Many factors in today’s changing societies contribute towards the continuous emergence of infectious diseases. Demographic change, globalization, bioterrorism, compounded with the resilient nature of viruses and diseases such as SARS and avian influenza have raised awareness for European society’s increasing vulnerability. Traditional Epidemic Intelligence systems are designed to identify potential health threats, and rely upon data transmissions from laboratories or hospitals. They can be used to recognise long-term trends, but are limited in several ways. Threats, such as SARS, can go unrecognised since the signals indicating its existence may originate from sources other than the traditional ones. Second, a critical strategy for circumventing devastating public health events is early detection and early response. Conflictingly, the time with which information propagates through the traditional channels, can undermine time-sensitive strategies. Finally, traditional systems are well suited for recognising indicators for known diseases, but are not well designed for detecting those that are emerging. Faced with these limitations, traditional systems need to be complemented with additional approaches which are better targeted for the early detection of emerging threats. The Medical EcoSystem (M-Eco) project, will address these limitations by using Open Access Media and User Generated Content, as unofficial information sources for Epidemic Intelligence. This type of content has transformed the manner in which information propagates across the globe. Based on this, M-Eco will develop an Event-Based Epidemic Intelligence System which integrates unofficial and traditional sources for the early detection of emerging health threats. M-Eco will emphasize adaptivity and personalized filtering so that relevant signals can be detected for targeting the needs of public health officials who have to synthesize facts, assess risks and react to public health threats.

Description in Czech
Many factors in today’s changing societies contribute towards the continuous emergence of infectious diseases. Demographic change, globalization, bioterrorism, compounded with the resilient nature of viruses and diseases such as SARS and avian influenza have raised awareness for European society’s increasing vulnerability. Traditional Epidemic Intelligence systems are designed to identify potential health threats, and rely upon data transmissions from laboratories or hospitals. They can be used to recognise long-term trends, but are limited in several ways. Threats, such as SARS, can go unrecognised since the signals indicating its existence may originate from sources other than the traditional ones. Second, a critical strategy for circumventing devastating public health events is early detection and early response. Conflictingly, the time with which information propagates through the traditional channels, can undermine time-sensitive strategies. Finally, traditional systems are well suited for recognising indicators for known diseases, but are not well designed for detecting those that are emerging. Faced with these limitations, traditional systems need to be complemented with additional approaches which are better targeted for the early detection of emerging threats. The Medical EcoSystem (M-Eco) project, will address these limitations by using Open Access Media and User Generated Content, as unofficial information sources for Epidemic Intelligence. This type of content has transformed the manner in which information propagates across the globe. Based on this, M-Eco will develop an Event-Based Epidemic Intelligence System which integrates unofficial and traditional sources for the early detection of emerging health threats. M-Eco will emphasize adaptivity and personalized filtering so that relevant signals can be detected for targeting the needs of public health officials who have to synthesize facts, assess risks and react to public health threats.

Keywords
Public Health Event Detection, Personalization, User
Generated Content

247829

English

Smrž Pavel, doc. RNDr., Ph.D. - principal person responsible

Department of Computer Graphics and Multimedia
- responsible department (27.1.2010 - not assigned)

Responsibility: Smrž Pavel, doc. RNDr., Ph.D.