  Contemporary Epidemiological Surveillance (ES) relies heavily on data
analytics. These analytics are critical input for pandemics preparedness
networks; however, this input is not integrated into a form suitable for
decision makers or experts in preparedness. A decision support system (DSS)
with Computational Intelligence (CI) tools is required to bridge the gap
between epidemiological model of evidence and expert group decision. We argue
that such DSS shall be a cognitive dynamic system enabling the CI and human
expert to work together. The core of such DSS must be based on machine
reasoning techniques such as probabilistic inference, and shall be capable of
estimating risks, reliability and biases in decision making.

Artificial Intelligence;Social and Information Networks