Medical ecosystem – personalized event-based surveillance

Tthe M-Eco (Medical Ecosystem Personalized Event-Based Surveillance) project helped to complement traditional surveillance systems with additional approaches for the early detection of emerging threats.

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 addressed 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 developed an Event-Based Epidemic Intelligence System that integrates unofficial and traditional sources for the early detection of emerging health threats. M-Eco emphasized 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.

MMLAP and other EU Projects

Health system analysis to support capacity development in response to the threat of pandemic influenza in Asia
Making society an active participant in water adaptation to global change
Public Participation in Developing a Common Framework for Assessment and Management of Sustainable Innovation
Effective communication in outbreak management: development of an evidence-based tool for Europe
Developing the framework for an epidemic forecast infrastructure
European monitoring of excess mortality for public health action
Modelling the spread of pandemic influenza and strategies for its containment and mitigation
Cost-effectiveness assessment of european influenza human pandemic alert and response strategies
Bridging the gap between science, stakeholders and policy makers
Promotion of immunization for health professionals in Europe
Towards inclusive research programming for sustainable food innovations
Medical ecosystem – personalized event-based surveillance
Public Engagement with Research And Research Engagement with Society
Computing Veracity – the Fourth Challenge of Big Data
Transparent communication in Epidemics: Learning Lessons from experience, delivering effective Messages, providing Evidence