Title |
Modelling the transmission of healthcare associated infections: a systematic review
|
---|---|
Published in |
BMC Infectious Diseases, June 2013
|
DOI | 10.1186/1471-2334-13-294 |
Pubmed ID | |
Authors |
Esther van Kleef, Julie V Robotham, Mark Jit, Sarah R Deeny, William J Edmunds |
Abstract |
Dynamic transmission models are increasingly being used to improve our understanding of the epidemiology of healthcare-associated infections (HCAI). However, there has been no recent comprehensive review of this emerging field. This paper summarises how mathematical models have informed the field of HCAI and how methods have developed over time. |
X Demographics
The data shown below were collected from the profiles of 14 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 14% |
United Kingdom | 1 | 7% |
Netherlands | 1 | 7% |
Canada | 1 | 7% |
Spain | 1 | 7% |
Argentina | 1 | 7% |
Czechia | 1 | 7% |
Unknown | 6 | 43% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 10 | 71% |
Practitioners (doctors, other healthcare professionals) | 2 | 14% |
Scientists | 1 | 7% |
Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 318 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 5 | 2% |
United States | 5 | 2% |
France | 2 | <1% |
Australia | 1 | <1% |
India | 1 | <1% |
Netherlands | 1 | <1% |
Canada | 1 | <1% |
Brazil | 1 | <1% |
Unknown | 301 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 66 | 21% |
Researcher | 52 | 16% |
Student > Master | 46 | 14% |
Student > Bachelor | 21 | 7% |
Student > Doctoral Student | 19 | 6% |
Other | 74 | 23% |
Unknown | 40 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 67 | 21% |
Agricultural and Biological Sciences | 45 | 14% |
Mathematics | 25 | 8% |
Immunology and Microbiology | 16 | 5% |
Biochemistry, Genetics and Molecular Biology | 15 | 5% |
Other | 85 | 27% |
Unknown | 65 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 04 October 2013.
All research outputs
#4,138,446
of 24,397,600 outputs
Outputs from BMC Infectious Diseases
#1,346
of 8,159 outputs
Outputs of similar age
#33,806
of 199,542 outputs
Outputs of similar age from BMC Infectious Diseases
#21
of 152 outputs
Altmetric has tracked 24,397,600 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,159 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 83% 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 199,542 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 83% of its contemporaries.
We're also able to compare this research output to 152 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.