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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Temporal aggregation impacts on epidemiological simulations employing microcontact data
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, November 2012
|
| DOI | 10.1186/1472-6947-12-132 |
| Pubmed ID | |
| Authors |
Mohammad Hashemian, Weicheng Qian, Kevin G Stanley, Nathaniel D Osgood |
| Abstract |
Microcontact datasets gathered automatically by electronic devices have the potential augment the study of the spread of contagious disease by providing detailed representations of the study population's contact dynamics. However, the impact of data collection experimental design on the subsequent simulation studies has not been adequately addressed. In particular, the impact of study duration and contact dynamics data aggregation on the ultimate outcome of epidemiological models has not been studied in detail, leaving the potential for erroneous conclusions to be made based on simulation outcomes. |
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 % |
|---|---|---|
| India | 1 | 50% |
| United States | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 3% |
| Australia | 1 | 3% |
| Unknown | 34 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 31% |
| Student > Ph. D. Student | 5 | 14% |
| Student > Master | 4 | 11% |
| Student > Bachelor | 3 | 8% |
| Professor | 3 | 8% |
| Other | 6 | 17% |
| Unknown | 4 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 22% |
| Computer Science | 6 | 17% |
| Mathematics | 3 | 8% |
| Agricultural and Biological Sciences | 2 | 6% |
| Nursing and Health Professions | 2 | 6% |
| Other | 9 | 25% |
| Unknown | 6 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 23 November 2012.
All research outputs
#15,256,044
of 22,685,926 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,305
of 1,979 outputs
Outputs of similar age
#112,461
of 178,791 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#34
of 42 outputs
Altmetric has tracked 22,685,926 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,979 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 24th percentile – i.e., 24% 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 178,791 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.