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Censored Regression Modeling To Predict Virus Inactivation in Wastewaters

Overview of attention for article published in Environmental Science & Technology, January 2017
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Article details
Title
Censored Regression Modeling To Predict Virus Inactivation in Wastewaters
Published in
Environmental Science & Technology, January 2017
DOI 10.1021/acs.est.6b05190
Pubmed ID
Authors
Abstract

Among the many uncertainties presented by poorly studied pathogens is possible transmission via human faecal material or wastewaters. Such worries were a documented concern during the 2013 Ebola outbreak in West Africa. Using published experimental data on virus inactivation rates in wastewater and similar matrices, we extracted data to construct a model predicting the T90 (1 x log10 inactivation measured in seconds) of a virus. Extracted data were: RNA or DNA genome, enveloped or not, primary transmission pathway, temperature, pH, light levels and matrix. From the primary details, we further determined matrix level of contamination, genus and taxonomic family. Prior to model construction, three records were separated for verification. A censored normal regression model provided the best fit model, which predicted T90 from DNA or RNA structure, enveloped status, whether primary transmission pathway was faecal-oral, temperature and whether contamination was low, medium or high. Model residuals and predicted values were evaluated against observed values. Mean values of model predictions were compared to independent data, and considering 95% confidence ranges (which could be quite large). A relatively simple model can predict virus inactivation rates from virus and matrix attributes, providing valuable input when formulating risk management strategies for little studied pathogens.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 10 20%
Student > Ph. D. Student 9 18%
Researcher 8 16%
Other 3 6%
Professor 3 6%
Other 6 12%
Unknown 10 20%
Readers by discipline
Readers by discipline Count As %
Environmental Science 13 27%
Engineering 9 18%
Agricultural and Biological Sciences 3 6%
Medicine and Dentistry 3 6%
Chemistry 2 4%
Other 8 16%
Unknown 11 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 05 January 2017.
All research outputs
#18,879,873
of 27,376,552 outputs
Outputs from Environmental Science & Technology
#18,121
of 22,162 outputs
Outputs of similar age
#274,586
of 426,180 outputs
Outputs of similar age from Environmental Science & Technology
#209
of 264 outputs
Altmetric has tracked 27,376,552 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,162 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.9. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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 426,180 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 264 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.