Despite ~100 years of reseach we lack a good quantitiative understanding of our defese system against pathogens – the immune system. Complementary to in vivo studies and in vitro experiments, **in silico** **experiments** (computer simulations) provide an important tool to gain insight into the dynamics of the immune system of both healthy and infected individuals. A slight dysbalance in the numbers game between an invading pathogen and immune effectors may determine whether or not a host survives an infection or how severe the outcome of a disease will be.

Example (B cell dynamics)How many B-cells circulate within an adult individual? What is the daily tunover (assuming 10% turnover per day)? What is the tunover per second (assuming 1 day has 10e5 seconds)? What is the total weight of B-cells (assuming 2×10e-10 g per cell)? What is the weight of the daily replenished B-cells? What is the weight of B-cells fighting a pathogen (peak of acute infection)? How many sugar cubes does this correspond to (1 sugar cube = 4g)? * This corresponds to the weight of two standard Swiss chocolat bars (100g each). | >10e12 B cells>10e11 B cells >10e06 B cells ~200 g* ~20 g ~10 g ~2 ½ | |||

Spatial infection dynamics of virus (left) and virus-specific immune effectors (right). Solide line: no spatial coupling, dashed line: with spatial coupling.

For details, please consult: Funk et al., 2005, J Theor Biol