tlo.methods.measles module

class Measles(name=None, resourcefilepath=None)[source]

This module represents measles infections and disease.

Bases: tlo.core.Module

PARAMETERS:

Item

Type

Description

beta_baseline

REAL

Baseline measles transmission probability

beta_scale

REAL

Scale value for measles transmission probability sinusoidal function

phase_shift

REAL

Phase shift for measles transmission probability sinusoidal function

period

REAL

Period for measles transmission probability sinusoidal function

vaccine_efficacy_1

REAL

Efficacy of first measles vaccine dose against measles infection

vaccine_efficacy_2

REAL

Efficacy of second measles vaccine dose against measles infection

prob_severe

REAL

Probability of severe measles infection, requiring hospitalisation

risk_death_on_treatment

REAL

Risk of scheduled death occurring if on treatment for measles complications

symptom_prob

DATA_FRAME

Probability of each symptom with measles infection

case_fatality_rate

DICT

Probability that case of measles will result in death if not treated

PROPERTIES:

Item

Type

Description

me_has_measles

BOOL

Measles infection status

me_date_measles

DATE

Date of onset of measles

me_on_treatment

BOOL

Currently on treatment for measles complications

Class attributes:

CAUSES_OF_DEATH : {‘Measles’: <tlo.methods.causes.Cause object at 0x130c4cad0>}

CAUSES_OF_DISABILITY : {‘Measles’: <tlo.methods.causes.Cause object at 0x130c4cbd0>}

INIT_DEPENDENCIES : {‘SymptomManager’, ‘HealthSystem’, ‘Demography’}

METADATA : {<Metadata.USES_SYMPTOMMANAGER: 2>, <Metadata.DISEASE_MODULE: 1>, <Metadata.USES_HEALTHBURDEN: 4>, <Metadata.USES_HEALTHSYSTEM: 3>}

OPTIONAL_INIT_DEPENDENCIES : {‘HealthBurden’}

Functions (defined or overridden in class Measles):

__init__(name=None, resourcefilepath=None)[source]

Construct a new disease module ready to be included in a simulation.

Initialises an empty parameters dictionary and module-specific random number generator.

Parameters:

name – the name to use for this module. Defaults to the concrete subclass’ name.

read_parameters(data_folder)[source]

Read parameter values from file

pre_initialise_population()[source]

Carry out any work before any populations have been initialised

This optional method allows access to all other registered modules, before any of the modules have initialised a population. This is expected to be useful for when a module’s properties rely upon information from other modules.

initialise_population(population)[source]

Set our property values for the initial population. set whole population to measles-free for 1st jan

initialise_simulation(sim)[source]

Schedule measles event to start straight away. Each month it will assign new infections

on_birth(mother_id, child_id)[source]

Initialise our properties for a newborn individual assume all newborns are uninfected

Parameters:
  • mother_id – the ID for the mother for this child

  • child_id – the ID for the new child

report_daly_values()[source]
process_parameters()[source]

Process the parameters (following being read-in) prior to the simulation starting. Make self.symptom_probs to be a dictionary keyed by age, with values of dictionaries keyed by symptoms and the probability of symptom onset.

class MeaslesEvent(module)[source]

MeaslesEvent runs every month and creates a number of new infections which are scattered across the month. * Seasonality is captured by the risk of infection changing according to the month. * Vaccination lowers an individual’s likelihood of getting the infection (one dose will be 85% protective and two

doses will be 99% protective).

Bases: tlo.events.RegularEvent, tlo.events.Event, tlo.events.PopulationScopeEventMixin

Class attributes:

__annotations__ : {}

Functions (defined or overridden in class MeaslesEvent):

__init__(module)[source]

Create a new regular event.

Parameters:
  • module – the module that created this event

  • frequency (pandas.tseries.offsets.DateOffset) – the interval from one occurrence to the next (must be supplied as a keyword argument)

apply(population)[source]

Apply this event to the given target.

This is a no-op; subclasses should override this method.

Parameters:

target – the target of the event

class MeaslesOnsetEvent(module, person_id)[source]

Bases: tlo.events.Event, tlo.events.IndividualScopeEventMixin

Functions (defined or overridden in class MeaslesOnsetEvent):

__init__(module, person_id)[source]

Create a new event.

Note that just creating an event does not schedule it to happen; that must be done by calling Simulation.schedule_event.

