BMJ 17/05/12 Can Twitter predict disease outbreaks? Journal of Infection and Public Health Available online 8 August 2016 Impact of Twitter intensity, time, and location on message lapse of bluebird's pursuit of fleas in Madagascar. Open Archive Abstract Background.
Procedia Computer Science Volume 82, 2016, Towards a Disease Outbreak Notification Framework Using Twitter Mining for Smart Home Dashboards. Volume 82, 2016, Pages 132–134 4th Symposium on Data Mining Applications, SDMA2016, 30 March 2016, Riyadh, Saudi Arabia Edited By Basit Qureshi and AbdulAziz Al Sehibani Abstract Disease outbreaks are becoming a primary concern for many countries due to the recent cases of MERS, Ebola to name a few.
Preventive measures can be taken into account when proper information about an outbreak is disseminated among the masses. JOURNAL OF RISK RESEARCH 27/01/17 The social amplification of risk on Twitter: the case of ash dieback disease in the United Kingdom. PLOS 25/07/16 Applying GIS and Machine Learning Methods to Twitter Data for Multiscale Surveillance of Influenza. Abstract Traditional methods for monitoring influenza are haphazard and lack fine-grained details regarding the spatial and temporal dynamics of outbreaks.
Twitter gives researchers and public health officials an opportunity to examine the spread of influenza in real-time and at multiple geographical scales. In this paper, we introduce an improved framework for monitoring influenza outbreaks using the social media platform Twitter. Relying upon techniques from geographic information science (GIS) and data mining, Twitter messages were collected, filtered, and analyzed for the thirty most populated cities in the United States during the 2013–2014 flu season. The results of this procedure are compared with national, regional, and local flu outbreak reports, revealing a statistically significant correlation between the two data sources. Editor: Mansour Ebrahimi, Qom University, ISLAMIC REPUBLIC OF IRAN Received: October 22, 2015; Accepted: June 4, 2016; Published: July 25, 2016. PLOS 18/05/16 DEFENDER: Detecting and Forecasting Epidemics Using Novel Data-Analytics for Enhanced Response.
Abstract In recent years social and news media have increasingly been used to explain patterns in disease activity and progression.
Social media data, principally from the Twitter network, has been shown to correlate well with official disease case counts. This fact has been exploited to provide advance warning of outbreak detection, forecasting of disease levels and the ability to predict the likelihood of individuals developing symptoms. In this paper we introduce DEFENDER, a software system that integrates data from social and news media and incorporates algorithms for outbreak detection, situational awareness and forecasting. As part of this system we have developed a technique for creating a location network for any country or region based purely on Twitter data. Citation: Thapen N, Simmie D, Hankin C, Gillard J (2016) DEFENDER: Detecting and Forecasting Epidemics Using Novel Data-Analytics for Enhanced Response.
BIORXIV 22/09/16 Dynamic forecasting of Zika epidemics using Google Trends. IMPERIAL COLLEGE LONDON 17/11/16 Présentation : Social media analytics - detecting and tracking infectious disease based on Twitter activity. Advances in Experimental Medicine and Biology 22/12/16 The Potential of Social Media and Internet-Based Data in Preventing and Fighting Infectious Diseases: From Internet to Twitter. JPHMP - 2017 - Using Twitter to Identify and Respond to Food Poisoning: The Food Safety STL Project. PLOS 30/03/16 Analysis of the Capacity of Google Trends to Measure Interest in Conservation Topics and the Role of Online News. Abstract With the continuous growth of internet usage, Google Trends has emerged as a source of information to investigate how social trends evolve over time.
Knowing how the level of interest in conservation topics—approximated using Google search volume—varies over time can help support targeted conservation science communication. However, the evolution of search volume over time and the mechanisms that drive peaks in searches are poorly understood. We conducted time series analyses on Google search data from 2004 to 2013 to investigate: (i) whether interests in selected conservation topics have declined and (ii) the effect of news reporting and academic publishing on search volume. Although trends were sensitive to the term used as benchmark, we did not find that public interest towards conservation topics such as climate change, ecosystem services, deforestation, orangutan, invasive species and habitat loss was declining. Editor: Zhong-Ke Gao, Tianjin University, CHINA. SCIENCE DAILY 23/02/17 Using Twitter may increase food-poisoning reporting. Nearly 1 in 4 U.S. citizens gets food poisoning every year, but very few report it.
