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Development of a hierarchical model for predicting microbiological contamination of private groundwater supplies in a geologically heterogeneous region

Overview of attention for article published in Environmental Pollution, February 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

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blogs
1 blog
policy
1 policy source
twitter
6 X users

Citations

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30 Dimensions

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78 Mendeley
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Title
Development of a hierarchical model for predicting microbiological contamination of private groundwater supplies in a geologically heterogeneous region
Published in
Environmental Pollution, February 2018
DOI 10.1016/j.envpol.2018.02.052
Pubmed ID
Authors

Jean O'Dwyer, Paul D. Hynds, Kenneth A. Byrne, Michael P. Ryan, Catherine C. Adley

Abstract

Private groundwater sources in the Republic of Ireland provide drinking water to an estimated 750,000 people or 16% of the national population. Consumers of untreated groundwater are at increased risk of infection from pathogenic microorganisms. However, given the volume of private wells in operation, remediation or even quantification of public risk is both costly and time consuming. In this study, a hierarchical logistic regression model was developed to 'predict' contamination with E. coli based on the results of groundwater quality analyses of private wells (n = 132) during the period of September 2011 to November 2012. Assessment of potential microbial contamination risk factors were categorised into three groups: Intrinsic (environmental factors), Specific (local features) and Infrastructural (groundwater source characteristics) which included a total of 15 variables. Overall, 51.4% of wells tested positive for E. coli during the study period with univariate analysis indicating that 11 of the 15 assessed risk factors, including local bedrock type, local subsoil type, septic tank reliance, 5 day antecedent precipitation and temperature, along with well type and depth, were all significantly associated with E. coli presence (p < 0.05). Hierarchical logistic regression was used to develop a private well susceptibility model with the final model containing 8 of the 11 associated variables. The model was shown to be highly efficient; correctly classifying the presence of E. coli in 94.2% of cases, and the absence of E. coli in 84.7% of cases. Model validation was performed using an external data set (n = 32) and it was shown that the model has promising accuracy with 90% of positive E. coli cases correctly predicted. The developed model represents a risk assessment and management tool that may be used to develop effective water-quality management strategies to minimize public health risks both in Ireland and abroad.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 78 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 14%
Student > Bachelor 10 13%
Student > Master 8 10%
Researcher 7 9%
Student > Doctoral Student 6 8%
Other 10 13%
Unknown 26 33%
Readers by discipline Count As %
Environmental Science 12 15%
Earth and Planetary Sciences 7 9%
Agricultural and Biological Sciences 6 8%
Engineering 6 8%
Chemical Engineering 4 5%
Other 10 13%
Unknown 33 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 January 2021.
All research outputs
#2,351,166
of 25,818,700 outputs
Outputs from Environmental Pollution
#941
of 13,722 outputs
Outputs of similar age
#48,084
of 345,312 outputs
Outputs of similar age from Environmental Pollution
#16
of 177 outputs
Altmetric has tracked 25,818,700 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,722 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 345,312 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 177 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.