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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Maximum linkage space-time permutation scan statistics for disease outbreak detection
|
|---|---|
| Published in |
International Journal of Health Geographics, June 2014
|
| DOI | 10.1186/1476-072x-13-20 |
| Pubmed ID | |
| Authors |
Marcelo A Costa, Martin Kulldorff |
| Abstract |
In disease surveillance, the prospective space-time permutation scan statistic is commonly used for the early detection of disease outbreaks. The scanning window that defines potential clusters of diseases is cylindrical in shape, which does not allow incorporating into the cluster shape potential factors that can contribute to the spread of the disease, such as information about roads, landscape, among others. Furthermore, the cylinder scanning window assumes that the spatial extent of the cluster does not change in time. Alternatively, a dynamic space-time cluster may indicate the potential spread of the disease through time. For instance, the cluster may decrease over time indicating that the spread of the disease is vanishing. |
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 % |
|---|---|---|
| Colombia | 2 | 67% |
| United States | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Unknown | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Switzerland | 1 | 2% |
| Unknown | 49 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 31% |
| Researcher | 8 | 16% |
| Student > Bachelor | 4 | 8% |
| Student > Doctoral Student | 4 | 8% |
| Student > Master | 4 | 8% |
| Other | 6 | 12% |
| Unknown | 9 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 12% |
| Veterinary Science and Veterinary Medicine | 5 | 10% |
| Mathematics | 5 | 10% |
| Medicine and Dentistry | 5 | 10% |
| Computer Science | 4 | 8% |
| Other | 15 | 29% |
| Unknown | 11 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 31 May 2015.
All research outputs
#14,254,992
of 25,371,288 outputs
Outputs from International Journal of Health Geographics
#342
of 654 outputs
Outputs of similar age
#114,808
of 244,218 outputs
Outputs of similar age from International Journal of Health Geographics
#6
of 16 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 654 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.7. This one is in the 47th percentile – i.e., 47% 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 244,218 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 52% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.