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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Social media posts and online search behaviour as early-warning system for MRSA outbreaks
|
|---|---|
| Published in |
Antimicrobial Resistance & Infection Control, May 2018
|
| DOI | 10.1186/s13756-018-0359-4 |
| Pubmed ID | |
| Authors |
Tom H. van de Belt, Pieter T. van Stockum, Lucien J. L. P. G. Engelen, Jules Lancee, Remco Schrijver, Jesús Rodríguez-Baño, Evelina Tacconelli, Katja Saris, Marleen M. H. J. van Gelder, Andreas Voss |
| Abstract |
Despite many preventive measures, outbreaks with multi-drug resistant micro-organisms (MDROs) still occur. Moreover, current alert systems from healthcare organizations have shortcomings due to delayed or incomplete notifications, which may amplify the spread of MDROs by introducing infected patients into a new healthcare setting and institutions. Additional sources of information about upcoming and current outbreaks, may help to prevent further spread of MDROs.The study objective was to evaluate whether methicillin-resistant Staphylococcus aureus (MRSA) outbreaks could be detected via social media posts or online search behaviour; if so, this might allow earlier detection than the official notifications by healthcare organizations. We conducted an exploratory study in which we compared information about MRSA outbreaks in the Netherlands derived from two online sources, Coosto for Social Media, and Google Trends for search behaviour, to the mandatory Dutch outbreak notification system (SO-ZI/AMR). The latter provides information on MDRO outbreaks including the date of the outbreak, micro-organism involved, the region/location, and the type of health care organization. During the research period of 15 months (455 days), 49 notifications of outbreaks were recorded in SO-ZI/AMR. For Coosto, the number of unique potential outbreaks was 37 and for Google Trends 24. The use of social media and online search behaviour missed many of the hospital outbreaks that were reported to SO-ZI/AMR, but detected additional outbreaks in long-term care facilities. Despite several limitations, using information from social media and online search behaviour allows rapid identification of potential MRSA outbreaks, especially in healthcare settings with a low notification compliance. When combined in an automated system with real-time updates, this approach might increase early discovery and subsequent implementation of preventive measures. |
X Demographics
The data shown below were collected from the profiles of 19 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 Kingdom | 4 | 21% |
| Belgium | 2 | 11% |
| Netherlands | 2 | 11% |
| Finland | 1 | 5% |
| Venezuela, Bolivarian Republic of | 1 | 5% |
| Korea, Democratic People's Republic of | 1 | 5% |
| Switzerland | 1 | 5% |
| Canada | 1 | 5% |
| Australia | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 4 | 21% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 12 | 63% |
| Scientists | 4 | 21% |
| Practitioners (doctors, other healthcare professionals) | 2 | 11% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 70 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 14 | 20% |
| Researcher | 7 | 10% |
| Student > Ph. D. Student | 7 | 10% |
| Student > Bachelor | 5 | 7% |
| Student > Postgraduate | 5 | 7% |
| Other | 8 | 11% |
| Unknown | 24 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 10 | 14% |
| Social Sciences | 8 | 11% |
| Business, Management and Accounting | 4 | 6% |
| Computer Science | 4 | 6% |
| Nursing and Health Professions | 4 | 6% |
| Other | 12 | 17% |
| Unknown | 28 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 22. 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 10 August 2020.
All research outputs
#1,729,107
of 25,377,790 outputs
Outputs from Antimicrobial Resistance & Infection Control
#176
of 1,456 outputs
Outputs of similar age
#36,211
of 344,250 outputs
Outputs of similar age from Antimicrobial Resistance & Infection Control
#7
of 29 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,456 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.4. This one has done well, scoring higher than 87% 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 344,250 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 89% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.