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COVID-19 case prediction via wastewater surveillance in a low-prevalence urban community: a modeling approach

Overview of attention for article published in Journal of Water & Health, February 2022
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (71st percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
9 X users
facebook
1 Facebook page

Citations

dimensions_citation
25 Dimensions

Readers on

mendeley
44 Mendeley
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Title
COVID-19 case prediction via wastewater surveillance in a low-prevalence urban community: a modeling approach
Published in
Journal of Water & Health, February 2022
DOI 10.2166/wh.2022.183
Pubmed ID
Authors

Yifan Zhu, Wakana Oishi, Chikako Maruo, Sewwandi Bandara, Mu Lin, Mayuko Saito, Masaaki Kitajima, Daisuke Sano

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 14%
Student > Master 5 11%
Professor > Associate Professor 3 7%
Student > Doctoral Student 2 5%
Researcher 2 5%
Other 5 11%
Unknown 21 48%
Readers by discipline Count As %
Engineering 6 14%
Environmental Science 3 7%
Agricultural and Biological Sciences 3 7%
Biochemistry, Genetics and Molecular Biology 2 5%
Medicine and Dentistry 2 5%
Other 4 9%
Unknown 24 55%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 11 November 2022.
All research outputs
#6,759,465
of 25,392,582 outputs
Outputs from Journal of Water & Health
#187
of 723 outputs
Outputs of similar age
#144,640
of 519,272 outputs
Outputs of similar age from Journal of Water & Health
#5
of 25 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 723 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. This one has gotten more attention than average, scoring higher than 73% 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 519,272 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.