  The aim of this work was to show few examples and few perspective of modeling
in epidemiology. We began with differential equations which were a first tool
to describe and predict that phenomena. Wroclaw as a cite was very important,
because statistics from smallpox epidemic were used by Bernoulli to estimate
parameters of first mathematical model of epidemic. Next step were SIR models
and those also appeared first as differential equations. They were very popular
in begin of XX century. When computer simulation changed the world of
mathematical modeling agent-based models gave more possibilities in
epidemiology. That models have a big privilege on differential equation,
because of information of social network people habits and reaction on
infections, which can me involved in agent-based models as well as governmental
intervention. We showed in this work how that human relations are important in
transmitting diseases and there is example, where it is possible to conduct
experiments of significant policy relevance (vaccinating), such as
investigating the initial growth of an epidemic on a real-world network.
Presented H1N1 model could be observed in real time (prediction was made in
September 2009 for winter season 2009/2010) what make it more exiting and also
practice.
