laser.measles.components.base_vital_dynamics

laser.measles.components.base_vital_dynamics

laser.measles.components.base_vital_dynamics.BaseVitalDynamicsParams

Bases: BaseModel

Parameters specific to vital dynamics.

laser.measles.components.base_vital_dynamics.BaseVitalDynamicsProcess(model, verbose=False, params=None)

Bases: BasePhase, ABC

Phase for simulating the vital dynamics in the model with MCV1.

This phase handles the simulation of births and deaths in the population model along with routine vaccination (MCV1).

.. warning::

The ``mcv1`` scenario parameter **only vaccinates newborns** at each tick.
It does **not** immunize the existing population. In short simulations
(< 5 years), this produces negligible population-level immunity changes.

To model a population with pre-existing vaccine-derived immunity, either:

- Use ``InitializeEquilibriumStatesProcess`` to set an appropriate S/R
  split at the start of the simulation, or
- Directly set ``states.S`` and ``states.R`` before running.
- Use ``SIACalendarProcess`` for discrete campaign-based vaccination.

See the *Vaccination Modeling* tutorial (``docs/tutorials/tut_vaccination.py``)
for detailed examples of each approach.

Parameters

model : object The simulation model containing nodes, states, and parameters verbose : bool, default=False Whether to print verbose output during simulation params : VitalDynamicsParams | None, default=None Component-specific parameters. If None, will use default parameters

Notes

• Birth rates are calculated per tick
• MCV1 coverage is applied only to newborns; expect 5-10+ years of simulation time before routine immunization significantly shifts population-level immunity

laser.measles.components.base_vital_dynamics.BaseVitalDynamicsProcess.lambda_birth property

birth rate per tick

laser.measles.components.base_vital_dynamics.BaseVitalDynamicsProcess.mu_death property

death rate per tick

laser.measles.components.base_vital_dynamics.BaseVitalDynamicsProcess.calculate_capacity(model) abstractmethod

Calculate the capacity of the model.