PLOS 07/12/16 Social Media as a Sentinel for Disease Surveillance: What Does Sociodemographic Status Have to Do with It? Dengue is a mosquito-borne disease transmitted between humans by infected Aedes mosquitoes1 and is a major cause of illness and death in many tropical and subtropical regions2.
Despite improvements in disease surveillance and investments in mosquito control programs, dengue remains a major public health threat in many countries3,4,5,6. Efforts at improving surveillance have explored non-traditional data sources, including, crowd-generated approaches using mobile phones and social media7,8, and Internet search query data9,10,11. These systems have the potential to capture mild infections not requiring medical attention, and enable the ascertainment of the probable temporal and spatial distribution of cases prior to official reports of disease.
To extract major features distinguishing irrelevant and relevant (i.e. suspected dengue disease) tweets, we considered emojis, location information (state, county and micro-region), unigrams, bigrams and trigrams. Sociodemographic Analysis John S. CCTS VIA YOUTUBE 23/03/16 The Future of Disease Monitoring: Wearable Biosensors, Social Media, and Smartphone Applications. American Journal of Infection Control Volume 44, Issue 12, 1 December 2016, Ebola virus disease and social media: A systematic review. Veille signaux faibles via GOOGLE TRENDS et TWITTER. WASHINGTON UNIVERSITY IN ST LOUIS - FEV 2016 - Présentation : Using Social Media to Detect Potential Foodborne Outbreaks. RISQUES_GOUV_FR - 2016 - Utiliser les médias sociaux en situation d'urgence #MSGU Bonnes pratiques numériques en situation d’urgence. BRGM 17/11/16 Observatoire citoyen des risques naturels : collecter, informer et prévenir grâce aux réseaux sociaux. ISPRS 19/08/16 Use of Social Media for the Detection and Analysis of Infectious Diseases in China.
Introduction Since 2013, 2.35 million cases of dengue fever have been reported in the Americas, and 37,687 of these dengue fever cases were considered to be severe . Identifying the geographical ranges helps the public understand the risk posed by infectious disease outbreaks . Early detection of disease activity, followed by a rapid response, can largely reduce the impact of both seasonal and pandemic influenza . Social media analytics enable the possibility of infectious disease surveillance at a fine scale and in a timely manner . The geographical context of health research has shifted from a data-scarce to a data-rich environment .
UNIVERSITY OF APPLIED SCIENCE BONN-RHEIN-SIEG - 2015 - Web Data Mining and Social Media Analysis for better Communication in Food Safety Cris. FOOD SAFETY MAGAZINE - OCT 2014 - Emerging Risk Identification in the Age of Social Media. Signature Series | October 2014 By Adrienne M.
Dunham and Forrest M. Hillery In recent years, a recurring discussion within the food industry concerning the use of a processed ground beef product became national news. How? In 2013, another blog post advocating the removal of Yellow Dye No.’s 5 and 6 in a popular children’s food product led to more national media attention, followed by an outpouring of public support, ultimately resulting in the removal of those ingredients from some well-established and popular food products. Increasingly, consumers are becoming more aware of what goes into their food and how it’s produced. ASPC 03/09/15 Les données massives et le Réseau mondial d'information en santé publique (RMISP) Pour partager cette page, veuillez cliquez sur le réseau sociale de votre choix.
Relevé des maladies transmissibles au Canada (RMTC) ASPC 12/09/14 Utilisation des technologies numériques en santé publique. Pour partager cette page, veuillez cliquez sur le réseau sociale de votre choix.
[Page précédente] [Table des matières] [Page suivante] Points saillants Les technologies sont utilisables de nombreuses manières pour améliorer, promouvoir et surveiller la santé. Dans le domaine de la santé publique, les technologies sont utiles aux chercheurs, aux professionnels de la santé publique, aux collectivités et aux individus. L’omniprésence des ordinateurs et des technologies informatiques peuvent grandement contribuer à la mise en œuvre et à l’exécution de programmes de prévention et de promotion de la santé.
THE POLICY AND INTERNET BLOG 14/10/13 Can Twitter provide an early warning function for the next pandemic? 14 October 2013 With factors such as air travel act as a catalyst in the spread of new and novel viruses, the need to improve global population monitoring and enhance surveillance of infectious diseases is more pressing than ever.
Patty Kostkova (UCL) discusses how the real-time streams of user data generated on social networks like Twitter can be used for monitoring the health of large populations, providing a potential early warning function for pandemics, detecting flu spikes weeks before official surveillance systems. Watch Patty talk on this subject at the OII.
