Epidemiological Modelling, Surveillance and Web-Based Information Systems: Tools for Public Health Decision Making

The current threat of pandemic influenza, and recent threats such as SARS raise major public health concerns and urge to preparedness, risk assessment and management. Epidemiological models have become important tools in analyzing the spread and control of these threats and assist decision makers in taking proper prevention measures. The use of mathematical models in conjunction with surveillance in planning, implementing and evaluating various detection, prevention and control programs, is of importance for public health decision makers. Web-based medical information systems provide an additional valuable source of information especially with respect to fast identification of an emerging infectious disease outbreak. Public health surveillance systems provide the bulk of the information about incidence, case-fatality rates, age structure of the population, susceptible population groups, geographical distribution of incidence, etc., which is expected to be reliable and precise. However, in a crisis situation, national public health surveillance systems may face conditions where their structure and design may fail to provide the right information when needed. During a public health crisis situation where infectious diseases are characterized by high transmission probability in time and space information from other sources than surveillance can be useful. Web-based information system can retrieve information fast from a variety of web sources. Although the accuracy of this information is limited it can be of interest by providing valuable signals regarding the spread of the epidemic. Epidemiological modelling approaches are part of the quantitative risk assessment and risk management process of an epidemic. Modelling tools can utilise the information provided by surveillance and web-based medical systems and run scenarios on questions such as how the outbreak is going to develop. In particular, real-time models are useful in monitoring hospital capacity, checking health care system resilience, assessing logistical demand such as antiviral stockpile and delivery, and providing evidence whether control methods works as expected and adjust plans. For that purpose future incidence and key previously unknown parameters need to be predicted. These predictions rely on the quality of the supporting input information from the data systems. Modelling in conjunction with surveillance and web-based medical information systems are important tools for public health decision making during epidemics and pandemics. The establishment of the necessary infrastructure, which will be able to provide fast collection and dissemination of the relevant information requires enormous preparedness efforts at the national and the European level.-JRC.G.2-Support to external securit