Twitter communications between the public and the proper government authorities could improve foodborne illness reporting as well as the steps that follow, according to a new study from the Brown School at Washington University in St. Louis. Jenine Harris, associate professor, and colleagues partnered with the City of St. Louis Department of Health in October 2015 to implement the HealthMap Foodborne Dashboard developed at Boston Children's Hospital. In the first seven months of the pilot study, they identified 193 tweets relevant to food poisoning and replied with a link to a form for reporting illness to the health department. "The dashboard technology has potential for improving foodborne illness reporting and can be implemented in other areas to improve response to public health issues such as suicidality, the spread of Zika virus, infection and hospital quality," Harris said.
FOOD SAFETY MAGAZINE 24/02/17 Twitter Use Improves Food Poisoning Reports, Says Washington University. News | February 24, 2017 By Staff According to a new study conducted by the Brown School at Washington University (St.
Louis, MO), notifying the proper government authorities of suspected food poisoning could improve not only the reporting of such illnesses, but thoroughness of the follow up investigation as well. Jenine Harris, an associate professor at the university teamed up with some colleagues and the St. HAUTE ECOLE DE GESTION DE GENEVE 22/06/15 Thèse en ligne : L’exploration du Big Data par sa visualisation – Application au projet GEoTweet. UNIVERSITE TOULOUSE III 02/06/16 Thèse en ligne : Apport de l'outil Google Trends(r) dans les études épidémiologiques : exemple de l'amalgame. Canceill , Thibault (2016) Apport de l'outil Google Trends(r) dans les études épidémiologiques : exemple de l'amalgame.
Thèse d'exercice en Thèses > Dentaire, Université Toulouse lll - Paul Sabatier. Introduction : l'amalgame dentaire est un matériau d'obturation inséré en méthode directe. Utilisé depuis des décennies, il est actuellement très décrié à cause de sa toxicité potentielle, liée à sa composition. Ainsi, le rôle joué par les médias pourrait occulter ses autres propriétés, méconnues du grand public. BLOG MICROBIO 02/07/16 Epidemiología digital: Google nos puede ayudar a controlar las epidemias. La epidemiología digital demuestra la estacionalidad global de enfermedades infantiles y los efectos de la vacunación Las enfermedades infecciosas infantiles continúan siendo un problema global muy importante.
BIORXIV 22/09/16 Dynamic forecasting of Zika epidemics using Google Trends. NEWS FULTON COUNTY 27/08/15 Uganda using Twitter to detect disease outbreaks. – With porous borders and disease outbreaks inside and around Uganda, authorities are using Twitter to speed up response times By Halima Athumani KAMPALA, Uganda – Uganda’s Ministry of Health is using Twitter to collect real time information about disease outbreaks in the East African country.
In an exclusive interview with Anadolu Agency at the Public Health Emergency Operations Center in Kampala, Dr. Issa Makumbi said: “We set up this center in July 2013 because of the constant disease outbreaks and we needed to prepare and cope with them more effectively and efficiently.” The World Health Organization’s Department of Global Capacities, Alert and Response established the Public Health Emergency Operations Center Network in order to strengthen global collaboration and WHO member states’ capacity for effective responses to public health hazards. “Ebola and Marburg were rampant at the time and since then we have had five Ebola outbreaks and three Marburg outbreaks,” Dr. Dr. Dr. Governmental Institute of Public Health of Lower Saxony Hannover, Germany - 2011 - A New Age of Public Health: Identifying Disease Outbreaks by Analyzing Tweets. UNIVERSITY OF STRATHCLYDE GLASWOG - 2013 - Nowcasting with Google Trends : a keyword selection method.
Ross, Andrew (2013) Nowcasting with Google Trends : a keyword selection method. Fraser of Allander Economic Commentary, 37 (2). pp. 54-64. ISSN 2046-5378 Search engines, such as Google, keep a log of searches entered into their websites. BMC 31/12/14 Using internet search queries for infectious disease surveillance: screening diseases for suitability. Multiple Sclerosis International Volume 2013 (2013), Infodemiology and Infoveillance of Multiple Sclerosis in Italy. DERMATOLOGY ONLINE JOURNAL - JANV 2015- Comparing burden of dermatologie disease to search interest on google trends. Cad. Saúde Pública vol.31 no.6 Rio de Janeiro June 2015 Google Trends (GT) related to influenza.
