Serialized population file

To model a population with endemic disease, you cannot use a common modeling technique in which you introduce a disease outbreak to a naive population and analyze the immediate aftermath. Instead, you must run the simulation for a period of time until the disease dynamics reach an equilibrium (aside from stochastic noise). This is known as steady state. The simulation output prior to that point is disregarded. This is a modeling concept known as simulation burn-in, borrowed from the electronics industry where the first items produced by a manufacturing process are discarded before the process is applied.

However, the time necessary to run simulations until this point can be significant, especially for large populations. Indeed, for endemic disease present at low absolute prevalence, you should simulate a larger population size that allows a small number of infected individuals to be represented.

EMOD avoids the need to run the burn-in period again and again with each simulation by using serialization to save the population state after it reaches equilibrium. Then, when you want to begin a subsequent simulation investigating the outcome of a particular set of interventions, you can begin the simulation at that point rather than needing to re-run the burn-in period. You can serialize the population at multiple time steps during a simulation.

The serialized population files created are placed in the output directory and use the naming convention state-<timestep>.dtk. They are binary files that contain state information about every agent in a simulation: their health status, age, property values, and more. These files can be consumed by subsequent simulations to decrease run time.

Note

If you used repeating interventions during the burn-in period, those interventions will not continue based on the information in the serialized population file. Check your campaign file for repeating interventions and reconfigure them as needed for the period after burn-in.

See Simulation setup parameters for more information.