请输入您要查询的百科知识：

　

词条 Infoveillance
释义

  1. Google Flu Trends

  2. Google Dengue Trends

  3. Flu Detector

  4. Mood of the Nation

  5. See also

  6. References

  7. External links

Infoveillance is the type of syndromic surveillance that utilizes the online contents.[1] The term was coined by Gunther Eysenbach in 2004 for the first time along with Infodemiology [2][3]

The work of Gunther Eysenbach, which utilized the Google Search queries, had led to the birth of Google Flu. Other than Google search engines have also been used.[4]

[5]

Later other researchers utilized other social media such as Twitter to find the disease outbreak patterns.[6][7] The infoveillance detects disease outbreaks quicker than traditional public health surveillance systems with the minimal cost involved, revealing the promising results for the future surveillance methodologies.{{citation needed|date=December 2011}}

Google Flu Trends

Google uses the query information to detect the flu trends and it compares the results to the countries' official surveillance data.

The primary research behind the Google Flu Trend is found here.[8] In light of evidence showing that Google Flu Trends was occasionally over-estimating flu rates, researchers have also proposed a series of more advanced and better-performing approaches to flu modelling from Google search queries.[9]

Google Dengue Trends

Google uses the query information to detect the dengue trendsand it compares the results to the countries' official surveillance data.

The primary research behind the Google Dengue Trend is found here.[10]

Flu Detector

Flu Detector was developed by Vasileios Lampos et al. at the University of Bristol. It is an application of Machine Learning that firstly uses Feature Selection to automatically extract flu-related terms from Twitter content and then uses those terms to compute a flu-score for several UK regions based on geolocated tweets. The primary research behind the Flu Detector is found here;[6] a generalised scheme able to track other events as well is proposed here.[11]

A new, totally revamped (in terms of models and online data) version of the Flu Detector has been recently launched.

Mood of the Nation

Mood of the Nation was developed by Vasileios Lampos et al. at the University of Bristol. It performs mood analysis on tweets geo-located in various regions of the United Kingdom computing on a daily basis scores for four types of emotion: anger, fear, joy and sadness.

See also

  • Participatory surveillance

References

1. ^{{cite journal |pmid=17238340 |year=2006 |last1=Eysenbach |first1=Gunther |title=Infodemiology: Tracking Flu-Related Searches on the Web for Syndromic Surveillance |pages=244–8 |pmc=1839505 |journal=AMIA Annual Symposium Proceedings}}
2. ^{{Cite journal | author = Gunther Eysenbach | title = Infodemiology and infoveillance tracking online health information and cyberbehavior for public health | journal = American Journal of Preventive Medicine | volume = 40 | issue = 5 Suppl 2 | pages = S154–S158 |date=May 2011 | doi = 10.1016/j.amepre.2011.02.006 | pmid = 21521589}}
3. ^{{Cite journal | author = Gunther Eysenbach | title = Infodemiology and infoveillance: framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the Internet | journal = Journal of Medical Internet Research | volume = 11 | issue = 1 | pages = e11 | year = 2009 | month = | doi = 10.2196/jmir.1157 | pmid = 19329408 | pmc=2762766}}
4. ^{{cite journal |pages=841–9 |doi= 10.1007/s00038-014-0581-7 |title= Demand-based web surveillance of sexually transmitted infections in Russia |year=2014 |last1=Domnich |first1=Alexander |last2=Arbuzova |first2=Eva K. |last3=Signori |first3=Alessio |last4=Amicizia |first4=Daniela |last5=Panatto |first5=Donatella |last6=Gasparini |first6=Roberto |journal=International Journal of Public Health |volume=59 |issue=5 |pmid=25012799}}
5. ^{{cite journal |pages=241–8 |doi= 10.1631/jzus.C0910371 |title= Notifiable infectious disease surveillance with data collected by search engine|year=2010 |last1=Zhou |first1=Xi-chuan |last2=Shen |first2=Hai-bin |journal= Journal of Zhejiang University-SCIENCE C (Computers & Electronics) |volume=11 |issue=4}}
6. ^1 {{cite journal |pages=411–6 |doi=10.1109/CIP.2010.5604088 |title=Tracking the flu pandemic by monitoring the social web |journal=2010 2nd International Workshop on Cognitive Information Processing |year=2010 |last1=Lampos |first1=Vasileios |last2=Cristianini |first2=Nello |isbn=978-1-4244-6459-3}}
7. ^{{cite journal |pmid=20865540 |year=2010 |last1=Corley |first1=Courtney D. |last2=Cook |first2=Diane J. |last3=Mikler |first3=Armin R. |last4=Singh |first4=Karan P. |title=Using Web and Social Media for Influenza Surveillance |volume=680 |pages=559–64 |doi=10.1007/978-1-4419-5913-3_61 |journal=Advances in Computational Biology |isbn=978-1-4419-5912-6 |series=Advances in Experimental Medicine and Biology}}
8. ^{{cite journal |pages=1012–4 |doi=10.1038/nature07634 |title=Detecting influenza epidemics using search engine query data |year=2008 |last1=Ginsberg |first1=Jeremy |last2=Mohebbi |first2=Matthew H. |last3=Patel |first3=Rajan S. |last4=Brammer |first4=Lynnette |last5=Smolinski |first5=Mark S. |last6=Brilliant |first6=Larry |journal=Nature |volume=457 |issue=7232 |pmid=19020500}}
9. ^{{cite journal |last=Lampos |first=Vasileios |last2=Miller |first2=Andrew C. |last3=Crossan |first3=Steve| last4=Stefansen |first4=Christian |date=3 Aug 2015 |title=Advances in nowcasting influenza-like illness rates using search query logs |journal=Scientific Reports |volume=5 |issue=12760|pages=12760 | doi=10.1038/srep12760 |pmid=26234783 |pmc=4522652}}
10. ^{{cite journal |doi=10.1371/journal.pntd.0001206 |pmc=3104029 |title=Using Web Search Query Data to Monitor Dengue Epidemics: A New Model for Neglected Tropical Disease Surveillance |year=2011 |editor1-last=Aksoy |editor1-first=Serap |last1=Chan |first1=Emily H. |last2=Sahai |first2=Vikram |last3=Conrad |first3=Corrie |last4=Brownstein |first4=John S. |journal=PLoS Neglected Tropical Diseases |volume=5 |issue=5 |pages=e1206 |pmid=21647308}}
11. ^{{cite journal| author=Lampos, Vasileios, Cristianini, Nello | title=Nowcasting Events from the Social Web with Statistical Learning | journal=ACM Transactions on Intelligent Systems and Technology | volume=3 | issue=4 | pages=1–22 | year=2012 | doi=10.1145/2337542.2337557 }}

External links

  • "Google Flu Trend"
  • "Google Dengue Trend"
  • "Flu Detector"
  • [https://www.ncbi.nlm.nih.gov/pubmed/19329408/ "Health informatics"]
  • "JMIR e-collection of peer-reviewed articles on Infodemiology and Infoveillance"
  • "JMIR Public Health & Surveillance e-collection of peer-reviewed articles on Infoveillance, Infodemiology and Digital Disease Surveillance"

3 : Internet culture|Internet Society people|Epidemiology
随便看

　

开放百科全书收录14589846条英语、德语、日语等多语种百科知识，基本涵盖了大多数领域的百科知识，是一部内容自由、开放的电子版国际百科全书。

　

Copyright © 2023 OENC.NET All Rights Reserved
京ICP备2021023879号 更新时间：2024/9/23 1:32:43