Identifying Determinants of Oncomelania hupensis Habitats and Assessing the Effects of Environmental Control Strategies in the Plain Regions with the Waterway Network of China at the Microscale

Abstract

This study aims to identify the landscape ecological determinants related to Oncomelania hupensis distribution, map the potential high risk of O. hupensis habitats at the microscale, and assess the effects of two environmental control strategies. Sampling was performed on 242 snail sites and 726 non-snail sites throughout Qianjiang City, Hubei Province, China. An integrated approach of landscape pattern analysis coupled with multiple logistic regression modeling was applied to investigate the effects of environmental factors on snail habitats. The risk probability of snail habitats positively correlated with patch fractal dimension (FD), paddy farm land proportion, and wetness index but inversely correlated with categorized normalized difference vegetation index (NDVI) and elevation. These findings indicate that FD can identify irregular features (e.g., irrigation ditches) in plain regions and that a moderate NDVI increases the microscale risk probability. Basing on the observed determinants, we predicted a map showing high-risk areas of snail habitats and simulated the effects of conduit hardening and paddy farming land rotation to dry farming land. The two approaches were confirmed effective for snail control. These findings provide an empirical basis for health professionals in local schistosomiasis control stations to identify priority areas and promising environmental control strategies for snail control and prevention.

Genetic Evidence of Contemporary Dispersal of the Intermediate Snail Host of Schistosoma japonicum: Movement of an NTD Host Is Facilitated by Land Use and Landscape Connectivity

“…Other models considered the role of stream movement (stream only, stream velocity, streams and channels), soil wetness and water, and land use features in determining intermediate host dispersal (Table 1). Landsat and IKONOS imagery was mosaicked using ENVI (ITT Visual Information Solutions, Boulder, Colorado, USA) and land cover was classified using a maximum likelihood supervised classification approach with five classes—surface water, agriculture, forest, barren, and built, in order of least to greatest resistance to host movement—following previous methods [39, 40]. …”

The influence of natural factors on the spatio-temporal distribution of Oncomelania hupensis

“…Compared with the eastern region relatively far from the lake, the lake region is crisscrossed by irrigation canals and ditches, and resident production and living activities are frequent, making the schistosomiasis prevalence in the region more serious, which is why it has attracted increasing attention from relevant departments. Therefore, snail density changes may objectively be caused by some local environmental differences, such as channel type; weed density and man-made factors, including agricultural and pastoral activities; snail control projects; and so on (Qiu et al, 2014;Shan et al, 2014). Of course, the specific mechanisms underlying these changes require more research and validation.…”

“…There may be two reasons for these results. First, these factors are linked, influence each other, and, together, constitute the breeding environment of the snails (Remais et al, 2009;Qiu et al, 2014), which means that a correlation analysis based on a single factor cannot fully reflect their influence on snail distribution. Second, snail breeding and living environments have relatively strict requirements with respect to environmental factors, such as temperature, humidity, and light intensity, as extremes of these parameters are not suitable for snail survival.…”

Quantitative Impacts of Climate Change and Human Activities on Water-Surface Area Variations from the 1990s to 2013 in Honghu Lake, China

“…In addition, some measures, including paddy rotation to dry land and conduit hardening, have been performed to control the spread of snails [44,45]. Thus, the water demands for farmland have decreased.…”