Google Trends (GT) related to influenza Google Trends relacionado à influenza Google Trends relacionado a la influenza 1Surin Rajabhat University, Surin, Thailand. 2Wiwanitkit House, Bangkok, Thailand. 3Hainan Medical College, Hainan, China. Editors, ROYAL SOCIETY OPEN SCIENCE 29/10/14 Adaptive nowcasting of influenza outbreaks using Google searches. Abstract Seasonal influenza outbreaks and pandemics of new strains of the influenza virus affect humans around the globe. However, traditional systems for measuring the spread of flu infections deliver results with one or two weeks delay. Recent research suggests that data on queries made to the search engine Google can be used to address this problem, providing real-time estimates of levels of influenza-like illness in a population.
Others have however argued that equally good estimates of current flu levels can be forecast using historic flu measurements. Here, we build dynamic ‘nowcasting’ models; in other words, forecasting models that estimate current levels of influenza, before the release of official data one week later. 2. Large technological systems have now become a central part of our everyday life. PLOS 31/12/14 Improving Google Flu Trends Estimates for the United States through Transformation. Abstract Google Flu Trends (GFT) uses Internet search queries in an effort to provide early warning of increases in influenza-like illness (ILI).
In the United States, GFT estimates the percentage of physician visits related to ILI (%ILINet) reported by the Centers for Disease Control and Prevention (CDC). However, during the 2012–13 influenza season, GFT overestimated %ILINet by an appreciable amount and estimated the peak in incidence three weeks late. Using data from 2010–14, we investigated the relationship between GFT estimates (%GFT) and %ILINet. Based on the relationship between the relative change in %GFT and the relative change in %ILINet, we transformed %GFT estimates to better correspond with %ILINet values. Citation: Martin LJ, Xu B, Yasui Y (2014) Improving Google Flu Trends Estimates for the United States through Transformation. PLOS 22/10/14 The Use of Google Trends in Health Care Research: A Systematic Review. Abstract Background Google Trends is a novel, freely accessible tool that allows users to interact with Internet search data, which may provide deep insights into population behavior and health-related phenomena.
However, there is limited knowledge about its potential uses and limitations. We therefore systematically reviewed health care literature using Google Trends to classify articles by topic and study aim; evaluate the methodology and validation of the tool; and address limitations for its use in research. PLOS 25/01/13 Using Google Trends for Influenza Surveillance in South China. Abstract Background Google Flu Trends was developed to estimate influenza activity in many countries; however there is currently no Google Flu Trends or other Internet search data used for influenza surveillance in China. Methods and Findings. CDC EID - JANV 2010 - Diseases Tracked by Using Google Trends, Spain. Cad. Saúde Pública, Rio de Janeiro, 31(6):1333-1335, jun, 2015 Google Trends (GT) related to influenza. WIRED - OCT 2015 - What We Can Learn From the Epic Failure of Google Flu Trends. Every day, millions of people use Google to dig up information that drives their daily lives, from how long their commute will be to how to treat their child’s illness.
This search data reveals a lot about the searchers: their wants, their needs, their concerns—extraordinarily valuable information. If these searches accurately reflect what is happening in people’s lives, analysts could use this information to track diseases, predict sales of new products, or even anticipate the results of elections. ABONDANCE 19/06/15 Google Trends maintenant en temps réel. FRENCHWEB 03/04/15 Les médecins bientôt sur Google Trends pour prédire les risques de maladies graves? L’idée paraît peu croyable, elle vient pourtant d’être démontrée par des chercheurs universitaires australiens. Les requêtes Internet que l’on fait sur les moteurs de recherche permettraient de prédire les risques de maladies non transmissibles, dans une région en particulier.
L’étude reprise sur le site du Globe and Mail part du postulat selon lequel les recherches qui sont faites sont liées aux comportements. Les risques d’accidents vasculaires, de maladies cardiaques ou de cancers deviennent prévisibles. Par exemple, des internautes qui feraient une recherche Google sur les horaires d’ouverture d’un club de gym indiquent qu’il sont en recherche d’exercices physiques. INSEE - MARS 2015 - Apports de Google Trends pour prévoir la conjoncture française : des pistes limitée. INRA - 2014 - Projet Geek - Suivre les pullulations et anticiper la progression des espèces envahissantes grâce à Google. Diaporama GEEK.