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Spatiotemporal analysis of Cryptosporidium species/genotypes and relationships with other zoonotic pathogens in surface water from mixed-use watersheds

Wilkes, G., Ruecker, N.J., Neumann, N.F., Gannon, V.P.J., Jokinen, C., Sunohara, M., Topp, E., Pintar, K.D.M., Edge, T.A., Lapen, D.R. (2013). Spatiotemporal analysis of Cryptosporidium species/genotypes and relationships with other zoonotic pathogens in surface water from mixed-use watersheds, 79(2), 434-448. http://dx.doi.org/10.1128/AEM.01924-12

Abstract

Nearly 690 raw surface water samples were collected during a 6-year period from multiple watersheds in the South Nation River basin, Ontario, Canada. Cryptosporidium oocysts in water samples were enumerated, sequenced, and genotyped by detailed phylogenetic analysis. The resulting species and genotypes were assigned to broad, known host and human infection risk classes. Wildlife/unknown, livestock, avian, and human host classes occurred in 21, 13, 3, and<1% of sampled surface waters, respectively. Cryptosporidium andersoni was the most commonly detected livestock species, while muskrat I and II genotypes were the most dominant wildlife genotypes. The presence of Giardia spp., Salmonella spp., Campylobacter spp., and Escherichia coli O157:H7 was evaluated in all water samples. The greatest significant odds ratios (odds of pathogen presence when host class is present/odds of pathogen presence when host class is absent) for Giardia spp., Campylobacter spp., and Salmonella spp. in water were associated, respectively, with livestock (odds ratio of 3.1), avian (4.3), and livestock (9.3) host classes. Classification and regression tree analyses (CART) were used to group generalized host and human infection risk classes on the basis of a broad range of environmental and land use variables while tracking cooccurrence of zoonotic pathogens in these groupings. The occurrence of livestock- associated Cryptosporidium was most strongly related to agricultural water pollution in the fall (conditions also associated with elevated odds ratios of other zoonotic pathogens occurring in water in relation to all sampling conditions), whereas wildlife/unknown sources of Cryptosporidium were geospatially associated with smaller watercourses where urban/rural development was relatively lower. Conditions that support wildlife may not necessarily increase overall human infection risks associated with Cryptosporidium since most Cryptosporidium genotypes classed as wildlife in this study (e.g., muskrat I and II genotype) do not pose significant infection risks to humans. Consequently, from a human health perspective, land use practices in agricultural watersheds that create opportunities for wildlife to flourish should not be rejected solely on the basis of their potential to increase relative proportions of wildlife fecal contamination in surface water. The present study suggests that mitigating livestock fecal pollution in surface water in this region would likely reduce human infection risks associated with Cryptosporidium and other zoonotic pathogens. © 2013, American Society for Microbiology.

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