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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Modeling and Statistical Analysis of the Spatio-Temporal Patterns of Seasonal Influenza in Israel
|
|---|---|
| Published in |
PLOS ONE, October 2012
|
| DOI | 10.1371/journal.pone.0045107 |
| Pubmed ID | |
| Authors |
Amit Huppert, Oren Barnea, Guy Katriel, Rami Yaari, Uri Roll, Lewi Stone |
| Abstract |
Seasonal influenza outbreaks are a serious burden for public health worldwide and cause morbidity to millions of people each year. In the temperate zone influenza is predominantly seasonal, with epidemics occurring every winter, but the severity of the outbreaks vary substantially between years. In this study we used a highly detailed database, which gave us both temporal and spatial information of influenza dynamics in Israel in the years 1998-2009. We use a discrete-time stochastic epidemic SIR model to find estimates and credible confidence intervals of key epidemiological parameters. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Ireland | 1 | 1% |
| Israel | 1 | 1% |
| United Kingdom | 1 | 1% |
| Romania | 1 | 1% |
| Japan | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 76 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 20 | 24% |
| Researcher | 16 | 20% |
| Student > Master | 11 | 13% |
| Professor > Associate Professor | 5 | 6% |
| Professor | 5 | 6% |
| Other | 15 | 18% |
| Unknown | 10 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 14 | 17% |
| Medicine and Dentistry | 14 | 17% |
| Mathematics | 12 | 15% |
| Computer Science | 6 | 7% |
| Environmental Science | 4 | 5% |
| Other | 15 | 18% |
| Unknown | 17 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 07 July 2023.
All research outputs
#2,914,643
of 24,034,335 outputs
Outputs from PLOS ONE
#36,800
of 206,253 outputs
Outputs of similar age
#20,045
of 175,546 outputs
Outputs of similar age from PLOS ONE
#659
of 4,667 outputs
Altmetric has tracked 24,034,335 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 206,253 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.6. This one has done well, scoring higher than 81% 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 175,546 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 88% of its contemporaries.
We're also able to compare this research output to 4,667 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.