update_methods

class update_methods(year, eff=None, dur_use=None, p_use=None, method_mix=None, method_choice_pars=None, verbose=False, **kwargs)

Bases: Intervention

Intervention to modify method efficacy and/or switching matrix.

Parameters:

• year (float) – The year we want to change the method.

• eff (dict) –

  An optional key for changing efficacy; its value is a dictionary with the following schema:

  {method: efficacy}

  Where method is the name of the contraceptive method to be changed, and efficacy is a number with the efficacy

• dur_use (dict) –

  Optional key for changing the duration of use; its value is a dictionary with the following schema:

  {method: dur_use}

  Where method is the method to be changed, and dur_use is a dict representing a distribution, e.g. dur_use = {‘Injectables: dict(dist=’lognormal’, par1=a, par2=b)}

• p_use (float) – probability of using any form of contraception

• method_mix (list/arr) – probabilities of selecting each form of contraception

Attributes

auto_state_list	List of "automatic" states with boolean type (ss.BoolState) that were added via define_states()
dt	Get the current module timestep
has_product	Check if the intervention has a product
now	Shortcut to self.t.now()
state_dict	Return a flat dictionary (objdict) of all states
state_list	Return a flat list of all states (ss.Arr objects)
ti	Get the current module timestep
timevec	Shortcut to self.t.timevec

Methods

step()

Applies the efficacy or contraceptive uptake changes if it is the specified year based on scenario specifications.