| Title |
Spatiotemporal characteristics of pandemic influenza
|
|---|---|
| Published in |
BMC Infectious Diseases, July 2014
|
| DOI | 10.1186/1471-2334-14-378 |
| Pubmed ID | |
| Authors |
Lars Skog, Annika Linde, Helena Palmgren, Hans Hauska, Fredrik Elgh |
| Abstract |
Prediction of timing for the onset and peak of an influenza pandemic is of vital importance for preventive measures. In order to identify common spatiotemporal patterns and climate influences for pandemics in Sweden we have studied the propagation in space and time of A(H1N1)pdm09 (10,000 laboratory verified cases), the Asian Influenza 1957-1958 (275,000 cases of influenza-like illness (ILI), reported by local physicians) and the Russian Influenza 1889-1890 (32,600 ILI cases reported by physicians shortly after the end of the outbreak). |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 33% |
| United States | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 3% |
| Unknown | 29 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 23% |
| Researcher | 6 | 20% |
| Student > Master | 6 | 20% |
| Student > Bachelor | 4 | 13% |
| Professor > Associate Professor | 3 | 10% |
| Other | 5 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 30% |
| Agricultural and Biological Sciences | 4 | 13% |
| Nursing and Health Professions | 3 | 10% |
| Computer Science | 3 | 10% |
| Immunology and Microbiology | 2 | 7% |
| Other | 7 | 23% |
| Unknown | 2 | 7% |
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 15 February 2022.
All research outputs
#2,946,209
of 23,881,329 outputs
Outputs from BMC Infectious Diseases
#920
of 7,931 outputs
Outputs of similar age
#29,356
of 228,395 outputs
Outputs of similar age from BMC Infectious Diseases
#17
of 149 outputs
Altmetric has tracked 23,881,329 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 7,931 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. 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 228,395 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 87% of its contemporaries.
We're also able to compare this research output to 149 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.