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