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X Demographics
Mendeley readers
Attention Score in Context
| Title |
FluTE, a Publicly Available Stochastic Influenza Epidemic Simulation Model
|
|---|---|
| Published in |
PLoS Computational Biology, January 2010
|
| DOI | 10.1371/journal.pcbi.1000656 |
| Pubmed ID | |
| Authors |
Dennis L. Chao, M. Elizabeth Halloran, Valerie J. Obenchain, Ira M. Longini |
| Abstract |
Mathematical and computer models of epidemics have contributed to our understanding of the spread of infectious disease and the measures needed to contain or mitigate them. To help prepare for future influenza seasonal epidemics or pandemics, we developed a new stochastic model of the spread of influenza across a large population. Individuals in this model have realistic social contact networks, and transmission and infections are based on the current state of knowledge of the natural history of influenza. The model has been calibrated so that outcomes are consistent with the 1957/1958 Asian A(H2N2) and 2009 pandemic A(H1N1) influenza viruses. We present examples of how this model can be used to study the dynamics of influenza epidemics in the United States and simulate how to mitigate or delay them using pharmaceutical interventions and social distancing measures. Computer simulation models play an essential role in informing public policy and evaluating pandemic preparedness plans. We have made the source code of this model publicly available to encourage its use and further development. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 2 | 50% |
| Norway | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 249 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 3% |
| Italy | 2 | <1% |
| Australia | 2 | <1% |
| United Kingdom | 2 | <1% |
| South Africa | 1 | <1% |
| Israel | 1 | <1% |
| Brazil | 1 | <1% |
| Canada | 1 | <1% |
| Switzerland | 1 | <1% |
| Other | 2 | <1% |
| Unknown | 228 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 57 | 23% |
| Student > Ph. D. Student | 54 | 22% |
| Student > Master | 25 | 10% |
| Student > Bachelor | 17 | 7% |
| Professor > Associate Professor | 16 | 6% |
| Other | 50 | 20% |
| Unknown | 30 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 38 | 15% |
| Medicine and Dentistry | 35 | 14% |
| Agricultural and Biological Sciences | 28 | 11% |
| Mathematics | 27 | 11% |
| Engineering | 20 | 8% |
| Other | 58 | 23% |
| Unknown | 43 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 31. 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 20 February 2024.
All research outputs
#1,282,597
of 25,461,852 outputs
Outputs from PLoS Computational Biology
#1,067
of 8,981 outputs
Outputs of similar age
#5,384
of 173,107 outputs
Outputs of similar age from PLoS Computational Biology
#6
of 58 outputs
Altmetric has tracked 25,461,852 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,981 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done well, scoring higher than 88% 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 173,107 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 58 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.