Pyfectious: An individual-level simulator to discover optimal containment policies for epidemic diseases
Fig 7
Simulator’s clock is translated to Virus Spread Events indicated by yellow circles on the timeline axis.
In (a) and (b) two characteristically similar simulators’ timelines are displayed that only differ in their clock periods (T1 for (a) and T2 for (b)). If the probability of transmission in a single clock trigger is p, the probability of disease transmission for the whole time is a geometric distribution with parameters equal to (p, ⌊t/T⌋), where T is the clock period. The probability of disease not being transmitted is shown above the axes for a simple interaction between two individuals. In order to have consistent results for both similar simulators with different resolutions, the mentioned probabilities should be equal to each other for the simulators. In other words, (1 − p1)⌊t/T1⌋ = (1−p2)⌊t/T2⌋. For better illustration, in this plot the virus spread events are placed exactly at the ends of the intervals; but in simulations, they are uniformly distributed within each interval.