Communication of risk in any public health emergency is a complex task for healthcare agencies; a task made more challenging when citizens are bombarded with online information. Mexico City, 2009. Ed: Could you briefly outline your study? Patty: We investigated the role of Twitter during the 2009 swine flu pandemics from two perspectives. Ed: How difficult is this data to process? Patty: This is a fundamental question. . [1.] International Journal for Parasitology: Parasites and Wildlife Volume 2, December 2013, Networks and the ecology of parasite transmission: A framework for wildlife parasitology. Highlights Animal behaviour can generate heterogeneities in parasite transmission.
Network models represent these heterogeneities as links (edges) among hosts (nodes). Variety of lifecycles and transmission methods can be represented using networks. Framework for exploring a range of ecological questions about parasite transmission. Challenges remain in their application to wildlife parasitology. Journal of Biomedical Informatics Volume 54, April 2015, Utilizing social media data for pharmacovigilance: A review. Fig. 1 Sample search queries used for article retrieval from Medline.
Fig. 2 A framework for ADR detection and extraction from social media data. Highlights •We present a review of pharmacovigilance techniques from social media (SM) data. Abstract. Preventive Medicine Volume 67, October 2014 Online reports of foodborne illness capture foods implicated in official foodborne outbreak reports. CDC MMWR 15/08/14 Health Department Use of Social Media to Identify Foodborne Illness — Chicago, Illinois, 2013–2014. August 15, 2014 / 63(32);681-685 Jenine K.
Harris, PhD1, Raed Mansour, MS2, Bechara Choucair, MD2, Joe Olson3, Cory Nissen, MS3, Jay Bhatt, DO2 (Author affiliations at end of text) An estimated 55 million to 105 million persons in the United States experience acute gastroenteritis caused by foodborne illness each year, resulting in costs of $2–$4 billion annually (1). NORTHWESTERN UNIVERSITY, EVANSTON - AOUT 2013 - Detecting and Tracking Disease Outbreaks by Mining Social Media Data. PEDIATRICS 05/05/14 Social Media Methods for Studying Rare Diseases. Epidemics Volume 10, March 2015 Eight challenges for network epidemic models. Open Access Highlights Modelling transmission through networks is challenging.
We overview most of the outstanding open problems. We identify topics ranging from theoretical to applied ends of modelling spectrum. Abstract Networks offer a fertile framework for studying the spread of infection in human and animal populations. Keywords Infectious disease models; Transmission dynamics; Contact networks; Random graphs; Dynamic networks; Control measures. BLOG BMJ 05/01/15 Social media during epidemics: a poisoned chalice? 5 Jan, 15 | by Claire Bower, Digital Comms Manager, @clairebower Social networking is now the most popular online activity worldwide. Social networking sites account for nearly 1 in every 5 minutes spent online globally, reaching 82 percent of the world’s Internet population. As such, sites such as Facebook and Twitter have become an unavoidable part of crisis communication. However, opinion is mixed as to whether this pervasiveness is a blessing or a curse to organisations charged with protecting public health. The very attributes that make social media invaluable to communicators (instantaneous, wide-reaching) also make it incredibly difficult to control and moderate.
One concern about social media is that it has the potential to generate and perpetuate rumour. Trying to stem the spread of incorrect information online shares many similarities with containing a virus in the real world. MEDPAGETODAY 02/04/14 Social Media and Disease: There's an App for That. Can social media help detect and track infectious disease outbreaks? Well, there's an app for that. In fact, there are several -- and more on the way. Call it the crowd-sourcing of epidemiology. "We're putting the public into public health," says Mark Smolinski, MD, director of global health threats for the San Francisco-based Skoll Global Threats Fund.
Smolinski was talking about Flu Near You, his organization's Web- and smartphone-based app that asks people to report their flu symptoms -- or lack thereof -- on a weekly basis. But in an age of constant online chatter, he could have been talking about a host of projects that aim to cull useful information from all the gossip. American Journal of Public Health - JULY 2010 - The Next Public Health Revolution: Public Health Information Fusion and Social Networks.
