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| Title |
Web-based infectious disease surveillance systems and public health perspectives: a systematic review
|
|---|---|
| Published in |
BMC Public Health, December 2016
|
| DOI | 10.1186/s12889-016-3893-0 |
| Pubmed ID | |
| Authors |
Jihye Choi, Youngtae Cho, Eunyoung Shim, Hyekyung Woo |
| Abstract |
Emerging and re-emerging infectious diseases are a significant public health concern, and early detection and immediate response is crucial for disease control. These challenges have led to the need for new approaches and technologies to reinforce the capacity of traditional surveillance systems for detecting emerging infectious diseases. In the last few years, the availability of novel web-based data sources has contributed substantially to infectious disease surveillance. This study explores the burgeoning field of web-based infectious disease surveillance systems by examining their current status, importance, and potential challenges. A systematic review framework was applied to the search, screening, and analysis of web-based infectious disease surveillance systems. We searched PubMed, Web of Science, and Embase databases to extensively review the English literature published between 2000 and 2015. Eleven surveillance systems were chosen for evaluation according to their high frequency of application. Relevant terms, including newly coined terms, development and classification of the surveillance systems, and various characteristics associated with the systems were studied. Based on a detailed and informative review of the 11 web-based infectious disease surveillance systems, it was evident that these systems exhibited clear strengths, as compared to traditional surveillance systems, but with some limitations yet to be overcome. The major strengths of the newly emerging surveillance systems are that they are intuitive, adaptable, low-cost, and operated in real-time, all of which are necessary features of an effective public health tool. The most apparent potential challenges of the web-based systems are those of inaccurate interpretation and prediction of health status, and privacy issues, based on an individual's internet activity. Despite being in a nascent stage with further modification needed, web-based surveillance systems have evolved to complement traditional national surveillance systems. This review highlights ways in which the strengths of existing systems can be maintained and weaknesses alleviated to implement optimal web surveillance systems. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Belgium | 2 | 33% |
| Unknown | 4 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 83% |
| Practitioners (doctors, other healthcare professionals) | 1 | 17% |
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 | 1 | <1% |
| Unknown | 317 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 64 | 20% |
| Researcher | 43 | 14% |
| Student > Ph. D. Student | 42 | 13% |
| Student > Bachelor | 31 | 10% |
| Other | 15 | 5% |
| Other | 44 | 14% |
| Unknown | 79 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 51 | 16% |
| Computer Science | 39 | 12% |
| Nursing and Health Professions | 27 | 8% |
| Agricultural and Biological Sciences | 13 | 4% |
| Business, Management and Accounting | 12 | 4% |
| Other | 77 | 24% |
| Unknown | 99 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 38. 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 11 August 2022.
All research outputs
#1,141,321
of 26,456,908 outputs
Outputs from BMC Public Health
#1,284
of 18,258 outputs
Outputs of similar age
#22,055
of 426,183 outputs
Outputs of similar age from BMC Public Health
#19
of 204 outputs
Altmetric has tracked 26,456,908 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 18,258 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.9. This one has done particularly well, scoring higher than 92% 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 426,183 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 204 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.