laser.generic.vitaldynamics

laser.generic.vitaldynamics

laser.generic.vitaldynamics.BirthsByCBR(model, birthrates, pyramid, track=True, validating=False)

Component to model births based on crude birth rates (CBR).

On each tick, selects the number of agents to be born in each node based on the CBR for that tick and the total population at that tick.

\(\#births = Poisson (N \times ((1 + \frac {CBR} {1000})^{\frac {1} {365}} - 1))\)

Newborns are added to the susceptible state by default. Calls the on_birth() method of other components in the model, if they implement it, with the indices of the newborn agents. Optionally tracks date of birth (dob) for individuals which may be required for other components (see MortalityByEstimator) or otherwise useful, e.g., age-based intervention targeting.

Parameters:

Name	Type	Description	Default
model	Model	The simulation model instance.	required
birthrates	ndarray	Array of crude birth rates (per 1000 per year) for each time step.	required
pyramid	AliasedDistribution	Age pyramid data structure for sampling dates of birth.	required
track	bool	Whether to track date of birth (dob) for individuals. Default is True.	True
validating	bool	Whether to enable validation checks. Default is False.	False

laser.generic.vitaldynamics.ConstantPopVitalDynamics(model, recycle_rates, dobs=False, mappings=None, validating=False)

Component to model vital dynamics with constant population via recycling - agents are returned to the susceptible state and, optionally, given a new date of birth.

On each tick, probabilistically "recycles" agents (resets state to susceptible and optionally resets dob) based on the CDR for that tick and the total population at that tick.

\(p(recycle) = 1 - e^{1 - (1 - \frac {rate} {1000})^{\frac {1} {365}}}\)

Uses a mapping of (state_value, state_name) tuples to decrement counts in the specified states when individuals die. The default mapping is for 'S', 'E', 'I', and 'R' states.

Optionally tracks date of birth (dob) for individuals which may be useful, e.g., age-based intervention targeting or age-at-infection tracking.

Parameters:

Name	Type	Description	Default
model	Model	The simulation model instance.	required
recycle_rates	ndarray	Array of recycling rates (per 1000 per year) for each time step.	required
dobs	bool	Whether to track date of birth (dob) for recycled individuals. Default is False.	False
mappings	list of tuples	Optional list of (state_value, state_name) tuples to map states for recycling. 'S', 'E', 'I', 'R' by default.	None
validating	bool	Whether to enable validation checks. Default is False.	False

laser.generic.vitaldynamics.MortalityByCDR(model, mortalityrates, mappings=None, validating=False)

Component to model mortality based on crude death rates (CDR).

On each tick, probabilistically "recycles" agents based on the CDR for that tick and the total population at that tick.

\(p(death) = 1 - e^{1 - (1 - \frac {CDR} {1000})^{\frac {1} {365}}}\)

Uses a mapping of (state_value, state_name) tuples to decrement counts in the specified states when individuals die. The default mapping is for 'S', 'E', 'I', and 'R' states.

Parameters:

Name	Type	Description	Default
model	Model	The simulation model instance.	required
mortalityrates	ndarray	Array of crude death rates (per 1000 per year) for each time step.	required
mappings	list of tuples	Optional list of (state_value, state_name) tuples to map states for decrementing counts.	None
validating	bool	Whether to enable validation checks. Default is False.	False

laser.generic.vitaldynamics.MortalityByEstimator(model, estimator, mappings=None, validating=False)

Component to model mortality based on a life table estimator.

Uses a Kaplan-Meier or other estimator to sample dates of death for individuals based on their date of birth. At initialization, samples dates of death for all individuals in the population based on their initial age. Requires that individuals have a 'dob' property. At each tick, individuals whose date of death is equal to the current tick are marked as deceased. Uses a mapping of (state_value, state_name) tuples to decrement counts in the specified states when individuals die. The default mapping is for 'S', 'E', 'I', and 'R' states. Implements an on_birth() method to sample dates of death for newborn individuals.

Parameters:

Name	Type	Description	Default
model	Model	The simulation model instance.	required
estimator	KaplanMeierEstimator	Life table estimator instance with a method to sample dates of death.	required
mappings	list of tuples	Optional list of (state_value, state_name) tuples to map states for decrementing counts. 'S', 'E', 'I', 'R' by default.	None
validating	bool	Whether to enable validation checks. Default is False.	False