map and predict the spatial distribution of B. straminea in China. Snail occurrence data were assembled and investigated using MaxEnt software, along with climatic and environmental variables to produce a predictive risk map. Of the environmental variables tested, the precipitation of warmest quarter was the most contribution factor for snail’s spatial distribution. Risk areas were found in southeastern China and it is expected that they will guide policies and control programmes to potential areas area of snail abundance and used for spatial targeting of control interventions for this invasive species.

Details

Title
Predicting the spatial distribution of Biomphalaria straminea, a potential intermediate host for Schistosoma mansoni, in China
Author
Habib, Mohamed R; Yun-Hai Guo; Lv, Shan; Wen-Biao Gu; Xiao-Heng, Li; Xiao-Nong Zhou
Section
Original Articles
Publication year
2016
Publication date
Nov 2016
Publisher
PAGEPress Publications
ISSN
18271987
e-ISSN
19707096
Source type
Scholarly Journal
Language of publication
English; Italian
ProQuest document ID
2417186303
Copyright
© 2016. This work is published under http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.