ArticleInternational journal of health geographics2010
Temporal and spatial dynamics of Cryptosporidium parvum infection on dairy farms in the New York City Watershed: a cluster analysis based on crude and Bayesian risk estimates.
Article in International journal of health geographics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Prevalence and associated risk factors of Cryptosporidium infection in calves and hospitalized humans in Libo Kemkem, North Western Ethiopia.Veterinary medicine and science · 2024Article
- Investigation of multi-scale spatio-temporal pattern of oldest-old clusters in China on the basis of spatial scan statistics.PloS one · 2019Article
- Spatiotemporal patterns of clinical bovine dermatophilosis in Zimbabwe 1995-2014.The Onderstepoort journal of veterinary research · 2017Article
- Spatial analysis of Schistosomiasis in Hubei Province, China: a GIS-based analysis of Schistosomiasis from 2009 to 2013.PloS one · 2015Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCryptosporidium parvum is one of the most important biological contaminants in drinking water that produces life threatening infection in people with compromised immune systems. Dairy calves are thought to be the primary source of C. parvum contamination in watersheds. Understanding the spatial and temporal variation in the risk of C. parvum infection in dairy cattle is essential for designing cost-effective watershed management strategies to protect drinking water sources. Crude and Bayesian seasonal risk estimates for Cryptosporidium in dairy calves were used to investigate the spatio-temporal dynamics of C. parvum infection on dairy farms in the New York City watershed.
resultsBoth global (Global Moran's I) and specific (SaTScan) cluster analysis methods revealed a significant (p < 0.05) elliptical spatial cluster in the winter with a relative risk of 5.8, but not in other seasons. There was a two-fold increase in the risk of C. parvum infection in all herds in the summer (p = 0.002), compared to the rest of the year. Bayesian estimates did not show significant spatial autocorrelation in any season.
conclusionsAlthough we were not able to identify seasonal clusters using Bayesian approach, crude estimates highlighted both temporal and spatial clusters of C. parvum infection in dairy herds in a major watershed. We recommend that further studies focus on the factors that may lead to the presence of C. parvum clusters within the watershed, so that monitoring and prevention practices such as stream monitoring, riparian buffers, fencing and manure management can be prioritized and improved, to protect drinking water supplies and public health.
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