JOURNAL OF MEDICAL INTERNET RESEARCH - 2013 - Scoping Review on Search Queries and Social Media for Disease Surveillance: A Chronology of Innovation. Introduction Social media and search behavior produce vast new data sources of largely untapped scientific potential. The threat of a global pandemic posed by outbreaks of influenza H5N1 (1997) and Severe Acute Respiratory Syndrome (SARS, 2002), both diseases of zoonotic origin, provoked interest in improving early warning systems and reinforced the need for combining data from different sources. PLOS 02/06/14 The Contribution of Social Networks to the Health and Self-Management of Patients with Long-Term Conditions: A Longitudinal Study. Abstract Evidence for the effectiveness of patient education programmes in changing individual self-management behaviour is equivocal. More distal elements of personal social relationships and the availability of social capital at the community level may be key to the mobilisation of resources needed for long-term condition self-management to be effective.
Aim. NATURE 13/08/14 Online collaboration: Scientists and the social network. In 2011, Emmanuel Nnaemeka Nnadi needed help to sequence some drug-resistant fungal pathogens. A PhD student studying microbiology in Nigeria, he did not have the expertise and equipment he needed. So he turned to ResearchGate, a free social-networking site for academics, and fired off a few e-mails. When he got a reply from Italian geneticist Orazio Romeo, an international collaboration was born. Over the past three years, the two scientists have worked together on fungal infections in Africa, with Nnadi, now at Plateau State University in Bokkos, shipping his samples to Romeo at the University of Messina for analysis.
“It has been a fruitful relationship,” says Nnadi — and they have never even met. PLOS 05/10/15 Using Social Media for Actionable Disease Surveillance and Outbreak Management: A Systematic Literature Review. Methods This systematic review builds upon the preferred reporting items outlined in the PRISMA Statement in effort to properly assess the quality and quantity of health-related research using social media analytics for active surveillance, S1 Checklist. A social media application was defined for this review as, “an Internet-based application where people can communicate and share resources and information, and where users can activate and set their own profiles, have the ability to develop and update them constantly, and have the opportunity to make such profiles totally or partially public and linked with other profiles in a network.”
CDC EID – NOV 2015 – Au sommaire notamment: Use of Internet Search Queries to Enhance Surveillance of Foodborne Illness ; Gyung Jin Bahk , Yong Soo Kim, and Myoung Su Park Author affiliations: Kunsan National University, Gunsan, South Korea (G.J. Bahk, M.S. Park); Korea Health Industry Development Institute, Cheongwon, South Korea (Y.S. Kim) Suggested citation for this article. INRA 30/07/15 Un tweet, un post, ça vous parle ? A l’heure où les réseaux sociaux prennent une place de plus en plus importante dans la société, la recherche n’est pas en reste !
BLOG PLOS 29/01/15 Researchers Changing the Way We Respond to Epidemics with Wikipedia and Twitter. “A global disease-forecasting system will change the way we respond to epidemics.” Dr. Sara Del Valle, Los Alamos National Laboratory. Papers in Physics, - 2013 - Epidemics on social networks. PLOS 30/10/14 Internet and Free Press Are Associated with Reduced Lags in Global Outbreak Reporting. Am. J. Epidemiol. (2013) 178 (11): The Impact of Illness on Social Networks: Implications for Transmission and Control of Influe. CDC 25/11/13 CDC Competition Encourages Use of Social Media to Predict Flu. November 25, 2013 — CDC has launched the “Predict the Influenza Season Challenge,” a competition designed to foster innovation in flu activity modeling and prediction. UN GLOBAL PULSE 20/05/14 Can We Use Social Media For Disease Surveillance? Skip to main content Subscribe to our newsletter. INTERNET RESEARCH - 2013 - The power of prediction with social media. ARXIV 11/09/13 Containing epidemic outbreaks by message-passing techniques.
CSIRO 10/10/12 Emergency Situation Awareness tool for social media. A fire researcher observes a grass fire. European Journal of Epidemiology (2006) 21: 103–111 Feasibility of using web-based questionnaires in large population-based epid. PLOS 18/07/11 Community Structure in Social Networks: Applications for Epidemiological Modelling. During an infectious disease outbreak people will often change their behaviour to reduce their risk of infection. Furthermore, in a given population, the level of perceived risk of infection will vary greatly amongst individuals. J Health Med Inform 2012, 3:4 Mining Social Media and Web Searches for Disease Detection.
Interdisciplinary Perspectives on Infectious Diseases Volume 2011 (2011) Pathogens, Social Networks, and the Paradox of Transmis. CONSOMMATEURS (perception des risques, baromètres) Réseaux sociaux et alimentation. EPJ Data Science 2013, 2:4 The Dynamics of Health Behavior Sentiments on a Large Online Social Network. PLOS 22/10/14 The Use of Google Trends in Health Care Research: A Systematic Review.
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.