Parameters:
  • module – the module that created this event. All subclasses of Event take this as the first argument in their constructor, but may also take further keyword arguments.

  • priority – a keyword-argument to set the priority (see Priority enum)

apply(person_id)[source]

Onset a case of Measles

assign_symptoms(_age)[source]

Assign symptoms for this case and returns the date on which symptom onset. (Parameter values specify that everybody gets rash, fever and eye complain.)

get_prob_death(_age)[source]

Returns the probability of death for this person based on their age and whether they have untreated HIV.

class MeaslesSymptomResolveEvent(module, person_id)[source]

Bases: tlo.events.Event, tlo.events.IndividualScopeEventMixin

Functions (defined or overridden in class MeaslesSymptomResolveEvent):

__init__(module, person_id)[source]

Create a new event.

Note that just creating an event does not schedule it to happen; that must be done by calling Simulation.schedule_event.

Parameters:
  • module – the module that created this event. All subclasses of Event take this as the first argument in their constructor, but may also take further keyword arguments.

  • priority – a keyword-argument to set the priority (see Priority enum)

apply(person_id)[source]

this event is called by MeaslesOnsetEvent and HSI_Measles_Treatment

class MeaslesDeathEvent(module, person_id)[source]

Performs the Death operation on an individual and logs it.

Bases: tlo.events.Event, tlo.events.IndividualScopeEventMixin

Functions (defined or overridden in class MeaslesDeathEvent):

__init__(module, person_id)[source]

Create a new event.

Note that just creating an event does not schedule it to happen; that must be done by calling Simulation.schedule_event.

Parameters:
  • module – the module that created this event. All subclasses of Event take this as the first argument in their constructor, but may also take further keyword arguments.

  • priority – a keyword-argument to set the priority (see Priority enum)

apply(person_id)[source]

Apply this event to the given target.

Must be implemented by subclasses.

Parameters:

target – the target of the event

class HSI_Measles_Treatment(module, person_id)[source]

Health System Interaction Event It is the event when a person with diagnosed measles receives treatment

Bases: tlo.methods.healthsystem.HSI_Event, tlo.events.IndividualScopeEventMixin

Functions (defined or overridden in class HSI_Measles_Treatment):

__init__(module, person_id)[source]

Create a new event.

Note that just creating an event does not schedule it to happen; that must be done by calling Simulation.schedule_event.

Parameters:

module – the module that created this event. All subclasses of Event take this as the first argument in their constructor, but may also take further keyword arguments.

apply(person_id, squeeze_factor)[source]

Apply this event to the population.

Must be implemented by subclasses.

did_not_run()[source]

Called when this event is due but it is not run. Return False to prevent the event being rescheduled, or True to allow the rescheduling. This is called each time that the event is tried to be run but it cannot be.

class MeaslesLoggingEvent(module)[source]

Bases: tlo.events.RegularEvent, tlo.events.Event, tlo.events.PopulationScopeEventMixin

Class attributes:

__annotations__ : {}

Functions (defined or overridden in class MeaslesLoggingEvent):

__init__(module)[source]

Create a new regular event.

Parameters:
  • module – the module that created this event

  • frequency (pandas.tseries.offsets.DateOffset) – the interval from one occurrence to the next (must be supplied as a keyword argument)

apply(population)[source]

Log Summary Statistics Monthly

class MeaslesLoggingFortnightEvent(module)[source]

Bases: tlo.events.RegularEvent, tlo.events.Event, tlo.events.PopulationScopeEventMixin

Class attributes:

__annotations__ : {}

Functions (defined or overridden in class MeaslesLoggingFortnightEvent):

__init__(module)[source]

Create a new regular event.

Parameters:
  • module – the module that created this event

  • frequency (pandas.tseries.offsets.DateOffset) – the interval from one occurrence to the next (must be supplied as a keyword argument)

apply(population)[source]

Log Summary Statistics Every Two Weeks

class MeaslesLoggingAnnualEvent(module)[source]

Bases: tlo.events.RegularEvent, tlo.events.Event, tlo.events.PopulationScopeEventMixin

Class attributes:

__annotations__ : {}

Functions (defined or overridden in class MeaslesLoggingAnnualEvent):

__init__(module)[source]

Create a new regular event.

Parameters:
  • module – the module that created this event

  • frequency (pandas.tseries.offsets.DateOffset) – the interval from one occurrence to the next (must be supplied as a keyword argument)

apply(population)[source]

Log Summary Statistics Annually