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A community analysis approach to parasite transmission in multi-host systems: Assemblages of small mammal prey and in an urban area in North America. | LitMetric

A community analysis approach to parasite transmission in multi-host systems: Assemblages of small mammal prey and in an urban area in North America.

Int J Parasitol Parasites Wildl

Department of Ecosystem and Public Health, Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, Canada.

Published: August 2019

Background: () is a parasite with a complex life cycle whose transmission involves a predator-prey interaction. Accidental ingestion of eggs by humans may cause alveolar echinococcosis, a potentially fatal disease. Although previous research suggested that the composition of the assemblage of prey species may play a key role in the transmission, the relation between presence and the prey assemblages has never been analyzed. Herein, we propose a community analysis approach, based on assemblage similarity statistics, clustering, non-metric dimensional scaling and GLM modelling to analyze the relationships between small mammal assemblages, environmental variables, and the prevalence of in intermediate and definitive hosts in an urban area.

Results: In our study areas within the City of Calgary, Alberta (Canada), we identified three main small mammal assemblages associated with different prevalence of , characterized by a different proportion of species known to be good intermediate hosts for . As expected, assemblages with higher proportion of species susceptible to were observed with higher prevalence of parasite, whereas the total abundance of small mammals was not a predictor of transmission likely due to dilution effect. Furthermore, these assemblages were also predicted by simple environmental proxies such as land cover and terrain.

Conclusions: Our results indicated that the use of a community analysis approach allows for robust characterization of these complex and multivariate relationships, and may offer a promising tool for further understanding of parasite epidemiology in complex multi-host systems. In addition, this analysis indicates that it is possible to predict potential foci of disease risk within urban areas using environmental data commonly available to city planners and land managers.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449735PMC
http://dx.doi.org/10.1016/j.ijppaw.2019.03.012DOI Listing

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